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The following is a conversation with Michael Levin, one of the most fascinating and brilliant biologists I ve ever talked to.
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He and his lab at Tufts University works on novel ways to understand and control complex pattern formation in biological systems.
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Andrej Karpathy, a world-class AI researcher, is the person who first introduced me to Michael Levin s work.
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I bring this up because these two people make me realize that biology has a lot to teach us about AI, and AI might have a lot to teach us about biology.
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And now, a quick two-second mention of each sponsor.
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Check them out in the description.
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It s the best way to support this podcast.
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We got Henson Shaving for a great razor and shave, Aidsleep for e-commerce, Element for on-the-go electrolytes, and Insight Tracker for biological tracking.
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Choose wisely, my friends.
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And now, onto the full ad reads.
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Never ads in the middle.
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Those suck.
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I try to make these ads here interesting.
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So they re worth listening to perhaps, mostly because a lot of them don t have anything to do with a sponsor, they re almost like inspired by the sponsor.
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But if you still must skip, please check out the sponsors.
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They re the reason I m able to do this podcast, so please support them in any way you can.
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I enjoy their stuff, maybe you will too.
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This show is brought to you by Henson Shaving, a family-owned aerospace manufacturer bringing precision engineering to your shaving experience.
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You had me at engineering.
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If there s any word a person can state to me that, you know, I was gonna say turns me on a little bit, but that would be very inappropriate to do an ad read, so I would never say the thing like that.
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But anyway, I find engineering just...
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in all of its forms.
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Materials engineering, mechanical engineering, civil engineering, all of it.
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I love it.
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They re using aerospace grade CNC machines and because of that are able to make metal razors that extend just .0013 inches, which is less than the thickness of a human hair.
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and the precision of it is the reason you can have a safe, clean, smooth shave.
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Check them out at hensonshaving.com to pick your razor and use code LEX and you ll get 100 free blades with your razor.
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You must add both the 100 blade pack and the razor for the discount to apply.
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This episode is also brought to you by Eight Sleep and its new Pond 3 mattress.
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It is a source of happiness for me.
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Naps bring joy to my heart.
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They put to rest all the anxiety, the uncertainty, the sadness, the melancholy that I have on my heart.
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They let that fade and the phoenix rises from the ashes of the nap.
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and a cool surface of the bed with a warm blanket.
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I just love it.
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It s usually gonna be about 20 to 30 minute nap.
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Cures all ills.
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I can have so much uncertainty, so much fear, so much anxiety about the world and just a little nap or insecurity.
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all of it, a nap can cure it.
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And maybe that s a gift, maybe that s a chemical gift for me.
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I m so fortunate not to suffer from sort of chemical depression that can hold you down for many days, weeks, or months.
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For me, a nap can cure so much and it s beautiful.
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I mean, sleep is so, so important.
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So I highly recommend Eight Sleep.
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It s been, like I said, a source of a lot of happiness for me.
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Check it out and get special savings when you go to eightsleep.com slash life.
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This episode is also brought to you by Element Electrolyte Drink Mix, spelled L-M-N-T.
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I like their watermelon salt one, but lately I ve also been consuming some of the chocolate mint.
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I have a question mark on that.
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I don t remember if that s what that is, but it s what it tastes like, and it s delicious, but it s a different, it s kind of a different thing.
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Nutritionally, it s the same thing, but spiritually, it s a different thing.
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So watermelon salt is more what I m just trying to add a little, like, kick to my water, right, and making sure I m getting all the sodium, potassium, magnesium right for the low-carb stuff I m doing, but.
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The chocolate one has a little, I don t wanna say sweetness, but a little more complexity in the way chocolate does, right?
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And so I feel like it s the thing that relaxes me a bit more.
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It s like a dessert at the end of the day.
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Anyway, get a sample pack for free with any purchase.
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Try it at drinkelement.com slash lex.
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This show is also brought to you by InsideTracker, a service I use to track the biological data from my body.
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They have a bunch of plans, most include a blood test that gives you a bunch of information that is then used by machine learning algorithms to use your blood data, DNA data, and fitness tracker data to make recommendations for positive diet and lifestyle changes.
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Your body, as John Mayer has once said, is a wonderland.
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It s full of data, it s full of signals that it s sending to you.
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And the incredible aspect of our body is that it s able to integrate those signals to then maintain health, right?
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Now, we re creating a lot of medical tools and diet tools and all that kind of stuff that s able to extend the capabilities of our body, but it needs to know about those signals.
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It needs to know about the signals the body sends.
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It s obvious to me that this is the future of health and medicine and all that kind of stuff.
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Get special savings for a limited time when you go to insidetracker.com slash Lex.
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This is the Lex Friedman Podcast.
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To support it, please check out our sponsors in the description.
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And now, dear friends, here s Michael Levin.
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Embryogenesis is the process of building the human body from a single cell.
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I think it s one of the most incredible things that exists on Earth from a single embryo.
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So how does this process work?
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Yeah, it is an incredible process.
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I think it s maybe the most magical process there is.
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And I think one of the most fundamentally interesting things about it is that it shows that each of us takes the journey from so-called just physics to mind, right?
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Because we all start life as a single quiescent, unfertilized oocyte, and it s basically a bag of chemicals.
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And you look at that and you say, okay, this is chemistry and physics.
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And then nine months and some years later, you have an organism with high-level cognition and preferences and an inner life and so on.
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And what embryogenesis tells us is that that transformation from physics to mind is gradual.
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It s smooth.
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There is no special place where, you know, a lightning bolt says, boom, now you ve gone from physics to true cognition.
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That doesn t happen.
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And so we can see in this process that the whole mystery, you know, the biggest mystery of the universe, basically, how you get mind from matter.
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from just physics in quotes.
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So where s the magic to the thing?
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How do we get from information encoded in DNA and make physical reality out of that information?
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So one of the things that I think is really important if we re going to bring in DNA into this picture is to think about the fact that what DNA encodes is the hardware of life.
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DNA contains the instructions for the kind of micro-level hardware that every cell gets to play with.
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So all the proteins, all the signaling factors, the ion channels, all the cool little pieces of hardware that cells have, that s what s in the DNA.
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The rest of it is in so-called generic laws, and these are laws of mathematics, these are laws of computation, these are laws of physics, of all kinds of interesting things that are not directly in the DNA.
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And that process, you know, I think the reason I always put just physics in quotes is because I don t think there is such a thing as just physics.
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I think that
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thinking about these things in binary categories, like this is physics, this is true cognition, this is as if, it s only faking, all these kinds of things.
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I think that s what gets us in trouble.
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I think that we really have to understand that it s a continuum, and we have to work up the scaling, the laws of scaling, and we can certainly talk about that.
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There s a lot of really interesting thoughts to be had there.
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So the physics is deeply integrated with the information.
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So the DNA doesn t exist on its own.
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The DNA is integrated in some sense in response to the laws of physics at every scale, the laws of the environment it exists in.
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Yeah, the environment and also the laws of the universe.
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I mean, the thing about the thing about the DNA is that it s once evolution discovers a certain kind of machine, that if the physical implementation is appropriate, it s sort of, and this is hard to talk about, because we don t have a good vocabulary for this yet.
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But it s a very,
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um kind of a platonic notion that if the machine is there it pulls down interesting uh interesting things that you do not have to evolve from scratch because the laws of physics give it to you for free so just as a really stupid example if you re trying to evolve a particular triangle you can evolve the first angle and you evolve the second angle but you don t need to evolve the third you know what it is already now why do you know that s that s a gift for free from geometry in a particular space you know what that angle has to be
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and if you evolve an ion channel which is ion channels are basically transistors right they re voltage gated current conductances if you evolve that ion channel you immediately get to use things like truth tables you get logic functions you don t have to evolve the logic function you don t have to evolve a truth table it doesn t have to be in the dna
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you get it for free, right?
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And the fact that if you have NAND gates, you can build anything you want, you get that for free.
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All you have to evolve is that first step, that first little machine that enables you to couple to those laws.
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And there s laws of adhesion and many other things.
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And this is all that interplay between the hardware that s set up by the genetics and the software that s built, right?
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The physiological software that basically does all the computation and the cognition and everything else is a real interplay between
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the information in the DNA and the laws of physics of computation and so on.
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So is it fair to say, just like this idea that the laws of mathematics are discovered,
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they re latent within the fabric of the universe, in that same way the laws of biology are kind of discovered.
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Yeah, I think that s absolutely, and it s probably not a popular view, but I think that s right on the money, yeah.
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I think that s a really deep idea.
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Then embryogenesis is the process of revealing, of embodying, of manifesting these laws.
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You re not building the laws, you re just,
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creating the capacity to reveal.
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Yes, I think, again, not the standard view of molecular biology by any means, but I think that s right on the money.
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I ll give you a simple example, you know, some of our latest work with these xenobots, right?
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So what we ve done is to take some skin cells off of an early frog embryo and basically ask about their plasticity.
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If we give you a chance to sort of reboot your multicellularity in a different context, what would you do?
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Because
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what you might assume by the thing about embryogenesis is that it s super reliable right it s very robust and that really uh obscures some of its most interesting features we get used to it we get used to the fact that acorns make oak trees and frog eggs make frogs and we say well what else is it going to make that s what you know that s what it makes that s a standard story but the reality is and so and so you look at these um at these skin cells and you say well what do they know how to do well they know how to be a passive boring two-dimensional outer layer keeping the bacteria from getting into the embryo that s what they know how to do
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Well, it turns out that if you take these skin cells and you remove the rest of the embryo, so you remove all of the rest of the cells, and you say, well, you re by yourself now, what do you want to do?
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So what they do is they form this multi-little creature that runs around the dish.
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They have all kinds of incredible capacities.
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They navigate through mazes, they have various behaviors that they do both independently and together.
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They basically implement von Neumann s dream of self-replication, because if you sprinkle a bunch of loose cells into the dish, what they do is they run around, they collect those cells into little piles, they sort of mush them together until those little piles become the next generation of xenobots.
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So you ve got this machine that builds copies of itself from loose material in its environment.
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things that you would have expected from the frog genome.
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In fact, the genome is wild-typed.
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There s nothing wrong with their genetics.
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Nothing has been added, no nanomaterials, no genomic editing, nothing.
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And so what we have done there is engineer by subtraction.
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What you ve done is you ve removed the other cells that normally basically bully these cells into being skin cells.
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And you find out that what they really want to do is to be this, their default behavior is to be a xenobot.
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But in vivo, in the embryo, they get told to be skinned by these other cell types.
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And so now here comes this really interesting question that you just posed.
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when you ask where does the form of the tadpole and the frog come from the standard answer is well it s it s it s uh selection so over over millions of years right it s been shaped to to produce the specific body with that s fit for froggy environments where does the shape of the xenobot come from there s never been any xenobots there s never been selection to be a good xenobot these cells find themselves in the new environment in 48 hours they figure out how to be an entirely different
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a proto-organism with new capacities like kinematic self-replication.
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That s not how frogs or tadpoles replicate.
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We ve made it impossible for them to replicate their normal way.
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Within a couple days, these guys find a new way of doing it that s not done anywhere else in the biosphere.
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Well, actually, let s step back and define what are xenobots?
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So a xenobot is a self-assembling little proto-organism.
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It s also a biological robot.
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Those things are not distinct.
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It s a member of both classes.
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How much is it biology?
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How much is it robot?
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this point most of it is biology because what we re doing is we re discovering natural behaviors of these of these of the cells and also of the cell collectives now one of the really important parts of this was that we re working together with josh bongard s group at university of vermont they re computer scientists do ai
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and they ve basically been able to use an evolutionary, a simulated evolution approach to ask, how can we manipulate these cells, give them signals, not rewire their DNA, so not hardware, but experiences signals.
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So can we remove some cells?
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Can we add some cells?
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Can we poke them in different ways to get them to do other things?
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So in the future, there s going to be, you know, we re now, and this is future unpublished work, but we re doing all sorts of interesting ways to reprogram them to new behaviors.
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But before you can start to reprogram these things, you have to understand what their innate capacities are.
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Okay, so that means engineering, programming, you re engineering them in the future.
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And in some sense, the definition of a robot is something you in part engineer versus evolve.
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I mean,
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It s such a fuzzy definition anyway, in some sense, many of the organisms within our body are kinds of robots.
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And I think robots is a weird line, because we tend to see robots as the other.
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I think there will be a time in the future when there s going to be something akin to the civil rights movements for robots, but we ll talk about that later perhaps.
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Anyway.
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So how do you, can we just linger on it?
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How do you build a xenobot?
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What are we talking about here?
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From whence does it start and how does it become the glorious xenobot?
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Yeah, so just to take one step back, one of the things that a lot of people get stuck on is they say, well,
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you know, engineering requires new DNA circuits, or it requires new nanomaterials, you know, what the thing is, we re now moving from old school engineering, which use passive materials, right, that things like, you know, wood, metal, things like this, that basically, the only thing you could depend on is that they were going to keep their shape, that s it, they don t do anything else, you know, it s on you as an engineer to make them do everything they re going to do.
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And then there were active materials.
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And now computation materials, this is a whole new era, these are agential materials.
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You re now collaborating with your substrate because your material has an agenda.
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These cells have billions of years of evolution, they have goals, they have preferences, they re not just going to sit where you put them.
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That s hilarious that you have to talk your material into keeping its shape.
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That is exactly right.
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Stay there.
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It s like getting a bunch of cats or something and trying to organize the shape out of them.
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It s funny, we re on the same page here because in the paper, this is currently just been accepted in Nature by Engineering.
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One of the figures I have is building a tower out of Legos versus dogs, right?
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So think about the difference, right?
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If you build out of Legos, you have full control over where it s going to go.
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But if somebody knocks it over,
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It s game over.
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With the dogs, you cannot just come and stack them.
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They re not going to stay that way.
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But the good news is that if you train them, then somebody knocks it over, they ll get right back up.
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So as an engineer, what you really want to know is, what can I depend on this thing to do?
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A lot of people have definitions of robots as far as what they re made of or how they got here, design versus evolve, whatever.
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I don t think any of that is useful.
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I think, as an engineer, what you want to know is, how much can I depend on this thing to do when I m not around to micromanage it?
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what level of dependency can I give this thing?
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How much agency does it have?
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Which then tells you what techniques do you use.
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So do you use micromanagement, like you put everything where it goes?
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Do you train it?
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Do you give it signals?
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Do you try to convince it to do things, right?
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How intelligent is your substrate?
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And so now we re moving into this area where you re working with agential materials.
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That s a collaboration, that s not old style engineering.
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What s the word you re using, agential?
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Agential, yeah.
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What s that mean?
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Agency, it comes from the word agency.
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So basically the material has agency, meaning that
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It has some some level of, obviously not human level, but some level of preferences, goals, memories, ability to remember things, to compute into the future, meaning anticipate, you know, when you re working with cells, they have all of that to some to various degrees.
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Is that empowering or limiting, having material that has a mind of its own, literally?
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I think it s both, right?
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So it raises difficulties because it means that if you re using the old mindset, which is a linear kind of extrapolation of what s going to happen, you re going to be surprised and shocked all the time because biology does not do what we linearly expect materials to do.
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On the other hand, it s massively liberating.
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And so in the following way, I ve argued that advances in regenerative medicine require us to take advantage of this, because what it means is that you can get the material to do things that you don t know how to micromanage.
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So just as a simple example, right, if you had a rat,
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And you wanted this rat to do a circus trick, put a ball in the little hoop.
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You can do it the micromanagement way, which is try to control every neuron and try to play the thing like a puppet, right?
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And maybe someday that ll be possible, maybe.
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Or you can train the rat.
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And this is why humanity for thousands of years before we knew any neuroscience, we had no idea what s between the ears of any animal, we were able to train these animals.
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Because once you recognize the level of agency of a certain system,
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You can use appropriate techniques if you know the currency of motivation, reward, and punishment.
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You know how smart it is.
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You know what kinds of things it likes to do.
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You are searching a much smoother, much nicer problem space than if you try to micromanage the thing.
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And in regenerative medicine, when you re trying to get, let s say, an arm to grow back or an eye to repair a cell birth defect or something,
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Do you really want to be controlling tens of thousands of genes at each point to try to micromanage it?
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Or do you want to find the high-level modular controls that say, build an arm here?
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You already know how to build an arm.
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You did it before.
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Do it again.
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So I think it s both.
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It s both difficult and it challenges us to develop new ways of engineering.
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And it s hugely empowering.
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Okay, so how do you do, I mean, maybe sticking with the metaphor of dogs and cats, I presume you have to figure out the, find the dogs and dispose of the cats.
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Because, you know, it s like the old herding cats is an issue, so you may be able to train dogs.
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I suspect you will not be able to train cats.
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or if you do, you re never gonna be able to trust them.
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So is there a way to figure out which material is amenable to hurting?
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Is it in the lab work or is it in simulation?
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Right now it s largely in the lab because our simulations do not capture yet the most interesting and powerful things about biology.
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So the simulation, what we re pretty good at simulating are feed-forward emergent types of things,
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So cellular automata, if you have simple rules and you sort of roll those forward for every agent or every cell in the simulation, then complex things happen, ant colony algorithms, things like that.
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We re good at that and that s fine.
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The difficulty with all of that is that it s incredibly hard to reverse.
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So this is a really hard inverse problem.
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If you look at a bunch of termites and they make a thing with a single chimney and you say, well, I like it, but I d like two chimneys.
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How do you change the rules of behavior-free termites so they make two chimneys, right?
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Or if you say, here are a bunch of cells that are creating this kind of organism, I don t think that s optimal.
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I d like to repair that birth defect.
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How do you control all the individual low-level rules, right?
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All the protein interactions and everything else.
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Rolling it back from the anatomy that you want to the low-level hardware rules is, in general, intractable.
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It s an inverse problem.
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It s generally not solvable.
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So right now it s mostly in the lab, because what we need to do is we need to understand how biology uses top-down controls.
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So the idea is not bottom-up emergence, but the idea of things like goal-directed test-operate-exit kinds of loops, where it s basically an error minimization function over a new space.
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It s not a space of gene expression, but for example a space of anatomy.
1
SPEAKER_00
So just as a simple example, if you have a salamander, and it s got an arm, you can amputate that arm anywhere along the length.
1
SPEAKER_00
It will grow exactly what s needed, and then it stops.
1
SPEAKER_00
That s the most amazing thing about regeneration, is that it stops.
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SPEAKER_00
It knows when to stop.
1
SPEAKER_00
When does it stop?
1
SPEAKER_00
It stops when a correct salamander arm has been completed.
1
SPEAKER_00
So that tells you, that s right, that s a...
1
SPEAKER_00
a means ends kind of analysis where it has to know what the correct limb is supposed to look like right so it has a way to ascertain the current shape it has a way to measure that delta from from what shape it s supposed to be and then it will keep taking actions meaning remodeling and growing and everything else until that s complete
1
SPEAKER_00
So once you know that, and we ve taken advantage of this in the lab to do some really wild things with both planaria and frog embryos and so on, once you know that, you can start playing with that homeostatic cycle.
1
SPEAKER_00
You can ask, for example, well, how does it remember what the correct shape is and can we mess with that memory?
1
SPEAKER_00
Can we give it a false memory of what the shape should be and let the cells build something else?
1
SPEAKER_00
Or can we mess with the measurement apparatus, right?
1
SPEAKER_00
So it gives you those kinds of... So the idea is to
1
SPEAKER_00
basically appropriate a lot of the approaches and concepts from cognitive neuroscience and behavioral science into things that previously were taken to be dumb materials.
1
SPEAKER_00
And you know, you get yelled at in class for being anthropomorphic if you said, well, my cells want to do this and my cells want to do that.
1
SPEAKER_00
And I think that s a major mistake that leaves a ton of capabilities on the table.
1
SPEAKER_01
So thinking about biologic systems as things that have memory, have almost something like cognitive ability, but
1
SPEAKER_01
I mean, how incredible is it that the salamander arm is being rebuilt, not with a dictator.
1
SPEAKER_01
It s kind of like the cellular automata system.
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SPEAKER_01
All the individual workers are doing their own thing.
1
SPEAKER_01
So where s that top-down signal that does the control coming from?
1
SPEAKER_01
How can you find it?
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SPEAKER_01
Why does it stop growing?
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SPEAKER_01
How does it know the shape?
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SPEAKER_01
How does it have memory of the shape?
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SPEAKER_01
And how does it tell everybody to be like, whoa, slow down, we re done.
1
SPEAKER_00
So the first thing to think about, I think, is that there are no examples anywhere of a central dictator in this kind of science, because everything is made of parts.
1
SPEAKER_00
And so we, even though we feel as a unified central sort of intelligence and kind of point of cognition, we are a bag of neurons, right?
1
SPEAKER_00
All intelligence is collective intelligence.
1
SPEAKER_00
This is important to kind of
1
SPEAKER_00
think about because a lot of people think okay there s real intelligence like me and then there s collective intelligence which is ants and flocks of birds and you know termites and things like that and and you know and and maybe it s appropriate to think of them as a as a as a as an individual and maybe it s not a lot of people are skeptical about about that and so on but it s got you got to realize that we are not there s no such thing as this like indivisible diamond of intelligence that s like this one central thing that s not made of parts we are all made of parts
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SPEAKER_00
And so if you believe, which I think is hard to get around, that we in fact have a centralized set of goals and preferences and we plan and we do things and so on, you are already committed to the fact that a collection of cells is able to do this, because we are a collection of cells.
1
SPEAKER_00
There s no getting around that.
1
SPEAKER_00
In our case, what we do is we navigate the three-dimensional world and we have behavior.
1
SPEAKER_01
This is blowing my mind right now, because we are just a collection of cells.
1
SPEAKER_01
Oh yeah, yeah.
1
SPEAKER_01
So when I m moving this arm,
1
SPEAKER_01
I feel like I m the central dictator of that action.
1
SPEAKER_01
But there s a lot of stuff going on.
1
SPEAKER_01
All the cells here are collaborating in some interesting way.
1
SPEAKER_01
They re getting signal from the central nervous system.
1
SPEAKER_00
Well, even the central nervous system is misleadingly named because it isn t really central.
1
SPEAKER_00
Again, it s just a bunch of cells.
1
SPEAKER_00
I mean, there are no singular indivisible intelligences anywhere.
1
SPEAKER_00
Every example that we ve ever seen is a collective of something.
1
SPEAKER_00
It s just that we re used to it.
1
SPEAKER_00
We re used to, okay, this thing is kind of a single thing, but it s really not.
1
SPEAKER_00
You zoom in, you know what you see.
1
SPEAKER_00
You see a bunch of cells running around.
1
SPEAKER_01
Is there some unifying, I mean, we re jumping around, but that s something that you look at as the bioelectrical signal versus the biochemical, the chemistry, the electricity.
1
SPEAKER_01
Maybe the life is in that versus the cells.
1
SPEAKER_01
It s the, there s an orchestra playing, and the resulting music is the dictator.
1
SPEAKER_00
That s not bad.
1
SPEAKER_00
That s Dennis Noble s kind of view of things.
1
SPEAKER_00
He has two really good books where he talks about this musical analogy, right?
1
SPEAKER_00
So I think that s – I like it.
1
SPEAKER_00
I like it.
1
SPEAKER_01
Is it wrong though?
1
SPEAKER_00
No, I don t think it s wrong.
1
SPEAKER_00
I don t think it s wrong.
1
SPEAKER_00
I think the important thing about it is that we have to come to grips with the fact that
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SPEAKER_00
a true, a true proper cognitive intelligence can still be made of parts.
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SPEAKER_00
Those things are, in fact, it has to be.
1
SPEAKER_00
And I think it s a real shame, but I see this all the time.
1
SPEAKER_00
When you have when you have a collective like this, whether it be a group of robots or, you know, a collection of cells or neurons or whatever, as soon as as soon as we gain some insight into how it works, right, meaning that, oh, I see, in order to take this action, here s the information that got processed via this
1
SPEAKER_00
chemical mechanism or whatever, immediately people say, Oh, well, then that s not real cognition.
1
SPEAKER_00
That s just physics.
1
SPEAKER_00
And I think this is, this is fundamentally flawed because if you zoom into anything, what are you going to see?
1
SPEAKER_00
Of course, you re just going to see physics.
1
SPEAKER_00
What else could be underneath, right?
1
SPEAKER_00
That s not going to be fairy dust.
1
SPEAKER_00
It s going to be physics and chemistry, but that doesn t take away from the magic of the fact that there are certain ways to arrange that physics and chemistry and in particular, the bioelectricity, which, which I like a lot.
1
SPEAKER_00
to give you an emergent collective with goals and preferences and memories and anticipations that do not belong to any of the subunits.
1
SPEAKER_00
So I think what we re getting into here, and we can talk about how this happens during embryogenesis and so on, what we re getting into is the origin of a self, with a capital S. So we ourselves, there are many other kinds of selves, and we can tell some really interesting stories about where selves come from and how they become unified.
1
SPEAKER_01
Yeah, is this the first, or at least humans tend to think that this is the level at which the self, with a capital S, is first born.
1
SPEAKER_01
And we really don t wanna see human civilization or Earth itself as one living organism.
1
SPEAKER_01
That s very uncomfortable to us.
1
SPEAKER_01
But where s the self born?
1
SPEAKER_00
we have to grow up past that.
1
SPEAKER_00
So what I like to do is, I ll tell you two quick stories about that.
1
SPEAKER_00
I like to roll backwards.
1
SPEAKER_00
So as opposed to, so if you start and you say, okay, here s a paramecium and you see it, you know, it s a single cell organism, you see it doing various things and people will say, okay, I m sure there s some chemical story to be told about how it s doing it.
1
SPEAKER_00
So that s not true cognition, right?
1
SPEAKER_00
And people will argue about that.
1
SPEAKER_00
I like to work it backwards.
1
SPEAKER_00
I say, let s agree that you and I, as we sit here, are examples of true cognition, if anything.
1
SPEAKER_00
If there s anything that s true cognition, we are examples of it.
1
SPEAKER_00
Now let s just roll back slowly, right?
1
SPEAKER_00
So you roll back to the time when you were a small child and used to doing whatever, and then just sort of day by day, you roll back.
1
SPEAKER_00
And eventually you become more or less that paramecium, and then you re sort of even below that, right, as an unfertilized oocyte.
1
SPEAKER_00
It s, no one has, to my knowledge, no one has come up with any convincing discrete step at which my cognitive powers disappear, right?
1
SPEAKER_00
It just doesn t, biology doesn t offer any specific step.
1
SPEAKER_00
It s incredibly smooth and slow and continuous.
1
SPEAKER_00
And so I think this idea that it just sort of magically shows up at one point and then, you know, humans have true selves that don t exist elsewhere.
1
SPEAKER_00
I think it runs against everything we know about evolution, everything we know about developmental biology.
1
SPEAKER_00
These are all slow, continual.
1
SPEAKER_00
And the other really important story I want to tell is where embryos come from.
1
SPEAKER_00
So think about this for a second.
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SPEAKER_00
Amniote embryos, so this is humans, birds and so on, mammals and birds and so on.
1
SPEAKER_00
Imagine a flat disk of cells.
1
SPEAKER_00
So there s maybe 50,000 cells.
1
SPEAKER_00
And in that, so when you get an egg from a fertilized, let s say you buy a fertilized egg from a farm, right?
1
SPEAKER_00
That egg will have about 50,000 cells in a flat disk.
1
SPEAKER_00
It looks like a little tiny little frisbee.
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SPEAKER_00
And in that flat disk, what ll happen is there ll be one set of cells will become special, and it will tell all the other cells, I m going to be the head, you guys don t be the head.
1
SPEAKER_00
And so it ll amplify symmetry, breaking amplification, and you get one embryo.
1
SPEAKER_00
There s some neural tissue and some other stuff forms.
1
SPEAKER_00
Now you say, okay, I had one egg and one embryo and there you go, what else could it be?
1
SPEAKER_00
Well, the reality is, and I used to, I did all of this as a grad student, if you take a little needle and you make a scratch in that blastoderm, in that disc, such that the cells can t talk to each other, for a while it heals up, but for a while they can t talk to each other.
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SPEAKER_00
What ll happen is that both regions
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SPEAKER_00
will decide that they can be the embryo and there will be two of them and then when they heal up they become conjoined twins and you can make two you can make three you can make lots so the question of how many selves are in there cannot be answered until it s actually played all the way through it isn t necessarily that there s just one
1
SPEAKER_00
There can be many so what you have is you have this medium this this undifferentiated.
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SPEAKER_00
I m sure there s a there s a psychological Version of this somewhere that I don t know the proper terminology but you have this you have this list like the ocean of potentiality you have these thousands of cells and Some number of individuals are going to be formed out of it.
1
SPEAKER_00
Usually one sometimes zero sometimes several and
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SPEAKER_00
and they form out of these cells because a region of these cells organizes into a collective that will have goals, goals that individual cells don t have.
1
SPEAKER_00
For example, make a limb, make an eye.
1
SPEAKER_00
How many eyes?
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SPEAKER_00
Well, exactly two.
1
SPEAKER_00
So individual cells don t know what an eye is.
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SPEAKER_00
They don t know how many eyes you re supposed to have, but the collective does.
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SPEAKER_00
The collective has goals and memories and anticipations that the individual cells don t.
1
SPEAKER_00
And the establishment of that boundary with its own ability to pursue certain goals, that s the origin of selfhood.
1
SPEAKER_01
But is that goal
1
SPEAKER_01
in there somewhere?
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SPEAKER_01
Were they always destined?
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SPEAKER_01
Are they discovering that goal?
1
SPEAKER_01
Where the hell did evolution discover this?
1
SPEAKER_01
When you went from the prokaryotes to eukaryotic cells, and then they started making groups, and when you make a certain group, you make it sound
1
SPEAKER_01
and it s such a tricky thing to try to understand.
1
SPEAKER_01
You make it sound like the cells didn t get together and came up with a goal, but the very act of them getting together revealed the goal that was always there.
1
SPEAKER_01
There was always that potential for that goal.
1
SPEAKER_00
So the first thing to say is that there are way more questions here than certainties.
1
SPEAKER_00
Okay, so everything I m telling you is cutting-edge developing, you know, stuff.
1
SPEAKER_00
So it s not as if any of us know the answer to this.
1
SPEAKER_00
But here s my opinion on this.
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SPEAKER_00
I think what evolution... I don t think that evolution produces solutions to specific problems.
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SPEAKER_00
In other words, specific environments.
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SPEAKER_00
Like here s a frog that can live well in a froggy environment.
1
SPEAKER_00
I think what evolution produces is problem-solving machines that will solve problems in different spaces.
1
SPEAKER_00
So not just three-dimensional space.
1
SPEAKER_00
This goes back to what we were talking about before.
1
SPEAKER_00
The brain is evolutionarily a late development.
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SPEAKER_00
It s a system that is able to pursue goals in three-dimensional space by giving commands to muscles.
1
SPEAKER_00
Where did that system come from?
1
SPEAKER_00
That system evolved from a much more ancient, evolutionarily much more ancient system,
1
SPEAKER_00
where collections of cells gave instructions for cell behaviors, meaning cells move to divide, to die, to change into different cell types, to navigate morphous space, the space of anatomies, the space of all possible anatomies.
1
SPEAKER_00
And before that, cells were navigating transcriptional space, which is a space of all possible gene expressions, and before that, metabolic space.
1
SPEAKER_00
So what evolution has done, I think, is produced hardware that is very good at navigating different spaces using a bag of tricks, right, which I m sure many of them we can steal for autonomous vehicles and robotics and various things.
2
SPEAKER_00
And what happens is that they navigate these spaces without a whole lot of commitment to what the space is.
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SPEAKER_00
In fact, they don t know what the space is, right?
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SPEAKER_00
We are all brains in a vat, so to speak.
2
SPEAKER_00
Every cell does not know, right?
2
SPEAKER_00
Every cell is some other cell s external environment, right?
2
SPEAKER_00
So where does that border between you and the outside world, you don t really know where that is, right?
2
SPEAKER_00
Every collection of cells has to figure that out from scratch.
2
SPEAKER_00
And the fact that evolution requires all of these things to figure out what they are, what effectors they have, what sensors they have, where does it make sense to draw a boundary between me and the outside world, the fact that you have to build all that from scratch, this autopoiesis, is what defines the border of a self.
2
SPEAKER_00
Now, biology uses like a multi-scale competency architecture, meaning that every level has goals.
2
SPEAKER_00
So molecular networks have goals, cells have goals, tissues, organs, colonies.
2
SPEAKER_00
And it s the interplay of all of those that enable biology to solve problems in new ways, for example, in xenobots and various other things.
2
SPEAKER_00
This is, you know, it s exactly as you said, in many ways, the cells are discovering new ways of being, but at the same time, evolution certainly shapes all this.
2
SPEAKER_00
So evolution is very good at this agential bioengineering, right?
2
SPEAKER_00
When evolution is discovering a new way of being an animal, an animal or a plant or something,
2
SPEAKER_00
Sometimes it s by changing the hardware, you know, protein, changing proteins, protein structure, and so on.
2
SPEAKER_00
But much of the time, it s not by changing the hardware, it s by changing the signals that the cells give to each other.
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SPEAKER_00
It s doing what we as engineers do, which is try to convince the cells to do various things by using signals, experiences, stimuli.
2
SPEAKER_00
That s what biology does.
2
SPEAKER_00
It has to, because it s not dealing with a blank slate.
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SPEAKER_00
Every time, as you know, if you re evolution and you re trying to
2
SPEAKER_00
make an organism, you re not dealing with a passive material that is fresh and you have to specify.
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SPEAKER_00
It already wants to do certain things.
2
SPEAKER_00
So the easiest way to do that search, to find whatever is going to be adaptive, is to find the signals that are going to convince cells to do various things, right?
2
SPEAKER_01
Your sense is that evolution operates both in the software and the hardware, and it s just easier and more efficient to operate in the software.
2
SPEAKER_00
Yes, and I should also say, I don t think the distinction is sharp.
2
SPEAKER_00
In other words, I think it s a continuum, but I think it s a meaningful distinction where you can make
2
SPEAKER_00
changes to a particular protein and now the enzymatic function is different and it metabolizes differently and whatever, and that will have implications for fitness.
2
SPEAKER_00
Or you can change the huge amount of information in the gene, though, that isn t structural at all.
2
SPEAKER_00
It s signaling.
2
SPEAKER_00
It s when and how do cells say certain things to each other, and that can have massive changes as far as how it s gonna solve problems.
2
SPEAKER_01
I mean, this idea of multi-hierarchical competence architecture, which is incredible to think about,
2
SPEAKER_01
So this hierarchy that evolution builds, I don t know who s responsible for this.
2
SPEAKER_01
I also see the incompetence of bureaucracies of humans when they get together.
2
SPEAKER_01
So how the hell does evolution build this?
2
SPEAKER_01
Where at every level, only the best get to stick around, they somehow figure out how to do their job without knowing the bigger picture.
2
SPEAKER_01
And then there s like the bosses that do the bigger thing.
2
SPEAKER_01
somehow, or you can now abstract away the small group of cells as an organ or something, and then that organ does something bigger in the context of the full body or something like this.
2
SPEAKER_01
How is that built?
2
SPEAKER_01
Is there some intuition you can kind of provide of how that s constructed, that hierarchical competence architecture?
2
SPEAKER_01
I love that, competence, just the word competence is pretty cool in this context, because everybody s good at their job somehow.
2
SPEAKER_00
Yeah, no, it s really key.
2
SPEAKER_00
And the other nice thing about competency is that, so my central belief in all of this is that engineering is the right perspective on all of this stuff, because it gets you away from subjective terms.
2
SPEAKER_00
People talk about sentience and this and that.
2
SPEAKER_00
Those things are very hard to define.
2
SPEAKER_00
People argue about them philosophically.
2
SPEAKER_00
I think that engineering terms like competency, like pursuit of goals, right,
2
SPEAKER_00
All of these things are empirically incredibly useful because you know it when you see it.
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SPEAKER_00
And if it helps you build, right, if I can pick the right level, I say, this thing has, I believe this is X level of competency.
2
SPEAKER_00
I think it s like a thermostat, or I think it s like a better thermostat, or I think it s a, you know,
2
SPEAKER_00
various other kinds of, you know, many, many different kinds of complex systems.
2
SPEAKER_00
If that helps me to control and predict and build such systems, then that s all there is to say.
2
SPEAKER_00
There s no more philosophy to argue about.
2
SPEAKER_00
So I like competency in that way because you can quantify, you could, you have to, in fact, you have to, you have to make a claim competent at what?
2
SPEAKER_00
And then or if I say, if I tell you it has a goal, the question is, what s the goal and how do you know?
2
SPEAKER_00
And I said, well, because every time I deviated from this particular state, that s what it spends energy to get back to.
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SPEAKER_00
That s the goal.
2
SPEAKER_00
And we can quantify it and we can be objective about it.
2
SPEAKER_00
So so so the the we re not used to thinking about this.
2
SPEAKER_00
I give a talk sometimes called Why Don t Robots Get Cancer?
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SPEAKER_00
And the reason robots don t get cancer is because generally speaking, with a few exceptions, our architectures have been, you ve got a bunch of dumb parts, and you hope that if you put them together, the overlying machine will have some intelligence and do something or other, right?
2
SPEAKER_00
But the individual parts don t care.
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SPEAKER_00
They don t have an agenda.
2
SPEAKER_00
Biology isn t like that.
2
SPEAKER_00
Every level has an agenda.
2
SPEAKER_00
And the final outcome is the result of cooperation and competition, both within and across levels.
2
SPEAKER_00
So, for example, during embryogenesis, your tissues and organs are competing with each other.
2
SPEAKER_00
And it s actually a really important part of development.
2
SPEAKER_00
There s a reason they compete with each other.
2
SPEAKER_00
They re not all just, you know, sort of helping each other.
2
SPEAKER_00
They re also competing for information, for metabolic, for limited metabolic constraints.
2
SPEAKER_00
But to get back to your your your other point, which is, you know, which is which is the seems like really efficient and good and so on compared to some of our human efforts.
2
SPEAKER_00
We also have to keep in mind that what happens here is that each level
2
SPEAKER_00
bends the option space for the level beneath so that your parts basically they don t see the the the geometry so so i m using um and i and i think i take this this seriously uh terminology from from like um from like relativity right where the space is literally bent so the option space is deformed by the higher level so that the lower levels all they really have to do is go down their concentration gradient they don t have to in fact they don t they can t know what the big picture is
2
SPEAKER_00
But if you bend the space just right, if they do what locally seems right, they end up doing your bidding.
2
SPEAKER_00
They end up doing things that are optimal in the higher space.
2
SPEAKER_00
Conversely, because the components are good at getting their job done, you as the higher level don t need to try to compute all the low-level controls.
2
SPEAKER_00
All you re doing is bending the space.
2
SPEAKER_00
You don t know or care how they re going to do it.
2
SPEAKER_00
I ll give you a super simple example in the Tadpole.
2
SPEAKER_00
We found that, okay, so tadpoles need to become frogs.
2
SPEAKER_00
And to go from a tadpole head to a frog head, you have to rearrange the face.
2
SPEAKER_00
So the eyes have to move forward, the jaws have to come out, the nostrils move, everything moves.
2
SPEAKER_00
It used to be thought that because all tadpoles look the same and all frogs look the same, if you just remember, if every piece just moves in the right direction, the right amount, then you get your frog, right?
2
SPEAKER_00
So we decided to test.
2
SPEAKER_00
I had this hypothesis that I thought, actually, the system is probably more intelligent than that.
2
SPEAKER_00
So what did we do?
2
SPEAKER_00
We made what we call Picasso tadpoles.
2
SPEAKER_00
So these are so everything is scrambled So the eyes are on the back of the head the jaws are off to the side everything is scrambled Well, guess what?
2
SPEAKER_00
They make they make pretty normal frogs because all the different things move around in novel paths Configurations until they get to the correct froggy different sort of frog face configuration then they stop so so the thing about that is now imagine evolution, right so so you make some sort of mutation and
2
SPEAKER_00
It does, like every mutation, it does many things.
2
SPEAKER_00
So something good comes of it, but also it moves your mouth off to the side, right?
2
SPEAKER_00
Now, if there wasn t this multi-scale competency, you can see where this is going.
2
SPEAKER_00
If there wasn t this multi-scale competency, the organism would be dead.
2
SPEAKER_00
Your fitness is zero because you can t eat.
2
SPEAKER_00
And you would never get to explore the other beneficial consequences of that mutation.
2
SPEAKER_00
You d have to wait until you find some other way of doing it without moving the mouth.
2
SPEAKER_00
That s really hard.
2
SPEAKER_00
So the fitness landscape would be incredibly rugged.
2
SPEAKER_00
Evolution would take forever.
2
SPEAKER_00
The reason it works, one of the reasons it works so well, is because you do that, no worries, the mouth will find its way where it belongs, right?
2
SPEAKER_00
So now you get to explore.
2
SPEAKER_00
So what that means is that all of these mutations that otherwise would be deleterious are now neutral, because the competency of the parts
2
SPEAKER_00
make up for all kinds of things.
2
SPEAKER_00
So all the noise of development, all the variability in the environment, all these things, the competency of the parts makes up for it.
2
SPEAKER_00
So that s all fantastic, right?
2
SPEAKER_00
That s all great.
2
SPEAKER_00
The only other thing to remember when we compare this to human efforts is this.
2
SPEAKER_00
every component has its own goals in various spaces, usually with very little regard for the welfare of the other levels.
2
SPEAKER_00
So as a simple example, you as a complex system, you will go out and you will do jujitsu or whatever, you ll have some go, you have to go rock climbing and scrape a bunch of cells off your hands, and then you re happy as a system, right?
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SPEAKER_00
You come back and you ve accomplished some goals and you re really happy.
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SPEAKER_00
Those cells are dead, they re gone, right?
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SPEAKER_00
Did you think about those cells?
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SPEAKER_00
Not really, right?
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SPEAKER_00
You had some bruising, albinism.
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SPEAKER_00
That s it.
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SPEAKER_00
And so that s the thing to remember is that and we know this from history is that just being a collective isn t enough because what the goals of that collective will be relative to the welfare of the individual parts is a massively open question.
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SPEAKER_01
The ends justify the means.
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SPEAKER_01
I m telling you Stalin was onto something.
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SPEAKER_01
So that s the danger.
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SPEAKER_01
Exactly, that s the danger of, for us humans, we have to construct ethical systems under which we don t take seriously the full mechanism of biology and apply it to the way the world functions, which is an interesting line we ve drawn.
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SPEAKER_01
The world that built us,
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SPEAKER_01
is the one we reject in some sense when we construct human societies.
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SPEAKER_01
The idea that this country was founded on that all men are created equal, that s such a fascinating idea.
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SPEAKER_01
It s like you re fighting against nature and saying, well, there s something bigger here than, yeah.
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SPEAKER_01
a hierarchical competency architecture.
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SPEAKER_01
There s so many interesting things you said.
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SPEAKER_01
So from an algorithmic perspective, the act of bending the option space, that s really profound.
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SPEAKER_01
Because if you look at the way AI systems are built today, there s a big system, like you said, with robots, and it has a goal.
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SPEAKER_01
And it gets better and better at optimizing that goal, at accomplishing that goal.
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SPEAKER_01
But if biology built a hierarchical system where everything is doing computation and everything is accomplishing the goal, not only that, it s kind of dumb with the limited, with the bent option space, it s just doing the thing that s the easiest thing for it in some sense.
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SPEAKER_01
And somehow that allows you to have turtles on top of turtles, literally.
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SPEAKER_01
Dumb systems on top of dumb systems that as a whole create something incredibly smart.
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SPEAKER_00
Yeah, I mean, every system has some degree of intelligence in its own problem domain.
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SPEAKER_00
So cells will have problems they re trying to solve in physiological space and transcriptional space, and I can give you some cool examples of that.
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SPEAKER_00
But the collective is trying to solve problems in anatomical space, right, and forming a creature and growing your blood vessels and so on.
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SPEAKER_00
And then the whole body is solving yet other problems.
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SPEAKER_00
They may be in social space and linguistic space and three-dimensional space.
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SPEAKER_00
And who knows, the group might be solving problems in, I don t know, some sort of financial space or something.
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SPEAKER_00
So one of the major differences with most AIs today is A, the kind of flatness of the architecture, but also of the fact that they are constructed
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SPEAKER_00
from outside their borders and their, you know, so to a large extent, and of course there are counter examples now, but to a large extent, our technology has been such that you create a machine or a robot, it knows what its sensors are, it knows what its effectors are, it knows the boundary between it and the outside world, all of this is given from the outside.
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Biology constructs this from scratch.
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SPEAKER_00
Now, the best example of this that originally
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Robotics was actually Josh Bongard s work in 2006 where he made these robots that did not know their shape to start with.
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SPEAKER_00
So like a baby, they sort of floundered around, they made some hypotheses, well I did this and I moved in this way, well maybe I m a whatever, maybe I have wheels or maybe I have six legs or whatever, and they would make a model and eventually it would crawl around.
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SPEAKER_00
So that s, I mean, that s really good.
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SPEAKER_00
That s part of the autopoiesis, but we can go a step further.
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SPEAKER_00
And some people are doing this, and then we re sort of working on some of this too, is this idea that let s even go back further.
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SPEAKER_00
You don t even know what sensors you have.
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SPEAKER_00
You don t know where you end and the outside world begins.
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SPEAKER_00
All you have is certain things like active inference, meaning you re trying to minimize surprise, right?
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SPEAKER_00
You have some metabolic constraints.
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SPEAKER_00
You don t have all the energy you need.
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SPEAKER_00
You don t have all the time in the world to think about everything you want to think about.
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SPEAKER_00
So that means that you can t afford to be a micro-reductionist, you know, all this data coming in.
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SPEAKER_00
You have to coarse-grain it and say, I m going to take all this stuff and I m going to call that a cat.
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SPEAKER_00
I m going to take all this, I m going to call that the edge of the table I don t want to fall off of.
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SPEAKER_00
And I don t want to know anything about the microstates.
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SPEAKER_00
What I want to know is, what is the optimal way to cut up my world?
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SPEAKER_00
And by the way, this thing over here, that s me.
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SPEAKER_00
And the reason that s me is because I have more control over this than I have over any of this other stuff.
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SPEAKER_00
And so now you can begin to write.
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SPEAKER_00
So that s self construction, that that that figuring out making models of the outside world and then turning that inwards and starting to make a model of yourself, right, which immediately starts to get into issues of agency and control, because
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SPEAKER_00
In order to if you are under metabolic constraints, meaning you don t have the energy, right, that all the energy in the world, you have to be efficient, that immediately forces you to start telling stories about coarse grained agents that do things, right?
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SPEAKER_00
You don t have the energy to like Laplace s demon, you know, calculate every
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SPEAKER_00
every possible state that s going to happen, you have to coarse-grain and you have to say, that is the kind of creature that does things, either things that I avoid or things that I will go towards, that s a mate or food or whatever it s going to be.
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SPEAKER_00
And so right at the base of simple, very simple organisms starting to make
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SPEAKER_00
models of agents doing things, that is the origin of models of free will basically, right?
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SPEAKER_00
Because you see the world around you as having agency and then you turn that on yourself and you say, wait, I have agency too.
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SPEAKER_00
I do things, right?
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SPEAKER_00
And then you make decisions about what you re going to do.
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SPEAKER_00
So all of this one model is to view all of those kinds of things as
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SPEAKER_00
being driven by that early need to determine what you are and to do so and to then take actions in the most energetically efficient space possible.
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SPEAKER_01
So free will emerges when you try to simplify, tell a nice narrative about your environment.
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SPEAKER_00
I think that s very plausible, yeah.
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SPEAKER_01
You think free will is an illusion.
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SPEAKER_01
So you re kind of implying that it s a useful hack.
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SPEAKER_00
Well, I ll say two things.
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SPEAKER_00
The first thing is I think it s very plausible to say that any organism that self, or any agent that self, whether it s biological or not, any agent that self-constructs under energy constraints is going to believe in free will.
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SPEAKER_00
We ll get to whether it has free will momentarily, but I think what it definitely drives is a view of yourself and the outside world as an agential view.
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SPEAKER_00
I think that s inescapable.
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SPEAKER_01
So that s true for even primitive organisms.
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SPEAKER_00
I think so.
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SPEAKER_00
Now, obviously you have to scale down, right?
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SPEAKER_00
So they don t have the kinds of complex metacognition that we have, so they can do long-term planning and thinking about free will and so on.
2
SPEAKER_01
But the sense of agency is really useful to accomplish tasks, simple or complicated.
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SPEAKER_00
That s right.
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SPEAKER_00
In all kinds of spaces, not just in obvious three-dimensional space.
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SPEAKER_00
I mean, we re very good that the thing is,
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SPEAKER_00
humans are very good at detecting agency of like medium-sized objects moving at medium speeds in the three-dimensional world, right?
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SPEAKER_00
We see a bowling ball and we see a mouse and we immediately know what the difference is, right?
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SPEAKER_01
Mostly things you can eat or get eaten by.
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SPEAKER_00
Yeah, yeah.
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SPEAKER_00
That s our training set, right?
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SPEAKER_00
From the time you re little, your training set is visual data on this like little chunk of your experience.
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SPEAKER_00
But imagine if
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SPEAKER_00
Imagine if from the time that we were born, we had innate senses of your blood chemistry.
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SPEAKER_00
If you could feel your blood chemistry the way you can see, right?
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SPEAKER_00
You had a high bandwidth connection and you could feel your blood chemistry and you could see, you could sense all the things that your organs were doing.
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SPEAKER_00
So your pancreas, your liver, all the things.
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SPEAKER_00
If we had that, we would be very good at detecting intelligence in physiological space.
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SPEAKER_00
We would know the level of intelligence that our various organs were deploying to deal with things that were coming, to anticipate the stimuli, but we re just terrible at that.
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SPEAKER_00
In fact, people don t
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SPEAKER_00
even you know you talk about intelligence of these other paper spaces and a lot of people think that s just crazy because because all we re all we know is motion
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SPEAKER_01
We do have access to that information, so it s actually possible that, so evolution could if it wanted to construct an organism that s able to perceive the flow of blood through your body.
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SPEAKER_01
The way you see an old friend and say, yo, what s up, how s the wife and the kids?
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SPEAKER_01
In that same way, you would feel like a connection to the liver.
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SPEAKER_00
Yeah, yeah, I think, you know.
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SPEAKER_01
Maybe other people s liver, or no, just your own?
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SPEAKER_01
Because you don t have access to other people s liver.
3
SPEAKER_00
Not yet, but you could imagine some really interesting connection, right?
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SPEAKER_01
Like sexual selection?
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SPEAKER_01
Like, ooh, that girl s got a nice liver.
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SPEAKER_01
The way her blood flows, the dynamics of the blood is very interesting.
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SPEAKER_01
It s novel.
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SPEAKER_01
I ve never seen one of those.
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SPEAKER_00
But you know, that s exactly what we re trying to half-ass when we judge judgment of beauty by facial symmetry and so on.
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SPEAKER_00
That s a half-assed assessment of exactly that.
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SPEAKER_00
Because if your cells could not cooperate enough to keep your organism symmetrical, you can make some inferences about what else is wrong, right?
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SPEAKER_00
That s a very basic...
3
SPEAKER_01
Interesting, yeah, so in some deep sense, actually, that is what we re doing.
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SPEAKER_01
We re trying to infer how, we use the word healthy, but basically how functional is this biological system I m looking at so I can hook up with that one and make offspring.
3
SPEAKER_00
Yeah, well what kind of hardware might their genomics give me that might be useful in the future?
3
SPEAKER_01
I wonder why evolution didn t give us a higher resolution signal.
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SPEAKER_01
Like why the whole peacock thing with the feathers, it doesn t seem
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SPEAKER_01
It s a very low bandwidth signal for sexual selection.
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SPEAKER_00
I m not an expert on this stuff, but I ll take a stab at the reason.
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SPEAKER_00
I think that it s because it s an arms race.
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SPEAKER_00
You see, you don t want everybody to know everything about you.
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SPEAKER_00
So I think that as much as, and in fact, there s another interesting part of this arms race, which is,
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SPEAKER_00
If you think about this, the most adaptive, evolvable system is one that has the most level of top-down control, right?
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SPEAKER_00
If it s really easy to say to a bunch of cells, make another finger versus, okay, here s 10,000 gene expression changes that you need to do to change your finger, right?
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SPEAKER_00
The system with good top-down control that has memory, and we need to get back to that, by the way, that s a question I neglected to answer about where the memory is and so on.
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SPEAKER_00
A system that uses all of that is really highly evolvable, and that s fantastic.
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SPEAKER_00
But guess what?
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SPEAKER_00
It s also highly subject to hijacking by parasites, by cheaters of various kinds, by conspecifics.
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SPEAKER_00
We found that, and that goes back to the story of the pattern memory in these planaria, there s a bacterium that lives on these planaria.
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SPEAKER_00
That bacterium has an input into how many heads the worm is going to have.
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SPEAKER_00
because it hijacks that control system and it s able to make a chemical that basically interfaces with the system that calculates how many heads you re supposed to have and they can make them have two heads.
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SPEAKER_00
And so you can imagine that if you are two, so you want to be understandable for your own parts to understand each other, but you don t want to be too understandable because you ll be too easily controllable.
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SPEAKER_00
And so I think that my guess is that that opposing pressure keeps us from being a super high bandwidth kind of thing where we can just look at somebody and know everything about them.
3
SPEAKER_01
So it s a kind of biological game of Texas Hold em.
3
SPEAKER_01
Yeah.
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SPEAKER_01
You re showing some cards, and you re hiding other cards, and there s part of it, and there s bluffing, and there s all that, and then there s probably whole species that would do way too much bluffing.
3
SPEAKER_01
That s probably where peacocks fall.
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SPEAKER_01
There s a book
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SPEAKER_01
that I don t remember if I read or if I read summaries of the book, but it s about evolution of beauty in birds.
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SPEAKER_01
Where s that from?
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SPEAKER_01
Is that a book or does Richard Dawkins talk about it?
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SPEAKER_01
But basically there s some species start to over-select for beauty.
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SPEAKER_01
Not over-select, they just some reason select for beauty.
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SPEAKER_01
There is a case to be made, actually now I m starting to remember, I think Darwin himself made a case that you can select based on beauty alone.
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SPEAKER_01
So that beauty, there s a point where beauty doesn t represent some underlying biological truth.
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SPEAKER_01
You start to select for beauty itself.
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SPEAKER_01
And I think the deep question is, is there some evolutionary value to beauty?
3
SPEAKER_01
But it s an interesting kind of,
3
SPEAKER_01
thought that this, can we deviate completely from the deep biological truth to actually appreciate some kind of the summarization in itself?
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SPEAKER_01
Let me get back to memory, because this is a really interesting idea.
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SPEAKER_01
How do a collection of cells remember anything?
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SPEAKER_01
How do biological systems remember anything?
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SPEAKER_01
How is that akin to the kind of memory we think of humans as having within our big cognitive engine?
3
SPEAKER_00
Yeah.
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SPEAKER_00
One of the ways to start thinking about bioelectricity is to ask ourselves, where did neurons and all these cool tricks that the brain uses to run these amazing problem solving abilities on and basically an electrical network.
3
SPEAKER_00
Where did that come from?
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SPEAKER_00
That didn t just evolve, you know, up here out of nowhere.
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SPEAKER_00
It must have evolved from something.
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SPEAKER_00
And what it evolved from was a much more ancient ability of cells to form networks to solve other kinds of problems.
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SPEAKER_00
For example, to navigate morphous space, to control the body shape.
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SPEAKER_00
And so all of the components
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SPEAKER_00
of neurons, so ion channels, neurotransmitter machinery, electrical synapses, all this stuff is way older than brains, way older than neurons, in fact, older than multicellularity.
3
SPEAKER_00
And so it was already, even bacterial biofilms, there s some beautiful work from UCSD on brain-like dynamics and bacterial biofilms.
3
SPEAKER_00
So evolution figured out very early on that electrical networks are amazing at having memories, at integrating information across distance, at different kinds of optimization tasks, image recognition and so on.
3
SPEAKER_00
long before there were brains.
3
SPEAKER_01
Can you actually step back and return to it?
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SPEAKER_01
What is bioelectricity?
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SPEAKER_01
What is biochemistry?
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SPEAKER_01
What are electrical networks?
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SPEAKER_01
I think a lot of the biology community focuses on
3
SPEAKER_01
the chemicals as the signaling mechanisms that make the whole thing work.
3
SPEAKER_01
You have, I think, to a large degree uniquely, maybe you can correct me on that, have focused on the bioelectricity, which is using electricity for signaling.
3
SPEAKER_01
There s also probably mechanical.
3
SPEAKER_01
Like knocking on the door.
3
SPEAKER_01
So what s the difference and what s an electrical network?
3
SPEAKER_00
Yeah, so I want to make sure and kind of give credit where credit is due.
3
SPEAKER_00
So as far back as 1903 and probably late 1800s already, people were thinking about the importance of electrical phenomena in life.
3
SPEAKER_00
So I m for sure not the first person to stress the importance of electricity.
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SPEAKER_00
There were waves of research in the 30s, in the 40s, and then
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SPEAKER_00
again, in the kind of 70s, 80s and 90s of sort of the pioneers of bioelectricity who did some amazing work on all this.
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SPEAKER_00
I think what we ve done that s new is to step away from this idea that, and I ll describe what the bioelectricity is, is step away from the idea that, well, here s another piece of physics that you need to keep track of to understand
3
SPEAKER_00
physiology and development, and to really start looking at this as saying, you know, this is a privileged computational layer that gives you access to the actual cognition of the tissue, of basal cognition, so merging that developmental biophysics with ideas and cognition of computation and so on.
3
SPEAKER_00
I think that s what we ve done that s new, but people have been talking about bioelectricity for a really long time and so I ll define that.
3
SPEAKER_00
What happens is that if you have a single cell, cell has a membrane, in that membrane are proteins called ion channels, and those proteins allow charged molecules, potassium, sodium, chloride, to go in and out under certain circumstances.
3
SPEAKER_00
And when there s an imbalance of those ions, there becomes a voltage gradient across that membrane.
3
SPEAKER_00
And so all cells, all living cells, try to hold a particular kind of voltage difference across the membrane, and they spend a lot of energy to do so.
3
SPEAKER_00
So that s a single cell.
3
SPEAKER_00
When you have multiple cells, the cells sitting next to each other, they can communicate their voltage state to each other via a number of different ways, but one of them is this thing called a gap junction, which is basically like a little submarine hatch that just kind of docks, right?
3
SPEAKER_00
And the ions from one side can flow to the other side and vice versa.
3
SPEAKER_01
So- Isn t it incredible that this evolved?
3
SPEAKER_01
Isn t that wild?
3
SPEAKER_01
Because that didn t exist.
3
SPEAKER_00
Correct, this had to be evolved.
3
SPEAKER_00
It had to be invented.
3
SPEAKER_00
That s right.
3
SPEAKER_01
Somebody invented electricity in the ocean.
3
SPEAKER_01
When did this get invented?
3
SPEAKER_00
Yeah, so, I mean, it is incredible.
3
SPEAKER_00
The guy who discovered Gap Junctions, Werner Lowenstein, I visited him, he was really old.
3
SPEAKER_01
A human being?
3
SPEAKER_00
He discovered them.
3
SPEAKER_01
Because who really discovered them lived probably four billion years ago.
3
SPEAKER_01
Good point.
3
SPEAKER_01
So give credit where credit is due.
3
SPEAKER_00
I m just saying.
3
SPEAKER_00
He rediscovered gap junctions.
3
SPEAKER_00
But when I visited him in Woods Hole maybe 20 years ago now, he told me that he was writing, and unfortunately he passed away, and I think this book never got written.
3
SPEAKER_00
He was writing a book on gap junctions and consciousness.
3
SPEAKER_00
and I think it would have been an incredible book because gap junctions are magic.
3
SPEAKER_00
I ll explain why in a minute.
3
SPEAKER_00
What happens is that, just imagine, the thing about both these ion channels and these gap junctions is that many of them are themselves voltage sensitive.
3
SPEAKER_00
So that s a voltage-sensitive current conductance.
3
SPEAKER_00
That s a transistor.
3
SPEAKER_00
And as soon as you ve invented one, immediately, you now get access to, from this platonic space of mathematical truths, you get access to all of the cool things that transistors do.
3
SPEAKER_00
So now, when you have a network of cells, not only do they talk to each other, but they can send messages to each other, and the differences of voltage can propagate.
3
SPEAKER_00
Now, to neuroscientists, this is old hat, because you see this in the brain, right?
3
SPEAKER_00
There s action potentials, the electricity.
3
SPEAKER_00
They have these awesome movies where you can take a transparent animal, like a zebrafish, and you can literally look down and you can see all the firings as the fish is making decisions about what to eat and things like this, right?
3
SPEAKER_00
It s amazing.
3
SPEAKER_00
Well, your whole body is doing that all the time, just much slower.
3
SPEAKER_00
So there are very few things that neurons do that other cells, that all the cells in your body don t do.
3
SPEAKER_00
They all do very similar things, just on a much slower time scale.
3
SPEAKER_00
And whereas your brain is thinking about how to solve problems in three-dimensional space, the cells in the embryo are thinking about how to solve problems in anatomical space.
3
SPEAKER_00
They re trying to have memories like, hey, how many fingers are we supposed to have?
3
SPEAKER_00
Well, how many do we have now?
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SPEAKER_00
What do we do to get from here to there?
3
SPEAKER_00
That s the kind of problems they re thinking about.
3
SPEAKER_00
And the reason that gap junctions are magic is, imagine, right, from the
3
SPEAKER_00
from the earliest time.
3
SPEAKER_00
Here are two cells.
3
SPEAKER_00
This cell, how can they communicate?
3
SPEAKER_00
Well, the simple version is this cell could send a chemical signal, it floats over and it hits a receptor on this cell, right?
3
SPEAKER_00
Because it comes from outside, this cell can very easily tell that that came from outside.
3
SPEAKER_00
Whatever information is coming, that s not my information.
3
SPEAKER_00
That information is coming from the outside.
3
SPEAKER_00
I can trust it, I can ignore it, I can do various things with it, whatever, but I know it comes from the outside.
3
SPEAKER_00
Now imagine instead that you have two cells with a gap junction between them.
3
SPEAKER_00
Something happens, let s say this cell gets poked, there s a calcium spike, and the calcium spike or whatever small molecule signal propagates through the gap junction to this cell.
3
SPEAKER_00
There s no ownership metadata on that signal.
3
SPEAKER_00
This cell does not know now that it came from outside because it looks exactly like its own memories would have looked like of whatever had happened, right?
3
SPEAKER_00
So gap junctions, to some extent, wipe ownership information on data, which means that if you and I are sharing memories and we can t quite tell who the memories belong to, that s the beginning of a mind melt.
3
SPEAKER_00
That s the beginning of a scale up of cognition from here s me and here s you to no, now there s just us.
3
SPEAKER_01
So they enforce a collective intelligence gap juncture.
3
SPEAKER_00
That s right.
3
SPEAKER_00
It helps, it s the beginning.
3
SPEAKER_00
It s not the whole story by any means, but it s the start.
3
SPEAKER_01
Where s state stored of the system?
3
SPEAKER_01
Is it in part in the gap junctions themselves?
3
SPEAKER_01
Is it in the cells?
3
SPEAKER_00
There are many, many layers to this, as always, in biology.
3
SPEAKER_00
So there are chemical networks.
3
SPEAKER_00
So for example, gene regulatory networks, right, or basically any kind of chemical pathway where different chemicals activate and repress each other, they can store memories.
3
SPEAKER_00
So in a dynamical system sense, they can store memories.
3
SPEAKER_00
They can get into stable states that are hard to pull them out of, right?
3
SPEAKER_00
So that becomes, once they get in, that s a memory, a permanent memory, or a semi-permanent memory of something that s happened.
3
SPEAKER_00
There are cytoskeletal structures, right, that are physically, they store memories in physical configuration.
3
SPEAKER_00
There are electrical memories like flip-flops, where there is no physical, right?
3
SPEAKER_00
So if you look, I show my students this example, there s a flip-flop.
3
SPEAKER_00
And the reason that it stores a 0 or 1 is not because some piece of the hardware moved.
3
SPEAKER_00
It s because there s a cycling of the current in one side of the thing.
3
SPEAKER_00
If I come over and I hold the other side to a higher voltage for a brief period of time, it flips over and now it s here.
3
SPEAKER_00
But none of the hardware moved.
3
SPEAKER_00
The information is in a stable, dynamical sense.
3
SPEAKER_00
And if you were to x-ray the thing, you couldn t tell me if it was zero or one, because all you would see is where the hardware is.
3
SPEAKER_00
You wouldn t see the energetic state of the system.
3
SPEAKER_00
So there are bioelectrical states that are held in that exact way, like volatile RAM, basically, in the electrical state of the system.
3
SPEAKER_01
So it s very akin to the different ways that memory is stored in a computer.
3
SPEAKER_01
So there s RAM, there s hard drives.
3
SPEAKER_00
You can make that mapping, right?
3
SPEAKER_00
So I think the interesting thing is that based on the biology, we can have a more sophisticated, you know, I think we can revise some of our computer engineering methods because there are some interesting things that biology does that we haven t done yet.
3
SPEAKER_00
But that mapping is not bad.
3
SPEAKER_00
I mean, I think it works in many ways.
3
SPEAKER_01
Yeah, I wonder, because I mean, the way we build computers
3
SPEAKER_01
at the root of computer science is the idea of proof of correctness.
3
SPEAKER_01
We program things to be perfect, reliable.
3
SPEAKER_01
You know, this idea of resilience and robustness to unknown conditions is not as important.
3
SPEAKER_01
So that s what biology is really good at.
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SPEAKER_01
So I don t know what kind of systems, I don t know how we go from a computer to a biological system in the future.
3
SPEAKER_00
Yeah, I think that, you know, the thing about biology is all about making really important decisions really quickly on very limited information.
3
SPEAKER_00
I mean, that s what biology is all about.
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SPEAKER_00
You have to act, you have to act now.
3
SPEAKER_00
The stakes are very high and you don t know most of what you need to know to be perfect.
3
SPEAKER_00
And so there s not even an attempt to be perfect or to get it right in any sense.
3
SPEAKER_00
There are just things like active inference, minimize surprise, optimize some efficiency and some things like this.
3
SPEAKER_00
That guides the whole business.
3
SPEAKER_01
I mentioned to you offline that somebody who s a fan of your work is Andrej Karpathy, and he s, amongst many things, also writes occasionally a great blog.
3
SPEAKER_01
He came up with this idea, I don t know if he coined the term, but of Software 2.0.
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SPEAKER_01
where the programming is done in the space of configuring these artificial neural networks.
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SPEAKER_01
Is there some sense in which that would be the future of programming for us humans, where we re
3
SPEAKER_01
less doing Python-like programming and more, how would that look like?
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SPEAKER_01
But basically doing the hyperparameters of something akin to a biological system.
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SPEAKER_01
and watching it go and adjusting it and creating some kind of feedback loop within the system so it corrects itself.
3
SPEAKER_01
And then we watch it over time accomplish the goals we want it to accomplish.
3
SPEAKER_01
Is that kind of the dream of the dogs that you described in the nature paper?
3
SPEAKER_00
Yeah, I mean, that s what you just painted is a very good description of our efforts at regenerative medicine as a kind of somatic psychiatry.
3
SPEAKER_00
So the idea is that you re not trying to micromanage.
3
SPEAKER_00
I mean, think about the limitations of a lot of the medicines today.
3
SPEAKER_00
We try to interact down at the level of pathways, right?
3
SPEAKER_00
So we re trying to micromanage it.
3
SPEAKER_00
What s the problem?
3
SPEAKER_00
Well, one problem is that for almost every medicine other than antibiotics, once you stop it, the problem comes right back.
3
SPEAKER_00
You haven t fixed anything.
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SPEAKER_00
You were addressing symptoms.
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SPEAKER_00
You weren t actually curing anything, again, except for antibiotics.
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SPEAKER_00
That s one problem.
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SPEAKER_00
The other problem is you have a massive amount of side effects because you were trying to interact at the lowest level.
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SPEAKER_00
It s like, I m gonna try to program this computer by changing the melting point of copper.
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SPEAKER_00
Maybe you can do things that way, but my God, it s hard to program at the hardware level.
4
SPEAKER_00
So what I think we re starting to understand is that
4
SPEAKER_00
And by the way, this goes back to what you were saying before about that we could have access to our internal state, right?
4
SPEAKER_00
So people who practice that kind of stuff, right?
4
SPEAKER_00
So yoga and biofeedback and those, those are all the people that uniformly will say things like, well, the body has an intelligence and this and that, right?
4
SPEAKER_00
Like those two sets overlap perfectly, because that s exactly right.
4
SPEAKER_00
Because once you start thinking about it that way, you realize that
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SPEAKER_00
the better locus of control is not always at the lowest level.
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SPEAKER_00
This is why we don t all program with a soldering iron, right?
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SPEAKER_00
We take advantage of the high-level intelligences that are there, which means trying to figure out, okay, which of your tissues can learn?
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SPEAKER_00
What can they learn?
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SPEAKER_00
Why is it that certain drugs stop working after you take them for a while with this habituation, right?
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SPEAKER_00
And so can we understand habituation, sensitization, associative learning?
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SPEAKER_00
these kinds of things in chemical pathways.
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SPEAKER_00
We re going to have a completely different way, I think.
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SPEAKER_00
We re going to have a completely different way of using drugs and of medicine in general when we start focusing on the goal states and on the intelligence of our subsystems as opposed to treating everything as if the only path was micromanagement from chemistry upwards.
4
SPEAKER_01
Well, can you speak to this idea of somatic psychiatry?
4
SPEAKER_01
What are somatic cells?
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SPEAKER_01
How do they form networks that use bioelectricity to have memory and all those kinds of things?
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SPEAKER_01
What are somatic cells, like basics here?
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SPEAKER_00
The somatic cells just means the cells of your body, so much as means body, right?
4
SPEAKER_00
So somatic cells are just the, I m not even specifically making a distinction between somatic cells and stem cells or anything like that.
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SPEAKER_00
I mean, basically all the cells in your body, not just neurons, but all the cells in your body.
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SPEAKER_00
They form electrical networks during embryogenesis, during regeneration.
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SPEAKER_00
What those networks are doing, in part, is processing information about what our current shape is and what the goal shape is.
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SPEAKER_00
Now, how do I know this?
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SPEAKER_00
Because I can give you a couple of examples.
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SPEAKER_00
One example is when we started studying this, we said, okay, here s a planarian.
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SPEAKER_00
A planarian is a flatworm.
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SPEAKER_00
It has one head and one tail normally.
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SPEAKER_00
and the several amazing things about planaria.
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SPEAKER_00
But basically, I think planaria hold the answer to pretty much every deep question of life.
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SPEAKER_00
For one thing, they re similar to our ancestors.
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SPEAKER_00
So, they have true symmetry.
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SPEAKER_00
They have a true brain.
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SPEAKER_00
They re not like earthworms.
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SPEAKER_00
They re a much more advanced life form.
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SPEAKER_00
They have lots of different internal organs, but they re about maybe two centimeters to two in size.
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SPEAKER_00
They have a head and a tail.
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SPEAKER_00
And the first thing is planaria are immortal.
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SPEAKER_00
So they do not age.
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SPEAKER_00
There s no such thing as an old planarian.
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SPEAKER_00
So that right there tells you that these theories of thermodynamic limitations on lifespan are wrong.
4
SPEAKER_00
It s not that well over time, everything degrades.
4
SPEAKER_00
No, planaria can keep it going for probably, you know, how long, if they ve been around, 400 million years, right?
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SPEAKER_00
So these are the actual, so the planaria in our lab are actually in physical continuity with planaria that were here 400 million years ago.
4
SPEAKER_01
So there s planaria that have lived that long, essentially.
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SPEAKER_01
What does it mean, physical continuity?
4
SPEAKER_00
Because what they do is they split in half.
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SPEAKER_00
The way they reproduce is they split in half.
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SPEAKER_00
So the planaria, the back end grabs the petri dish, the front end takes off, and they rip themselves in half.
4
SPEAKER_01
But isn t in some sense we re, like, you are a physical continuation?
4
SPEAKER_00
Yes, except that we go through a bottleneck of one cell, which is the egg.
4
SPEAKER_00
They do not.
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SPEAKER_00
I mean, they can.
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SPEAKER_00
There are certain planaria that... Got it.
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SPEAKER_01
So we go through a very ruthless compression process, and they don t.
4
SPEAKER_00
Yes, like an autoencoder, you know.
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SPEAKER_00
squashed down to one cell and then back out.
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SPEAKER_00
These guys just tear themselves in half.
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SPEAKER_00
And so the other amazing thing about them is they regenerate.
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SPEAKER_00
So you can cut them into pieces.
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SPEAKER_00
The record is, I think, 276 or something like that by Thomas Hunt Morgan.
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SPEAKER_00
And each piece regrows a perfect little worm.
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SPEAKER_00
They know exactly, every piece knows exactly what s missing, what needs to happen.
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SPEAKER_00
In fact, if you chop it in half, as it grows the other half, the original tissue shrinks so that when the new tiny head shows up, they re proportional.
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SPEAKER_00
So it keeps perfect proportion.
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SPEAKER_00
If you starve them, they shrink.
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SPEAKER_00
If you feed them again, they expand.
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SPEAKER_00
Their control, their anatomical control is just insane.
4
SPEAKER_01
Somebody cut them into over 200 pieces?
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SPEAKER_00
Yeah, Thomas Hunt Morgan did.
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SPEAKER_01
Hashtag science.
4
SPEAKER_00
Amazing, yeah, and maybe more.
4
SPEAKER_00
I mean, they didn t have antibiotics back then.
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SPEAKER_00
I bet he lost some due to infection.
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SPEAKER_00
I bet it s actually more than that.
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SPEAKER_00
I bet you could do more than that.
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SPEAKER_01
Humans can t do that.
4
SPEAKER_00
Well, yes, I mean, again, true, except that- Maybe you can at the embryonic level.
4
SPEAKER_00
Well, that s the thing, right?
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SPEAKER_00
So when I talk about this, I say, just remember that as amazing as it is to grow a whole planarian from a tiny fragment, half of the human population can grow a full body from one cell.
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SPEAKER_00
So development is really, you can look at development as just an example of regeneration.
4
SPEAKER_01
Yeah, to think, we ll talk about regenerative medicine, but there s some sense it would be like that worm in like 500 years, where I can just go, regrow a hand.
4
SPEAKER_00
Yep, with a given time, it takes time to grow large things, but yeah, I think so.
4
SPEAKER_01
You can probably, why not accelerate?
4
SPEAKER_01
Oh, biology takes its time?
4
SPEAKER_00
I m not going to say anything is impossible, but I don t know of a way to accelerate these processes.
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SPEAKER_00
I think it s possible.
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SPEAKER_00
I think we are going to be regenerative, but I don t know of a way to make it fast.
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SPEAKER_01
I just think people from a few centuries from now will be like, well, they used to have to wait.
4
SPEAKER_01
a week for the hand to regrow.
4
SPEAKER_01
It s like when the microwave was invented.
4
SPEAKER_01
You can toast your, what s that called when you put a cheese on a toast?
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SPEAKER_01
It s delicious is all I know.
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SPEAKER_01
I m blanking.
4
SPEAKER_01
Anywho, all right, so planaria.
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SPEAKER_01
Why were we talking about the magical planaria that they have the mystery of life?
4
SPEAKER_00
Yeah, so the reason we re talking about planaria is not only are they immortal, okay, not only do they regenerate every part of the body,
4
SPEAKER_00
They generally don t get cancer, which we can talk about why that s important.
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SPEAKER_00
They re smart, they can learn things, so you can train them.
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SPEAKER_00
And it turns out that if you train a planarian and then cut their heads off, the tail will regenerate a brand new brain that still remembers the original information.
4
SPEAKER_01
Do they have a bioelectrical network going on or no?
4
SPEAKER_00
Yes, yes.
4
SPEAKER_01
So their somatic cells are forming a network, and that s what you mean by a true brain?
4
SPEAKER_01
What s the requirement for a true brain?
4
SPEAKER_00
I d like everything else, it s a continuum, but a true brain has certain characteristics as far as the density, like a localized density of neurons that guides behavior.
4
SPEAKER_01
In the head.
4
SPEAKER_00
Exactly.
4
SPEAKER_00
Connected to the head.
4
SPEAKER_00
Exactly.
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SPEAKER_00
If you cut their head off, the tail doesn t have, it doesn t do anything, it just sits there until the new brain is, you know, until a new brain regenerates.
4
SPEAKER_00
They have all the same neurotransmitters that you and I have.
4
SPEAKER_00
But here s why, here s why we re talking about them in this context.
4
SPEAKER_00
So here s your planaria, you cut off the head, you cut off the tail, you have a middle fragment.
4
SPEAKER_00
That middle fragment has to make one head and one tail.
4
SPEAKER_00
How does it know how many of each to make and where do they go?
4
SPEAKER_00
How come it doesn t switch?
4
SPEAKER_00
How come, right?
4
SPEAKER_00
So we did a very simple thing and we said, okay, let s make the hypothesis that there s a somatic electrical network that remembers the correct pattern and that what it s doing is recalling that memory and building to that pattern.
4
SPEAKER_00
So what we did was we used a way to visualize electrical activity in these cells, right?
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SPEAKER_00
It s a variant of what people use to look for electricity in the brain.
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SPEAKER_00
And we saw that that fragment has a very particular electrical pattern.
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SPEAKER_00
You can literally see it once we develop the technique.
4
SPEAKER_00
It has a very particular electrical pattern that shows you where the head and the tail goes, right?
4
SPEAKER_00
You can just see it.
4
SPEAKER_00
And then we said, okay, well, now let s test the idea that that s a memory that actually controls where the head and the tail goes.
4
SPEAKER_00
Let s change that pattern.
4
SPEAKER_00
So basically, incept a false memory.
4
SPEAKER_00
And so what you can do is you can do that in many different ways.
4
SPEAKER_00
One way is with drugs that target ion channels to say, and so you pick these drugs and you say, okay, I m gonna do it so that instead of this one head, one tail electrical pattern, you have a two-headed pattern, right?
4
SPEAKER_00
You re just editing the electrical information in the network.
4
SPEAKER_00
When you do that, guess what the cells build?
4
SPEAKER_00
They build a two-headed worm.
4
SPEAKER_00
And the coolest thing about it, now no genetic changes, so we haven t touched the genome.
4
SPEAKER_00
The genome is totally wild type.
4
SPEAKER_00
But the amazing thing about it is that when you take these two-headed animals and you cut them into pieces again,
4
SPEAKER_00
some of those pieces will continue to make two-headed animals.
4
SPEAKER_00
So that information, that memory, that electrical circuit, not only does it hold the information for how many heads, not only does it use that information to tell the cells what to do to regenerate, but it stores it.
4
SPEAKER_00
Once you ve reset it, it keeps.
4
SPEAKER_00
And we can go back, we can take a two-headed animal and put it back to one-headed.
4
SPEAKER_00
So now imagine, so there s a couple of interesting things here that have implications for understanding of genomes and things like that.
4
SPEAKER_00
Imagine I take this two-headed animal, oh, and by the way, when they reproduce, when they tear themselves in half, you still get two-headed animals.
4
SPEAKER_00
So imagine I take them and I throw them in the Charles River over here.
4
SPEAKER_00
So 100 years later, some scientists come along and they scoop up some samples and they go, oh, there s a single-headed form and a two-headed form.
4
SPEAKER_00
Wow, a speciation event, cool.
4
SPEAKER_00
Let s sequence the genome and see what happened.
4
SPEAKER_00
Genomes are identical, there s nothing wrong with the genome.
4
SPEAKER_00
So if you ask the question, how does, so this goes back to your very first question is where do body plants come from, right?
4
SPEAKER_00
How does the planarian know how many heads it s supposed to have?
4
SPEAKER_00
Now, it s interesting because you could say DNA, but as it turns out, the DNA produces a piece of hardware that by default
4
SPEAKER_00
says one head.
4
SPEAKER_00
The way that when you turn on a calculator, by default, it s a zero every single time, right?
4
SPEAKER_00
When you turn it on, it just says zero.
4
SPEAKER_00
But it s a programmable calculator, as it turns out.
4
SPEAKER_00
So once you ve changed that, next time it won t say zero.
4
SPEAKER_00
It ll say something else.
4
SPEAKER_00
And the same thing here.
4
SPEAKER_00
So you can make one-headed, two-headed, you can make no-headed worms.
4
SPEAKER_00
We ve done some other things along these lines, some other really weird constructs.
4
SPEAKER_00
So again, it s really important.
4
SPEAKER_00
The hardware-software distinction is really important, because the hardware is essential, because without proper hardware, you re never going to get to the right physiology of having that memory.
4
SPEAKER_00
But once you have it, it doesn t fully determine what the information is going to be.
4
SPEAKER_00
You can have other information in there, and it s reprogrammable by us, by bacteria, by various parasites, probably, things like that.
4
SPEAKER_00
The other amazing thing about these planarias, think about this,
4
SPEAKER_00
most animals when we get a mutation in our bodies our children don t inherit it right so you could go on you could run around for 50-60 years getting mutations your children don t have those mutations because we go through the egg stage planaria tear themselves in half and that s how they reproduce so for 400 million years they keep every mutation that they ve had that doesn t kill the cell that it s in so when you look at these planaria their bodies are what s called mixoploid meaning that every cell might have a different number of chromosomes they look like a tumor if you look at the
4
SPEAKER_00
the genome is an incredible mess because they accumulate all this stuff and yet their body structure is, they are the best regenerators on the planet, their anatomy is rock solid even though their genome is all kinds of crap.
4
SPEAKER_00
So this is kind of a scandal, right, that you know when we learn
4
SPEAKER_00
What are genomes?
4
SPEAKER_00
What genomes determine your body?
4
SPEAKER_00
Okay, why does the animal with the worst genome have the best anatomical control, the most cancer resistant, the most regenerative, right?
4
SPEAKER_00
Really, we re just beginning to start to understand this relationship between the genomically determined hardware, and by the way, just as of a couple of months ago, I think I now somewhat understand why this is, but it s really a major puzzle.
4
SPEAKER_01
I mean, that really throws a wrench into the whole nature versus nurture.
4
SPEAKER_01
Because you usually associate electricity with the nurture.
4
SPEAKER_01
and the hardware with the nature, and there s just this weird integrated mess that propagates through generations.
4
SPEAKER_00
Yeah, it s much more fluid, it s much more complex.
4
SPEAKER_00
You can imagine what s happening here, just imagine the evolution of an animal like this, that multiscale, this goes back to this multiscale competency, right?
4
SPEAKER_00
Imagine that you have an animal that,
4
SPEAKER_00
that where its tissues have some degree of multi-scale competency.
4
SPEAKER_00
So for example, like we saw in the tadpole, if you put an eye on its tail, they can still see out of that eye, right?
4
SPEAKER_00
There s incredible plasticity.
4
SPEAKER_00
So if you have an animal and it comes up for selection and the fitness is quite good,
4
SPEAKER_00
Evolution doesn t know whether the fitness is good because the genome was awesome or because the genome was kind of junky, but the competency made up for it, right?
4
SPEAKER_00
And things kind of ended up good.
4
SPEAKER_00
So what that means is that the more competency you have, the harder it is for selection to pick the best genomes.
4
SPEAKER_00
It hides information, right?
4
SPEAKER_00
And so that means that, so what happens, you know, evolution basically starts, all the hard work is being done to increase the competency.
4
SPEAKER_00
because it s harder and harder to see the genomes.
4
SPEAKER_00
And so I think in planaria what happened is that there s this runaway phenomenon where all the effort went into the algorithm such that we know you ve got a crappy genome, we can t clean up the genome, we can t keep track of it.
4
SPEAKER_00
So what s going to happen is what survives are the algorithms that can create a great worm no matter what the genome is.
4
SPEAKER_00
So everything went into the algorithm, which of course then reduces the pressure on keeping a clean genome.
4
SPEAKER_00
So this idea of right and different animals have this in different to different levels.
4
SPEAKER_00
But this idea of putting energy into an algorithm that does not overtrain on priors, right?
4
SPEAKER_00
It can t assume I mean, I think biology is this way in general, evolution doesn t take the past too seriously, because it makes these basically problem solving machines as opposed to like exactly what you know, to deal with exactly what happened last time.
4
SPEAKER_01
Yeah, problem solving versus memory recall.
4
SPEAKER_01
So a little memory, but a lot of problem solving.
4
SPEAKER_00
I think so, yeah, in many cases, yeah.
4
SPEAKER_00
Problem solving.
4
SPEAKER_01
I mean, it s incredible that those kinds of systems are able to be constructed, especially how much they contrast with the way we build problem solving systems in the AI world.
4
SPEAKER_01
Back to xenobots.
4
SPEAKER_01
I m not sure if we ever described how xenobots are built, but you have a paper titled Biological Robots, Perspectives on an Emerging Interdisciplinary Field.
4
SPEAKER_01
In the beginning, you mentioned that the word xenobots is controversial.
4
SPEAKER_01
Do you guys get in trouble for using xenobots?
4
SPEAKER_01
Or what, do people not like the word xenobots?
4
SPEAKER_01
Are you trying to be provocative with the word xenobots versus biological robots?
4
SPEAKER_01
I don t know.
4
SPEAKER_01
Is there some drama that we should be aware of?
4
SPEAKER_00
So there s a little bit of drama.
4
SPEAKER_00
I think the drama is basically related to people having very fixed ideas about what terms mean.
4
SPEAKER_00
And I think in many cases, these ideas are completely out of date with where science is now.
4
SPEAKER_00
And for sure, they re out of date with what s going to be.
4
SPEAKER_00
These concepts are not going to survive the next couple of decades.
4
SPEAKER_00
So if you ask a person, and including
4
SPEAKER_00
you know, a lot of people in biology who kind of want to keep a sharp distinction between biologicals and robots, right?
4
SPEAKER_00
See, what s a robot?
4
SPEAKER_00
Well, a robot, it comes out of a factory.
4
SPEAKER_00
It s made by humans.
4
SPEAKER_00
It is boring.
4
SPEAKER_00
It is a meaning that you can predict everything it s going to do.
4
SPEAKER_00
It s made of metal and certain other inorganic materials.
4
SPEAKER_00
Living organisms are magical.
4
SPEAKER_00
They arise, right?
4
SPEAKER_00
And so on.
4
SPEAKER_00
So there s these distinctions.
4
SPEAKER_00
I think these distinctions, I think, were never good.
4
SPEAKER_00
but they re going to be completely useless going forward.
4
SPEAKER_00
And so part of, there s a couple of papers that, that s one paper, and there s another one that Josh Bongard and I wrote where we really attack the terminology.
4
SPEAKER_00
And we say these binary categories are based on very,
4
SPEAKER_00
non-essential kind of surface limitations of technology and imagination that were true before, but they ve got to go.
4
SPEAKER_00
And so we call them xenobots.
4
SPEAKER_00
So for Xenopus laevis, it s the frog that these guys are made of, but we think it s an example of a biobot technology because
4
SPEAKER_00
Ultimately, once we understand how to communicate and manipulate the inputs to these cells, we will be able to get them to build whatever we want them to build.
4
SPEAKER_00
And that s robotics, right?
4
SPEAKER_00
It s the rational construction of machines that have useful purposes.
4
SPEAKER_00
I absolutely think that this is a robotics platform, whereas some biologists don t.
4
SPEAKER_01
but it s built in a way that all the different components are doing their own computation.
4
SPEAKER_01
So in a way that we ve been talking about, so you re trying to do top-down control on that biological system.
4
SPEAKER_00
And in the future, all of this will merge together because of course, at some point, we re gonna throw in synthetic biology circuits, right?
4
SPEAKER_00
New transcriptional circuits to get them to do new things.
4
SPEAKER_00
Of course, we ll throw some of that in, but we specifically stayed away from all of that because in the first few papers, and there s some more coming down the pike that are, I think, gonna be pretty dynamite,
4
SPEAKER_00
that we want to show what the native cells are made of.
4
SPEAKER_00
Because what happens is, you know, if you engineer the heck out of them, right?
4
SPEAKER_00
If we were to put in new, you know, new transcription factors and some new metabolic machinery and whatever, people will say, well, okay, you engineered this and you made it do whatever and fine.
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I wanted to show, and the whole team wanted to show, the plasticity and the intelligence and the biology
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SPEAKER_01
what does it do that s surprising before you even start manipulating the hardware in that way?
5
SPEAKER_00
Yeah, don t try to over control the thing, let it flourish.
5
SPEAKER_00
The full beauty of the biological system.
5
SPEAKER_00
Why Xenopus laevis, how do you pronounce it?
5
SPEAKER_01
The frog.
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SPEAKER_01
Xenopus laevis, yeah.
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SPEAKER_01
Yeah, it s a very popular.
5
SPEAKER_00
Why this frog?
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It s been used since I think the 50s.
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It s just very convenient because
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You can, you know, we keep the adults in this very fine frog habitat.
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They lay eggs, they lay tens of thousands of eggs at a time.
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The eggs develop right in front of your eyes.
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It s the most magical thing you can see because normally, you know, if you were to deal with mice or rabbits or whatever, you don t see the early stages, right, because everything s inside the mother.
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Everything s in a petri dish at room temperature.
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So you just, you have an egg, it s fertilized, and you can just watch it divide and divide and divide, and all the organs form, you can just see it.
5
SPEAKER_01
And at that point, the community has developed lots of different tools for understanding what s going on and also for manipulating, right?
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SPEAKER_01
So people use it for understanding birth defects and neurobiology and cancer immunology also.
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SPEAKER_00
So you get the whole embryogenesis in the Petri dish.
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SPEAKER_01
That s so cool to watch.
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SPEAKER_00
Is there videos of this?
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SPEAKER_01
Oh yeah, yeah, yeah.
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There s amazing videos online.
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I mean, mammalian embryos are super cool too.
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For example, monozygotic twins are what happens when you cut a mammalian embryo in half.
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You don t get two half bodies, you get two perfectly normal bodies because it s a regeneration event.
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Development is just the kind of regeneration, really.
5
SPEAKER_00
And why this particular frog?
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SPEAKER_00
It s just because they were doing it in the 50s.
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SPEAKER_01
It breeds well in, you know, it s easy to raise in the laboratory and it s very prolific and all the tools, basically for decades, people have been developing tools.
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SPEAKER_01
There s other pieces, some people use other frogs, but I have to say, this is important, xenobots
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are fundamentally not anything about frogs.
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So I can t say too much about this because it s not published and peer-reviewed yet, but we ve made xenobots out of other things that have nothing to do with frogs.
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SPEAKER_01
This is not a frog phenomenon.
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SPEAKER_01
We started with frog because it s so convenient, but this plasticity is not related to the fact that they re frogs.
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SPEAKER_00
What happens when you kiss it?
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SPEAKER_00
Does it turn into a prince?
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SPEAKER_00
No.
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SPEAKER_00
Or a princess?
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SPEAKER_00
Which way?
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SPEAKER_00
Prince.
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SPEAKER_01
Yeah, prince.
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SPEAKER_01
Yeah, that s an experiment that I don t believe we ve done.
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SPEAKER_01
And if we have, I don t want to know about it.
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SPEAKER_00
Well, we can collaborate.
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SPEAKER_00
I can take on the lead on that effort.
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SPEAKER_00
Okay, cool.
5
SPEAKER_00
how does the cells coordinate?
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SPEAKER_00
Let s focus in on just the embryogenesis.
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So there s one cell.
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So it divides, doesn t have to be very careful about what each cell starts doing once they divide.
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And when there s three of them, it s like the co-founders or whatever, slow down, you re responsible for this.
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SPEAKER_00
When do they become specialized and how do they coordinate that specialization?
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SPEAKER_01
So this is the basic science of developmental biology.
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There s a lot known about all of that.
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SPEAKER_01
But I ll tell you what I think is kind of the most important part, which is, yes, it s very important who does what.
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However, because going back to this issue of why I made this claim that biology doesn t take the past too seriously.
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And what I mean by that is it doesn t assume that everything is the way it s expected to be.
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Right.
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And here s an example of that.
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This was done, this was an old experiment going back to the 40s, but basically imagine, it s a newt, a salamander, and it s got these little tubules that go to the kidneys, right, this little tube.
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Take a cross-section of that tube, you see 8 to 10 cells that have cooperated to make this little tube in cross-section, right?
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SPEAKER_01
So one amazing thing you can do is you can mess with the very early cell division to make the cells gigantic, bigger.
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You can make them different sizes.
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You can force them to be different sizes.
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So if you make the cells different sizes, the whole nude is still the same size.
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So if you take a cross-section through that tubule, instead of 8 to 10 cells, you might have 4 or 5, or you might have 3, until
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you make the cell so enormous that one single cell wraps around itself.
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and gives you that same large-scale structure with a completely different molecular mechanism.
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So now instead of cell-to-cell communication to make a tubule, instead of that, it s one cell using the cytoskeleton to bend itself around.
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So think about what that means.
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In the service of a large-scale, talk about top-down control, right?
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In the service of a large-scale anatomical feature, different molecular mechanisms get called up.
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SPEAKER_01
So now, think about this.
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You re a new cell and you re trying to make an embryo.
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If you had a fixed idea of who was supposed to do what, you d be screwed because now your cells are gigantic, nothing would work.
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SPEAKER_01
There s an incredible tolerance for changes in the size of the parts, in the amount of DNA in those parts, all sorts of stuff.
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The life is highly interoperable.
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You can put electrodes in there, you can put weird nanomaterials, it still works.
5
SPEAKER_01
It s it s this is that problem solving action, right?
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It s able to do what it needs to do, even when circumstances change.
5
SPEAKER_01
That is, you know, the hallmark of intelligence, right?
5
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William James defined intelligence as the ability to get to the same goal by different means.
5
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That s this.
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You get to the same goal by completely different means.
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And so so so why am I bringing this up is just to say that, yeah, it s important for the cells to do the right stuff, but they have incredible tolerances for things not being what you expect.
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and to still get their job done.
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So if you re, you know, all of these things are not hardwired.
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There are organisms that might be hardwired.
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For example, the nematode C. elegans.
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In that organism, every cell is numbered, meaning that every C. elegans has exactly the same number of cells as every other C. elegans.
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They re all in the same place.
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They all divide.
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There s literally a map of how it works.
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In that sort of system, it s much more cookie cutter.
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But most organisms are incredibly plastic in that way.
5
SPEAKER_00
Is there something particularly magical to you about the whole developmental biology process?
5
SPEAKER_00
Is there something you could say, because you just said it, they re very good at accomplishing the goal, the job they need to do, the competency thing, but you get a freaking organism from one cell.
5
SPEAKER_00
It s like,
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SPEAKER_00
I mean, it s very hard to intuit that whole process, to even think about reverse engineering that process.
5
SPEAKER_01
Right, very hard, to the point where I often, just imagine, I sometimes ask my students to do this thought experiment.
5
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Imagine you were shrunk down to the scale of a single cell.
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And you were in the middle of an embryo and you were looking around at what s going on.
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And the cells running around, some cells are dying.
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Every time you look, it s kind of a different number of cells for most organisms and so on.
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SPEAKER_01
I think that if you didn t know what embryonic development was, you would have no clue that what you re seeing is always going to make the same thing.
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Never mind knowing what that is.
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Never mind being able to say, even with full genomic information, being able to say, what the hell are they building?
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We have no way to do that.
5
SPEAKER_01
But just even to guess that, wow, the outcome of all this activity is
5
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it s always gonna build the same thing.
5
SPEAKER_00
The imperative to create the final you as you are now is there already.
5
SPEAKER_00
So if you start from the same embryo, you create a very similar organism.
5
SPEAKER_01
Yeah, except for cases like the xenobots, when you give them a different environment, they come up with a different way to be adaptive in that environment.
5
SPEAKER_01
But overall, I mean, so I think to kind of summarize it, I think what evolution is really good at is creating hardware that has a very stable baseline mode, meaning that left to its own devices, it s very good at doing the same thing.
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SPEAKER_01
but it has a bunch of problem-solving capacity such that if any assumptions don t hold, if your cells are a weird size, or you get the wrong number of cells, or there s somebody stuck an electrode halfway through the body, whatever, it will still get most of what it needs to do done.
5
SPEAKER_00
You ve talked about the magic and the power of biology here.
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SPEAKER_00
If we look at the human brain, how special is the brain in this context?
5
SPEAKER_00
You re kind of minimizing the importance of the brain, or lessening its, we think of all the special computation happens in the brain, everything else is like the help.
5
SPEAKER_00
You re kind of saying that the whole thing is doing computation.
5
SPEAKER_00
But nevertheless, how special is the human brain in this full context of biology?
5
SPEAKER_01
Yeah, I mean, look, there s no getting away from the fact that the human brain allows us to do things that we could not do without it.
5
SPEAKER_00
You can say the same thing about the liver.
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SPEAKER_01
Yeah, no, this is true.
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SPEAKER_01
And so, you know, my goal is not, no, you re right, my goal is not- You re just being polite to the brain right now.
5
SPEAKER_00
Well, look- You re being a politician.
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SPEAKER_00
Like, listen, everybody has a use.
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SPEAKER_00
Everybody has a role, yeah.
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SPEAKER_00
It s a very important role.
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SPEAKER_00
That s right.
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SPEAKER_00
We have to acknowledge the importance of the brain, you know?
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SPEAKER_01
there are more than enough people who are cheerleading the brain, right?
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So I don t feel like nothing I say is going to reduce people s excitement about the human brain.
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And so I emphasize other things.
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I don t think it gets too much credit.
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I think other things don t get enough credit.
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I think the human brain is incredible and special and all that.
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SPEAKER_01
I think other things need more credit.
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SPEAKER_01
And I also think that
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And I m sort of this way about everything.
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I don t like binary categories about almost anything.
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SPEAKER_01
I like a continuum.
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SPEAKER_01
And the thing about the human brain is that by accepting that as some kind of an important category or essential thing, we end up with all kinds of weird pseudo problems and conundrums.
5
SPEAKER_01
So for example,
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SPEAKER_01
When we talk about it, you know, if you want to talk about ethics and other things like that, and what, you know, this idea that surely if we look out into the universe, surely we don t believe that this human brain is the only way to be sentient, right?
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SPEAKER_01
Surely we don t, you know, and to have high-level cognition.
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SPEAKER_01
I can t even wrap my mind around this idea that that is the only way to do it.
5
SPEAKER_01
No doubt there are other architectures made of completely different principles that achieve the same thing.
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SPEAKER_01
And once we believe that, then that tells us something important.
5
SPEAKER_01
It tells us that things that are not quite human brains, or chimeras of human brains and other tissue, or human brains or other kinds of brains and novel configurations, or things that are sort of brains but not really, or plants or embryos or whatever,
5
SPEAKER_01
might also have important cognitive status.
5
SPEAKER_01
So that s the only thing.
5
SPEAKER_01
I think we have to be really careful about treating the human brain as if it was some kind of like sharp binary category, you know, you are or you aren t.
5
SPEAKER_01
I don t believe that exists.
5
SPEAKER_00
So when we look out at all the beautiful variety of semi-biological architectures out there in the universe, how many intelligent alien civilizations do you think are out there?
5
SPEAKER_01
Boy, I have no expertise in that whatsoever.
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SPEAKER_00
You haven t met any?
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SPEAKER_01
I have met the ones we ve made.
5
SPEAKER_00
I mean, exactly.
5
SPEAKER_00
In some sense, with synthetic biology, are you not creating aliens?
5
SPEAKER_01
I absolutely think so, because look, all of life, all standard model systems are an N of one course of evolution on Earth, right?
5
SPEAKER_01
And trying to make conclusions about biology from looking at life on Earth is like testing your theory on the same data that generated it.
5
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It s all kind of like locked in.
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SPEAKER_01
So we absolutely have to create novel
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examples that have no history on earth that don t, you know, xenobots have no history of selection to be a good xenobot.
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SPEAKER_01
The cells have selection for various things, but the xenobot itself never existed before.
5
SPEAKER_01
And so we can make chimeras, you know, we make frogolotls that are, you know, sort of half frog, half axolotl.
5
SPEAKER_01
You can make all sorts of high broads, right?
5
SPEAKER_01
Constructions of living tissue with robots and whatever.
5
SPEAKER_01
We need to be making these things until we find actual aliens, because otherwise we re just looking at an N of one set of examples.
5
SPEAKER_01
All kinds of frozen accidents of evolution and so on.
5
SPEAKER_01
We need to go beyond that to really understand biology.
5
SPEAKER_00
But we re still, even when you do a synthetic biology, you re locked in to the basic components.
5
SPEAKER_00
of the way biology is done on this earth.
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SPEAKER_00
And also the basic constraints of the environment, even artificial environments that construct in the lab are tied up to the environment.
5
SPEAKER_00
I mean, what do you, okay, let s say there is, I mean, what I think is there s
5
SPEAKER_00
a nearly infinite number of intelligent civilizations living or dead out there.
5
SPEAKER_00
If you pick one out of the box, what do you think it would look like?
5
SPEAKER_00
So, when you think about synthetic biology, or creating synthetic organisms, how hard is it to create something that s very different?
5
SPEAKER_01
Yeah, I think it s very hard to create something that s very different, right?
5
SPEAKER_01
We are just locked in both experimentally and in terms of our imagination, right?
5
SPEAKER_01
It s very hard.
5
SPEAKER_00
And you also emphasized several times the idea of shape.
5
SPEAKER_00
The individual cell get together with other cells and they re gonna build a shape.
5
SPEAKER_00
So it s shape and function, but shape is a critical thing.
5
SPEAKER_01
Yeah.
5
SPEAKER_01
So here, I ll take a stab.
5
SPEAKER_01
I mean, I agree with you to whatever extent that we can say anything.
5
SPEAKER_01
I do think that there s probably an infinite number of different architectures that are with interest in cognitive properties out there.
5
SPEAKER_01
What can we say about them?
5
SPEAKER_01
I don t think we can rely on any of the typical stuff, carbon-based.
5
SPEAKER_01
I think all of that is just us having a lack of imagination.
5
SPEAKER_01
I think the things that are going to be universal, if anything is, are things, for example, driven by resource limitation.
5
SPEAKER_01
The fact that you are fighting a hostile world and you have to draw a boundary between yourself and the world somewhere.
5
SPEAKER_01
The fact that that boundary is not given to you by anybody, you have to assume it, you know, estimate it yourself.
5
SPEAKER_01
and the fact that you have to coarse-grain your experience and the fact that you re going to try to minimize surprise and the fact that, like, these are the things that I think are fundamental about biology.
5
SPEAKER_01
None of the, you know, the facts about the genetic code or even the fact that we have genes or the biochemistry of it.
5
SPEAKER_01
I don t think any of those things are fundamental.
5
SPEAKER_01
But it s going to be a lot more about the information and about the creation of the self.
5
SPEAKER_01
The fact that
5
SPEAKER_01
So in my framework, cells are demarcated by the scale of the goals that they can pursue.
5
SPEAKER_01
So from little tiny local goals to like massive, you know, planetary scale goals for certain humans and everything in between.
5
SPEAKER_01
So you can draw this like cognitive light cone that determines the scale of the goals you could possibly pursue.
5
SPEAKER_01
I think those kinds of frameworks like that, like active inference and so on, are going to be universally applicable, but none of the other things that are typically discussed.
5
SPEAKER_00
Quick pause.
5
SPEAKER_00
Do you need a bathroom break?
5
SPEAKER_01
We were just talking about, you know, aliens and all that.
5
SPEAKER_01
That s a funny thing, which is, I don t know if you ve seen them.
5
SPEAKER_01
There s a kind of debate that goes on about cognition in plants.
5
SPEAKER_01
And what can you say about different kinds of computation and cognition in plants?
5
SPEAKER_01
And I always, I always look at that some way.
5
SPEAKER_01
If you re weirded out by cognition in plants, you re not ready for exobiology, right?
5
SPEAKER_01
If, you know, something that s that similar here on earth is already like freaking you out, then I think there s going to be all kinds of cognitive life out there that we re going to have a really hard time recognizing.
5
SPEAKER_00
I think robots will help us expand our mind about cognition.
5
SPEAKER_00
Either that or, like xenobots, and they maybe becomes the same thing, is really when the human engineers the thing, at least in part,
5
SPEAKER_00
and then is able to achieve some kind of cognition that s different than what you re used to, then you start to understand like, oh, every living organism s capable of cognition.
5
SPEAKER_00
Oh, I need to kind of broaden my understanding of what cognition is.
5
SPEAKER_00
But do you think plants, like when you eat them, are they screaming?
5
SPEAKER_01
I don t know about screaming.
5
SPEAKER_01
I think you have to.
5
SPEAKER_00
That s what I think when I eat a salad.
5
SPEAKER_01
Yeah.
5
SPEAKER_00
Good.
5
SPEAKER_01
Yeah.
5
SPEAKER_01
I think you have to scale down the expectations in terms of right.
5
SPEAKER_01
So, so probably they re not screaming in the way that we would be screaming.
5
SPEAKER_01
However, there s plenty of data on plants being able to, um, to do anticipation and certain kinds of memory and, and, and so on.
5
SPEAKER_01
Um,
5
SPEAKER_01
I think, you know, what you just said about robots, I hope you re right.
5
SPEAKER_01
And I hope that s but there s two there s two ways that people can take that.
5
SPEAKER_01
Right.
5
SPEAKER_01
So one way is exactly what you just said to try to kind of expand their expand their their their notions for that category.
5
SPEAKER_01
The other way people often go is they just sort of define the term is if if if it s not a natural product, it s it s just faking.
5
SPEAKER_01
Right.
5
SPEAKER_01
It s not really intelligence if it was made by somebody else because it s
6
SPEAKER_00
same.
6
SPEAKER_00
It s the same thing.
6
SPEAKER_00
They can see how it s done.
6
SPEAKER_00
And once you see how it s like a magic trick, when you see how it s done, it s not as fun anymore.
6
SPEAKER_00
And I think people have a real tendency for that.
6
SPEAKER_00
And they sort of, which I find really strange in the sense that if somebody said to me,
6
SPEAKER_00
we have this sort of blind, like a hill climbing search, and then we have a really smart team of engineers, which one do you think is gonna produce a system that has good intelligence?
6
SPEAKER_00
I think it s really weird to say that it only comes from the blind search, right?
6
SPEAKER_00
It can t be done by people who, by the way, can also use evolutionary techniques if they want to, but also rational design.
6
SPEAKER_00
I think it s really weird to say that real intelligence only comes from natural evolution.
6
SPEAKER_00
So I hope you re right.
6
SPEAKER_00
I hope people take it the other way.
6
SPEAKER_01
But there s a nice shortcut.
6
SPEAKER_01
So I work with Lego robots a lot now for my own personal pleasure.
6
SPEAKER_01
Not in that way, internet.
6
SPEAKER_01
So four legs.
6
SPEAKER_01
And one of the things that changes my experience of the robots a lot is when I can t understand why I did a certain thing.
6
SPEAKER_01
And there s a lot of ways to engineer that.
6
SPEAKER_01
me, the person that created the software that runs it, there s a lot of ways for me to build that software in such a way that I don t exactly know why it did a certain basic decision.
6
SPEAKER_01
Of course, as an engineer, you can go in and start to look at logs, you can log all kind of data, sensory data, the decisions you made, all the outputs in your own networks and so on.
6
SPEAKER_01
But I also try to really experience that surprise and that really experience as another person would that totally doesn t know how it s built.
6
SPEAKER_01
And I think the magic is there in not knowing how it works.
6
SPEAKER_01
I think biology does that for you through the layers of abstraction.
6
SPEAKER_01
Because nobody really knows what s going on inside the biologicals.
6
SPEAKER_01
Like each one component is clueless about the big picture.
6
SPEAKER_00
I think there s actually really cheap systems that can illustrate that kind of thing, which is even like, you know, fractals, right?
6
SPEAKER_00
Like you have a very small, short formula in Z and you see it and there s no magic, you re just gonna crank through, you know, Z squared plus C, whatever, you re just gonna crank through it.
6
SPEAKER_00
But the result of it is this incredibly rich, beautiful image, right?
6
SPEAKER_00
That just like, wow, all of that was in this like 10 character long string, like amazing.
6
SPEAKER_00
the fact that you can, you can know everything there is to know about the details and the process and all the parts and everything like there s literally no magic of any kind there.
6
SPEAKER_00
And yet the outcome is something that you would never have expected.
6
SPEAKER_00
And it s just it just, you know, is incredibly rich and complex and beautiful.
6
SPEAKER_00
So there s a lot of that.
6
SPEAKER_01
You write that you work on developing conceptual frameworks for understanding unconventional cognition, so the kind of thing we ve been talking about.
6
SPEAKER_01
I just like the term unconventional cognition.
6
SPEAKER_01
And you want to figure out how to detect, study, and communicate with a thing.
6
SPEAKER_01
You ve already mentioned a few examples, but what is unconventional cognition?
6
SPEAKER_01
Is it as simply as everything outside of what we define usually as cognition, cognitive science, the stuff going on between our ears?
6
SPEAKER_01
Or is there some deeper way to get at the fundamentals of what is cognition?
6
SPEAKER_00
Yeah, I think like, and I m certainly not the only person who works in unconventional cognition.
6
SPEAKER_01
So it s the term used.
6
SPEAKER_00
Yeah, that s one that I so so I ve coined a number of weird terms, but that s not one of mine like that That s an existing thing.
6
SPEAKER_00
So so for example somebody like andy adamatsky who um, I don t know if you ve if you ve had him on if you haven t you should he s a he s a he s a you know, Very interesting guy.
6
SPEAKER_00
He s a computer scientist and he does unconventional cognition and slime molds and all kinds of weird Um, he s a real weird weird cat really interesting.
6
SPEAKER_00
Anyway, so so that s um, you know, there s a bunch of terms that i ve come up with but that s not one of mine, so
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SPEAKER_00
I think like many terms, that one is really defined by the times, meaning that things that are unconventional cognition today are not going to be considered unconventional cognition at some point.
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It s one of those things.
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SPEAKER_00
It s, you know, it s this really deep question of how do you recognize, communicate with, classify cognition when you cannot rely on the typical milestones, right?
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SPEAKER_00
So typical, you know, again, if you stick with the history of life on earth, like these exact model systems, you would say, ah, here s a particular structure of the brain, and this one has fewer of those, and this one has a bigger frontal cortex, and this one,
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So these are landmarks that we re used to, and it allows us to make very rapid judgments about things.
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But if you can t rely on that, either because you re looking at a synthetic thing or an engineered thing or an alien thing, then what do you do?
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And so that s what I m really interested in.
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I m interested in mind in all of its possible implementations, not just the obvious ones that we know from looking at brains here on Earth.
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Whenever I think about something like unconventional cognition, I think about cellular automata.
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I m just captivated by the beauty of the thing.
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the fact that from simple little objects you can create such beautiful complexity that very quickly you forget about the individual objects and you see the things that it creates as its own organisms.
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That blows my mind every time.
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SPEAKER_01
Honestly, I could full-time just,
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eat mushrooms and watch cellular automata.
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SPEAKER_01
Don t even have to do mushrooms, just cellular automata.
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SPEAKER_01
It feels like, I mean, from the engineering perspective, I love when a very simple system captures something really powerful, because then you can study that system to understand something fundamental about complexity, about life on Earth.
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SPEAKER_01
Anyway, how do I communicate with a thing?
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SPEAKER_01
If a cellular automata can do cognition, if a plant can do cognition, if a xenobot can do cognition, how do I whisper in its ear and get an answer back to how do I have a conversation?
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SPEAKER_01
How do I have a xenobot on a podcast?
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SPEAKER_00
It s a really, really interesting line of investigation that opens up.
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I mean, we ve thought about this.
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SPEAKER_00
So you need a few things.
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You need to understand the space in which they live.
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So not just the physical modality, like can they see light, can they feel vibration?
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I mean, that s important, of course, because that s how you deliver your message.
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But not just the ideas for a communication medium, not just the physical medium, but saliency, right?
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So what are important to this?
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What s important to this system?
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And systems have all kinds of different levels of sophistication of what you could expect to get back.
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And I think what s really important, I call this the spectrum of persuadability, which is this idea that when you re looking at a system, you can t assume where on the spectrum it is.
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You have to do experiments.
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For example, if you look at a gene regulatory network, which is just a bunch of nodes that turn each other on and off at various rates, you might look at that and you say, wow, there s no magic here.
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SPEAKER_00
I mean, clearly this thing is as deterministic as it gets.
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It s a piece of hardware.
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The only way we re going to be able to control it is by rewiring it, which is the way molecular biology works, right?
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We can add nodes, remove nodes, whatever.
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SPEAKER_00
Well, so we ve done simulations and shown that biological, and now we re doing this in the lab, the biological networks like that have associative memory.
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So they can actually learn, they can learn from experience, they have habituation, they have sensitization, they have associative memory, which you wouldn t have known if you assumed that they have to be on the left side of that spectrum.
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So when you re going to communicate with something, and we ve even
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Charles Abramson, I ve written a paper on behaviorist approaches to synthetic organism, meaning that if you re given something, you have no idea what it is or what it can do.
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How do you figure out what its psychology is, what its level is, what does it?
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And so we literally lay out a set of protocols, starting with the simplest things and then moving up to more complex things where you can make no assumptions about what this thing can do, right?
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SPEAKER_00
Just from you, you have to start and you ll find out.
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SPEAKER_00
So here s a simple, I mean, here s one way to communicate with something.
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If you can train it,
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That s a way of communicating.
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So if you can provide, if you can figure out what the currency of reward of positive and negative reinforcement is, right, and you can get it to do something it wasn t doing before, based on experiences you ve given it, you have taught it one thing, you have communicated one thing that that such and such an action is good.
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SPEAKER_00
So some other action is not good.
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That s, that s like a basic atom of a primitive atom of communication.
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SPEAKER_01
What about, in some sense, if it gets you to do something you haven t done before, is it answering back?
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SPEAKER_00
Most certainly, and I ve seen cartoons.
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Maybe Gary Larson or somebody had a cartoon of these rats in the maze, and the one rat assists to the other.
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SPEAKER_00
Hey, look at this.
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SPEAKER_00
Every time I walk over here, he starts scribbling on the clipboard that he has.
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SPEAKER_00
It s awesome.
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SPEAKER_01
If we step outside ourselves,
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and really measure how much, like if I actually measure how much I ve changed because of my interaction with certain cellular automata, I mean, you really have to take that into consideration about like, well, these things are changing you too.
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SPEAKER_01
I know you know how it works and so on, but you re being changed by the thing.
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SPEAKER_00
Absolutely.
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SPEAKER_00
I think I read, I don t know any details, but I think I read something about how wheat and other things have domesticated humans in terms of, right, but by their properties change the way that the human behavior and societal structures.
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In that sense, cats are running the world.
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because they took over the, so first of all, so first they, while not giving a shit about humans, clearly, with every ounce of their being, they ve somehow got just millions and millions of humans to take them home and feed them.
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And then, not only the physical space that they take over, they took over the digital space.
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They dominate the internet in terms of cuteness, in terms of memability.
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And so they re like, they got themselves literally inside the memes that become viral and spread on the internet.
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SPEAKER_01
And they re the ones that are probably controlling humans, that s my theory.
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SPEAKER_01
Another, that s a follow-up paper after the frog kissing.
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SPEAKER_01
Okay, I mean you mentioned,
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SPEAKER_01
sentience and consciousness, you have a paper titled Generalizing Frameworks for Sentience Beyond Natural Species.
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SPEAKER_01
So beyond normal cognition, if we look at sentience and consciousness, and I wonder if you draw an interesting distinction between those two, elsewhere.
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SPEAKER_01
outside of humans and maybe outside of Earth, you think aliens have sentience?
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SPEAKER_01
And if they do, how do we think about it?
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SPEAKER_01
So when you have this framework, what is this paper, what is the way you propose to think about sentience?
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SPEAKER_00
Yeah, that particular paper was a very short commentary on another paper that was written about crabs.
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SPEAKER_00
It was a really good paper on crabs and various, like a rubric of different types of behaviors that could be applied to different creatures and they re trying to apply it to crabs and so on.
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SPEAKER_00
Consciousness, we can talk about a few, but it s a whole separate kettle of fish.
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SPEAKER_00
I almost never talk about- Kettle of crabs.
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SPEAKER_00
In this case, yes.
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SPEAKER_00
I almost never talk about consciousness per se.
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I ve said very little about it, but we can talk about it if you want.
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Mostly what I talk about is cognition because I think that that s much easier to deal with in a kind of rigorous experimental way.
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I think that
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all of these terms have, you know, sentience and so on, have different definitions.
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And fundamentally, I think that people can, as long as they specify what they mean ahead of time, I think people can define them in various ways.
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The only thing that I really kind of insist on is that
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the right way to think about all this stuff is from an engineering perspective.
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What does it help me to control, predict, and does it help me do my next experiment?
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SPEAKER_00
So that s not a universal perspective.
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So some people have
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philosophical kind of underpinnings, and those are primary, and if anything runs against that, then it must automatically be wrong.
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SPEAKER_00
So some people will say, I don t care what else, if your theory says to me that thermostats have little tiny goals,
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SPEAKER_00
I m not, I m not, I m not.
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SPEAKER_00
So that s it.
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SPEAKER_00
I just did like, that s my philosophical, you know, preconception.
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SPEAKER_00
It s like thermostats do not have goals and that s it.
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SPEAKER_00
So, um, so that s one way of doing it.
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SPEAKER_00
And some people do it that way.
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SPEAKER_00
I do not do it that way.
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SPEAKER_00
And I think that we can t, we can t, I don t think we can know much of anything from an hour from a philosophical armchair.
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SPEAKER_00
I think that.
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All of these theories and ways of doing things stand or fall based on just basically one set of criteria.
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SPEAKER_00
Does it help you run a rich research program?
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That s it.
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SPEAKER_01
Which I agree with you totally, but so forget philosophy, what about the poetry of ambiguity?
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SPEAKER_01
What about at the limits of the things you can engineer using terms that can be defined in multiple ways and living within that?
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SPEAKER_01
in order to play with words until something lands that you can engineer.
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SPEAKER_01
I mean, that s to me where consciousness sits currently.
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SPEAKER_01
Nobody really understands the heart problem of consciousness, the subject, what it feels like.
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Because it really feels like, it feels like something to be this biological system.
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This conglomerate of a bunch of cells in this hierarchy of competencies feels like something.
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And yeah, I feel like one thing, and is that just,
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Is that just a side effect of a complex system?
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Or is there something more that humans have?
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SPEAKER_01
Or is there something more that any biological system has?
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SPEAKER_01
Some kind of magic, some kind of, not just a sense of agency, but a real sense with a capital letter S of agency.
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SPEAKER_00
Ah, boy, yeah, that s a deep question.
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SPEAKER_01
Is there room for poetry in engineering or no?
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SPEAKER_00
No, there definitely is.
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SPEAKER_00
And a lot of the poetry comes in when we realize that none of the categories we deal with are sharp as we think they are, right?
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SPEAKER_00
And so in the different areas of all these spectra are where a lot of the poetry sits.
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SPEAKER_00
I have many new theories about things, but I, in fact, do not have a good theory about consciousness that I plan to trot out.
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SPEAKER_01
And you almost don t see it as useful for your current work to think about consciousness.
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SPEAKER_00
I think it will come.
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SPEAKER_00
I have some thoughts about it, but I don t feel like they re gonna move the needle yet on that.
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SPEAKER_01
And you wanna ground it in engineering always.
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SPEAKER_01
So, well.
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SPEAKER_00
I mean, I don t, so if we really tackle consciousness per se, in terms of the heart problem, I don t, that isn t necessarily going to be groundable in engineering, right?
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SPEAKER_00
That aspect of cognition is, but actual consciousness per se, you know, first person perspective, I m not sure that that s groundable in engineering.
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SPEAKER_00
And I think specifically, what s different about it is there s a couple of things.
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SPEAKER_00
So let s, you know, here we go.
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I ll say a couple of things about,
6
SPEAKER_00
about consciousness.
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One thing is that what makes it different is that for every other tight aspect of science,
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when we think about having a correct or a good theory of it, we have some idea of what format that theory makes predictions in.
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SPEAKER_00
So whether those be numbers or whatever, we have some idea.
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SPEAKER_00
We may not know the answer, we may not have the theory, but we know that when we get the theory, here s what it s going to output, and then we ll know if it s right or wrong.
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SPEAKER_00
For actual consciousness, not behavior, not neural correlates, but actual first-person consciousness,
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SPEAKER_00
If we had a correct theory of consciousness, or even a good one, what format would it make predictions in, right?
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SPEAKER_00
Because all the things that we know about basically boil down to observable behaviors.
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SPEAKER_00
So the only thing I can think of when I think about that is, it ll be poetry, or it ll be something to, if I ask you, okay, you ve got a great theory of consciousness, and here s this creature, maybe it s a natural one, maybe it s an engineered one, whatever,
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SPEAKER_00
And I want you to tell me what your theory says about this being, what it s like to be this being.
7
SPEAKER_01
the only thing I can imagine you giving me is some piece of art, a poem or something that once I ve taken it in, I share, I now have a similar state as whatever.
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SPEAKER_01
That s about as good as I can come up with.
7
SPEAKER_00
Well, it s possible that once you have a good understanding of consciousness, it would be mapped to some things that are more measurable.
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SPEAKER_00
So for example, it s possible that
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a conscious being is one that s able to suffer.
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So you start to look at pain and suffering.
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You can start to connect it closer to things that you can measure that in terms of how they reflect themselves in behavior and problem solving and creation and attainment of goals, for example.
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SPEAKER_00
which I think suffering is one of the, you know, life is suffering, it s one of the big aspects of the human condition.
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SPEAKER_00
And so if consciousness is somehow a, maybe at least a catalyst for suffering,
7
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you could start to get echoes of it.
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You start to see the actual effects of consciousness on behavior, that it s not just about subjective experience, it s really deeply integrated in the problem-solving, decision-making of a system.
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Something like this, but also it s possible
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that we realize, this is not a philosophical statement.
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SPEAKER_00
Philosophers can write their books, I welcome it.
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SPEAKER_00
I take the Turing test really seriously.
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I don t know why people really don t like it when a robot convinces you that it s intelligent.
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SPEAKER_00
I think that s a really incredible accomplishment.
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And there s some deep sense in which that is intelligence.
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If it looks like it s intelligent, it is intelligent.
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And I think there s some deep aspect of a system that appears to be conscious.
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In some deep sense, it is conscious.
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At least for me, we have to consider that possibility.
7
SPEAKER_00
And a system that appears to be conscious is an engineering challenge.
7
SPEAKER_01
Yeah, I don t disagree with any of that.
7
SPEAKER_01
I mean, especially intelligence, I think is a publicly observable thing.
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SPEAKER_01
I, and I mean, you know, science fiction has dealt with this for a century or more, much more, maybe this idea that when you are confronted with something that
7
SPEAKER_01
just doesn t meet any of your typical assumptions, so you can t look in the skull and say, oh, well, there s that frontal cortex, so then I guess we re good, right?
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SPEAKER_01
If it s, you know, so this thing lands on your front lawn and this, you know, the little door opens and something trundles out and it s sort of like, you know, kind of shiny and aluminum looking and it hands you this, you know, it hands you this poem that it wrote while it was on, you know,
7
SPEAKER_01
know, flying over and how happy it is to meet you, like, what are what s going to be your criteria, right?
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SPEAKER_01
For whether whether you get to take it apart and see what makes a tick or whether you have to, you know, be nice to it.
7
SPEAKER_01
And, and whatever, right?
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SPEAKER_01
Like all the all the criteria that we have now.
7
SPEAKER_01
And, you know, that people are using.
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SPEAKER_01
And as you said, a lot of people are down on the Turing test and things like this, but but what else have we got?
7
SPEAKER_01
you know, because measuring the cortex size isn t gonna cut it, right, in the broader scheme of things.
7
SPEAKER_01
So, I think it s a wide open problem that, right, that we, you know, our solution to the problem of other minds, it s very simplistic, right?
7
SPEAKER_01
We give each other credit for having minds just because we sort of, on an anatomical level, we re pretty similar, and so that s good enough.
7
SPEAKER_01
But how far is that gonna go?
7
SPEAKER_01
So, I think that s really primitive.
7
SPEAKER_01
So, yeah, I think it s a major unsolved problem.
7
SPEAKER_00
It s a really challenging direction of thought to the human race that you talked about, like embodied minds.
7
SPEAKER_00
If you start to think that other things other than humans have minds, that s really challenging.
7
SPEAKER_00
Because all men are created equal starts being like, all right, well, we should probably treat
7
SPEAKER_00
not just cows with respect, but like plants, and not just plants, but some kind of organized conglomerates of cells in a Petri dish.
7
SPEAKER_00
In fact, some of the work we re doing, like you re doing, and the whole community of science is doing with biology, people might be like, we were really mean to viruses.
7
SPEAKER_01
Yeah, I mean, yeah, I the thing is, you re right.
7
SPEAKER_01
And I get I get I certainly get phone calls about people complaining about frog skin and so on.
7
SPEAKER_01
But
7
SPEAKER_01
I think we have to separate the sort of deep philosophical aspects versus what actually happens.
7
SPEAKER_01
So what actually happens on Earth is that people with exactly the same anatomical structure kill each other, you know, on a daily basis, right?
7
SPEAKER_01
So I think it s clear that simply knowing that something else is equally or maybe more cognitive or conscious than you are is not a guarantee of kind behavior, that much we know of.
7
SPEAKER_01
And so then we look at a commercial farming of mammals and various other things.
7
SPEAKER_01
And so I think on a practical basis, long before we get to worrying about things like frog skin, we have to ask ourselves, what can we do about the way that we ve been behaving towards creatures, which we know for a fact, because of our similarities, are basically just like us.
7
SPEAKER_01
You know, that s kind of a whole other social thing.
7
SPEAKER_01
But but but fundamentally, you know, of course, you re absolutely right in that we we are also think about this.
7
SPEAKER_01
We are on this planet in some way incredibly lucky.
7
SPEAKER_01
It s just dumb luck that we really only have one dominant species.
7
SPEAKER_01
It didn t have to work out that way.
7
SPEAKER_01
So you could easily imagine that there could be a planet somewhere with more than one equally or maybe near equally intelligent species.
7
SPEAKER_01
And then
7
SPEAKER_01
But they may not look anything like each other, right?
7
SPEAKER_01
So there may be multiple ecosystems where there are things of similar to human-like intelligence.
7
SPEAKER_01
And then you d have all kinds of issues about, you know, how do you relate to them when they re physically not like you at all, but yet, you know, in terms of behavior and culture and whatever, it s pretty obvious that they ve got as much on the ball as you have.
7
SPEAKER_01
Or maybe imagine that there was another group of beings that was like on average, you know, 40 IQ points lower.
7
SPEAKER_01
We re pretty lucky in many ways.
7
SPEAKER_01
We don t really have, even though we still act badly in many ways, but the fact is all humans are more or less in that same range, but it didn t have to work out that way.
7
SPEAKER_00
Well, but I think that s part of the way life works on Earth, or maybe human civilization works, is it seems like we want ourselves to be quite similar, and then within that, where everybody s about the same, relatively IQ, intelligence, problem-solving capabilities, even physical characteristics, but then we ll find some aspect of that that s different.
7
SPEAKER_00
And that seems to be like,
7
SPEAKER_00
I mean, it s really dark to say, but there seems to be not even a bug, but like a feature
7
SPEAKER_00
of the early development of human civilization.
7
SPEAKER_00
You pick the other, your tribe versus the other tribe, it s a kind of evolution in the space of memes, the space of ideas, I think, and you war with each other.
7
SPEAKER_00
So we re very good at finding the other, even when the characteristics are really the same.
7
SPEAKER_00
I don t know what,
7
SPEAKER_00
I mean, I m sure so many of these things echo in the biological world in some way.
7
SPEAKER_01
There s a fun experiment that I did.
7
SPEAKER_01
My son actually came up with this.
7
SPEAKER_01
We did a biology unit together.
7
SPEAKER_01
He s so homeschooled, and so we did this a couple years ago.
7
SPEAKER_01
We did this thing where, imagine, so you got this slime mold, right?
7
SPEAKER_01
Physarum polycephalum, and it grows on a petri dish of agar, and it sort of spreads out, and it s a single cell protist, but it s like this giant thing.
7
SPEAKER_01
and so you put down a piece of oat and it wants to go get the oat and it sort of grows towards the oat so what you do is you take a razor blade and you just you just separate the piece of the whole culture that s growing towards the the oh you just kind of separate it and so now think about think about the interesting decision making calculus for that little piece i can i can go get the oat and therefore i won t have to share those nutrients with this giant mass over there so the so the nutrients per unit volume is going to be amazing so i should go eat the oat
7
SPEAKER_01
But if I first rejoin, because Visarum, once you cut it, has the ability to join back up.
7
SPEAKER_01
If I first rejoin, then that whole calculus becomes impossible, because there is no more me anymore.
7
SPEAKER_01
There s just we, and then we will go eat this thing, right?
7
SPEAKER_01
So this interesting, you can imagine a kind of game theory where the number of agents isn t fixed, and that it s not just cooperate or defect, but it s actually merge and whatever, right?
7
SPEAKER_00
So that kind of, that computation, how does it do that decision-making?
7
SPEAKER_01
Yeah, so it s really interesting.
7
SPEAKER_01
And so empirically, what we found is that it tends to merge first.
7
SPEAKER_01
It tends to merge first, and then the whole thing goes.
7
SPEAKER_01
But it s really interesting that that calculus, do we even have, I mean, I m not an expert in the economic game theory and all that, but maybe there s some sort of hyperbolic discounting or something.
7
SPEAKER_01
But maybe this idea that the actions you take not only change your payoff,
7
SPEAKER_01
but they change who or what you are, and that you may not, you could take an action after which you don t exist anymore, or you are radically changed, or you are merged with somebody else.
7
SPEAKER_01
Like that s, you know, as far as I know, that s a whole, you know, we re still missing a formalism for even knowing how to model any of that.
7
SPEAKER_00
Do you see evolution, by the way, as a process that applies here on Earth, or is it some, where did evolution come from?
7
SPEAKER_00
So this thing that from the very origin of life that took us to today, what the heck is that?
7
SPEAKER_01
I think evolution is inevitable in the sense that if you combine, and basically I think one of the most useful things that was done in early computing, I guess in the 60s, it started with evolutionary computation and just showing how
7
SPEAKER_01
Simple it is that if you have imperfect heredity and competition together, those two things, well, three things, right?
7
SPEAKER_01
So heredity, imperfect heredity, and competition or selection, those three things, and that s it.
7
SPEAKER_01
Now you re off to the races, right?
7
SPEAKER_01
And so that can be, it s not just on earth because it can be done in the computer, it can be done in chemical systems, it can be done in, you know, Lee Smolin says it works on cosmic scales.
7
SPEAKER_01
So I think that,
7
SPEAKER_01
that kind of thing is incredibly pervasive and general, it s a general feature of life.
7
SPEAKER_01
It s interesting to think about, you know, the standard thought about this is that it s blind, right?
7
SPEAKER_01
Meaning that the intelligence of the process is zero, it s stumbling around.
7
SPEAKER_01
And I think that
7
SPEAKER_01
back in the day when the options were it s dumb like machines or it s smart like humans, then of course the scientists went in this direction because nobody wanted creationism.
7
SPEAKER_01
And so they said, okay, it s gotta be like completely blind.
7
SPEAKER_01
I m not actually sure, right?
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Because I think that everything is a continuum.
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And I think that it doesn t have to be smart with foresight like us, but it doesn t have to be completely blind either.
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I think there may be aspects of it.
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And in particular, this kind of multi-scale competency might give it a little bit of,
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look ahead maybe or a little bit of problem solving sort of baked in, but that s gonna be completely different in different systems.
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But I do think it s general.
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I don t think it s just on Earth.
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I think it s a very fundamental thing.
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It does seem to have a kind of direction that it s taking us that s somehow perhaps is defined by the environment itself.
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It feels like we re headed towards something.
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Like we re playing out a script that was just like a single cell defines the entire organism.
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It feels like from the origin of Earth itself, it s playing out a kind of script.
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You can t really go any other way.
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I mean, so this is very controversial.
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And I don t know the answer.
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But people have people have argued that this is called, you know, sort of rewinding the tape of life, right.
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And some people have argued, I think, I think Conway Morris, maybe has argued that it is that there s a deep attractor, for example, to human to the human
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Kind of structure and that and that if you were to rewind it again You d basically get more or less the same thing and then other people have argued that no, it s it s incredibly sensitive to frozen accidents and that once certain Stochastic decisions are made downstream.
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Everything is going to be different.
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I don t know.
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I don t know, you know, we re very bad at
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predicting attractors in the space of complex systems, generally speaking, right?
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We don t know.
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So maybe evolution on Earth has these deep attractors that no matter what has happened, pretty much would likely to end up there, or maybe not.
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I don t know.
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What s a really difficult idea to imagine that if you ran Earth a million times, 500,000 times, you would get Hitler?
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Like, we don t like to think like that.
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We think like, because, at least maybe in America, you like to think that individual decisions can change the world, and if individual decisions can change the world, then surely,
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Any perturbation results in a totally different trajectory.
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But maybe there s a, in this competency hierarchy, it s a self-correcting system that just ultimately, there s a bunch of chaos that ultimately is leading towards something like a superintelligent artificial intelligence system.
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The answer s 42.
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I mean, there might be a kind of imperative for life that it s headed to.
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and we re too focused on our day-to-day life of getting coffee and snacks and having sex and getting a promotion at work, not to see the big imperative of life on Earth, that it s headed towards something.
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Yeah, maybe, maybe.
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It s difficult.
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I think one of the things that s important about chimeric bioengineering technologies, all of those things, are that we have to start developing a better science of
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predicting the cognitive goals of composite systems.
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So we re just not very good at it, right?
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We don t know if I create a composite system, and this could be Internet of Things or swarm robotics or a cellular swarm or whatever,
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what is the emergent intelligence of this thing?
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First of all, what level is it going to be at?
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And if it has goal directed capacity, what are the goals going to be like?
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We are just not very good at predicting that yet.
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And I think that it s it s a it s a it s a existential level need for us to be able to because we re building these things all the time.
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Right.
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We re building we re building
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both physical structures like swarm robotics, and we re building social financial structures and so on, with very little ability to predict what sort of autonomous goals that system is going to have, of which we are now cogs.
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And so, right, so learning to predict and control those things is going to be critical.
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So if you re right, and there is some kind of attractor to evolution, it would be nice to know what that is, and then to make a rational decision of whether we re going to go along or we re going to pop out of it or try to pop out of it.
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Because there s no guarantee.
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I mean, that s the other, you know, kind of important thing.
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A lot of people, I get a lot of complaints from people emailing and say, you know, what you re doing, it isn t natural, you know.
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And I ll say, look, natural, that d be nice if somebody was making sure that natural was matched up to our values.
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But no one s doing that.
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You know, evolution optimizes for biomass.
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That s it.
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Nobody s optimizing, it s not optimizing for your happiness.
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It s, I don t think necessarily it s optimizing for, for, for intelligence or fairness or any of that stuff.
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I m gonna find that person that emailed you, beat them up, take their place, steal everything they own, and say, now this is natural.
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This is natural, yeah, exactly.
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Because it comes from an old world view where you could assume that whatever is natural, that that s probably for the best.
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And I think we re long out of that Garden of Eden kind of view.
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So I think we can do better.
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And we have to, right?
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Natural just isn t great for a lot of life forms.
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What are some cool synthetic organisms that you think about, you dream about?
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When you think about embodied mind, what do you imagine?
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What do you hope to build?
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Yeah, on a practical level, what I really hope to do is
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to gain enough of an understanding of the embodied intelligence of the organs and tissues such that we can achieve a radically different regenerative medicine so that we can say Basically, and I think about it as you know in terms of like, okay, can you what s the what s the?
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What s the goal kind of and and endgame for this whole thing to me?
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The endgame is something that you would call an anatomical compiler So the idea is you would sit down in front of the computer and you would draw
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the body or the organ that you wanted.
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Not molecular details, but like, this is what I want.
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I want a six-legged frog with a propeller on top, or I want a heart that looks like this, or I want a leg that looks like this.
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And what it would do, if we knew what we were doing, is
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put out, convert that anatomical description into a set of stimuli that would have to be given to cells to convince them to build exactly that thing, right?
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I probably won t live to see it, but I think it s achievable.
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And I think with that, if we can have that, then that is basically the solution to all of medicine except for infectious disease.
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So birth defects, right?
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Traumatic injury, cancer, aging, degenerative disease.
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If we knew how to tell cells what to build, all of those things go away.
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So, those things go away and the positive feedback spiral of economic costs where all of the advances are increasingly more heroic and expensive interventions of a sinking ship when you re like 90 and so on, right?
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All of that goes away because basically instead of trying to fix you up as you degrade, you
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you progressively regenerate, you know, you apply the regenerative medicine early before things degrade.
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So I think that that ll have massive economic impacts over what we re trying to do now, which is not at all, you know, sustainable.
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And that s what I hope.
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So to me, yes, the xenobots will be doing useful things, cleaning up the environment, cleaning out, you know, your joints and all that kind of stuff.
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But more important than that, I think we can use
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these synthetic systems to try to understand, to develop a science of detecting and manipulating the goals of collective intelligences of cells, specifically for regenerative medicine.
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And then sort of beyond that, if we, you know, sort of think further beyond that, what I hope is that kind of like what you said, all of this drives a reconsideration of how we formulate ethical norms.
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Because this old school, so in the olden days, what you could do is
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As you were confronted with something, you could tap on it, right?
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And if you heard a metallic clanging sound, you d said, ah, fine, right?
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So you could conclude it was made in a factory.
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I can take it apart.
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I can do whatever, right?
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If you did that and you got sort of a squishy kind of warm sensation, you d say, ah, I need to be more or less nice to it and whatever.
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That s not going to be feasible.
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It was never really feasible, but it was good enough because we didn t know any better.
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That needs to go.
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And I think that
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By breaking down those artificial barriers, someday we can try to build a system of ethical norms that does not rely on these completely contingent facts of our earthly history, but on something much, much deeper that, you know, really takes agency and the capacity to suffer and all that takes that seriously.
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The capacity to suffer and the deep questions I would ask of a system is can I eat it and can I have sex with it?
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Which is the two fundamental tests of, again, the human condition.
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So I can basically do what Dali does in the physical space.
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So print out, like a 3D print, Pepe the Frog with a propeller head, propeller hat, is the dream.
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Well, I want to, yes and no.
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I mean, I want to get away from the 3D printing thing because that will be available for some things much earlier.
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I mean, we can already do bladders and ears and things like that because it s micro level control, right?
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When you 3D print, you are in charge of where every cell goes.
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And for some things that, you know, for, for like this thing, they had that, I think 20 years ago or maybe earlier than that, you could do that.
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So yeah, I would like to emphasize the Dali part where you provide a few words and it generates a painting.
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So here you say, I want a frog.
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with these features, and then it would go direct a complex biological system to construct something like that.
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Yeah, the main magic would be, I mean, I think from looking at Dahlia and so on, it looks like the first part is kind of solved now, where you go from the words to the image, like that seems more or less solved.
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The next step is really hard.
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This is what keeps things like CRISPR and genomic editing and so on, this is what limits all the,
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impacts for regenerative medicine, because going back to, okay, this is the knee joint that I want, or this is the eye that I want.
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Now, what genes do I edit to make that happen, right?
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Going back in that direction is really hard.
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So instead of that, it s going to be, okay, I understand how to motivate cells to build particular structures.
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Can I rewrite the memory of what they think they re supposed to be building, such that then I can, you know, take my hands off the wheel and let them do their thing?
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So some of that is experiment, but some of that maybe AI can help too.
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Just like with protein folding, this is exactly the problem that protein folding in the most simple medium tried and has solved with alpha fold, which is how does the sequence of letters result in this three-dimensional shape?
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And you have to, I guess it didn t solve it because you have to
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If you say I want this shape, how do I then have a sequence of letters?
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Yeah, the reverse engineering step is really tricky.
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It is.
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I think where, and we re doing some of this now, is to use AI to try and build actionable models of the intelligence of the cellular collectives.
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So try to help us, help us gain models that, and we ve had some success in this.
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So we did something like this for,
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for repairing birth defects of the brain in frog.
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We ve done some of this for normalizing melanoma, where you can really start to use AI to make models of how would I impact this thing if I wanted to, given all the complexities, right?
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And given all the controls that it knows how to do.
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SPEAKER_00
So when you say regenerative medicine, so we talked about
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creating biological organisms, but if you regrow a hand, that information is already there, right?
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The biological system has that information.
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So how does regenerative medicine work today?
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How do you hope it works?
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What s the hope there?
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Yeah, how do you make it happen?
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Well, today there s a set of popular approaches.
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So one is 3D printing.
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So the idea is I m going to make a scaffold of the thing that I want, I m going to seed it with cells, and then there it is, right?
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So kind of direct, and then that works for certain things.
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You can make a bladder that way or an ear, something like that.
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The other idea is some sort of stem cell transplant.
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The idea is if we
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If we put in stem cells with appropriate factors, we can get them to generate certain kinds of neurons for certain diseases and so on.
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All of those things are good for relatively simple structures, but when you want an eye or a hand or something else, I think, and this may be an unpopular opinion, I think the only hope we have in any reasonable kind of time frame
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is to understand how the thing was motivated to get made in the first place.
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So what is it that made those cells in the beginning create a particular arm with a particular set of sizes and shapes and number of fingers and all that?
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And why is it that a salamander can keep losing theirs and keep regrowing theirs?
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And a planarian can do the same, even more so.
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To me, kind of ultimate regenerative medicine was when you can tell the cells to build whatever it is you need them to build.
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right?
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And so that we can all be like planaria, basically.
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Do you have to start at the very beginning or can you do a shortcut?
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Because if you re growing a hand, you already got the whole organism.
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Yeah.
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So here s what we ve done, right?
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So we ve more or less solved that in frogs.
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So frogs, unlike salamanders, do not regenerate their legs as adults.
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And so we ve shown that with a very kind of simple intervention.
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So what we do is there s two things.
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You need to have a signal that tells the cells what to do, and then you need some way of delivering it.
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And so this is work together with David Kaplan, and I should do a disclosure here.
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We have a company called Morphoceuticals, I think it s a spin-off.
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where we re trying to address limb regeneration.
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So we ve solved it in the frog, and we re now in trials in mice.
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So now we re in mammals now.
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I can t say anything about how it s going, but the frog thing is solved.
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SPEAKER_00
So what you do is... You have a little frog Lou Skywalker with every growing hand.
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Yeah, basically.
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Basically, yeah.
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Yeah, so what you do is, we did with legs instead of forearms, and what you do is after amputation, normally they don t regenerate, you put on a wearable bioreactor, so it s this thing that goes on, and Dave Kaplan s lab makes these things, and inside it s a very controlled environment.
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It is a silk gel that carries some drugs, for example, ion channel drugs, and what you re doing is you re saying to these cells,
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you should regrow what normally goes here.
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So that whole thing is on for 24 hours.
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Then you take it off.
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You don t touch the link again.
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This is really important because what we re not looking for is a set of micromanagement, you know, printing or controlling the cells.
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We want to trigger.
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We want to, we want to interact with it early on and then not touch it again because, because we don t know how to make a frog leg, but the frog knows how to make a frog leg.
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So 24 hours.
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18 months of leg growth after that without us touching it again.
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And after 18 months, you get a pretty good leg.
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That kind of shows this proof of concept that early on when the cells right after injury, when they re first making a decision about what they re going to do, you can you can impact them.
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And once they ve decided to make a leg, they don t need you after that.
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They can do their own thing.
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SPEAKER_01
So that s an approach that we re now taking.
8
SPEAKER_00
What about cancer suppression?
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SPEAKER_00
That s something you mentioned earlier.
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SPEAKER_00
How can all of these ideas help with cancer suppression?
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SPEAKER_01
So let s go back to the beginning and ask what cancer is.
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So I think, you know, asking why there s cancer is the wrong question.
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I think the right question is why is there ever anything but cancer?
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So in the normal state, you have a bunch of cells that are all cooperating towards a large scale goal.
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SPEAKER_01
if that process of cooperation breaks down and you ve got a cell that is isolated from that electrical network that lets you remember what the big goal is you revert back to your unicellular lifestyle as far as now think about that border between self and world right normally when all these cells are connected by gab junctions into an electrical network they are all one self right that meaning that um
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SPEAKER_01
their goals they have these large tissue level goals and so on as soon as the cell is disconnected from that the self is tiny right and so at that point and so so people a lot of people model cancer cell cells as being more selfish and all that they re not more selfish they re equally selfish it s just that their self is smaller normally the self is huge now they got tiny little selves now what are the goals of tiny little selves well proliferate right and migrate to wherever life is good and that s metastasis that s proliferation and metastasis
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SPEAKER_01
So one thing we found, and people have noticed years ago, that when cells convert to cancer, the first thing they see is they close the gap junctions.
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SPEAKER_01
And it s a lot like, I think, it s a lot like that experiment with the slime mold, where until you close that gap junction, you can t even entertain the idea of leaving the collective, because there is no you at that point, right?
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You re mind melded with this whole other network.
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But as soon as the gap junction is closed, now the boundary between you and now the rest of the body is just outside environment to you.
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You re just a unicellular organism in the rest of the body s environment.
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So we studied this process and we worked out a way to artificially control the bioelectric state of these cells to physically force them to remain in that network.
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And so then what that means is that nasty mutations like KRAS and things like that, these really tough oncogenic mutations that cause tumors, if you do them, but then artificially
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control of the bioelectrics, you greatly reduce tumorigenesis or normalize cells that had already begun to convert you.
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Basically, they go back to being normal cells.
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And so this is another, much like with the planaria, this is another way in which the bioelectric state kind of dominates what the genetic state is.
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So if you sequence the nucleic acid, you ll see the KRAS mutation.
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You ll say, well, that s going to be a tumor.
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but there isn t a tumor because bioelectrically you ve kept the cells connected and they re just working on making nice skin and kidneys and whatever else.
8
SPEAKER_01
So we ve started moving that to human glioblastoma cells and we re hoping for a patient in the future, interaction with patients.
8
SPEAKER_00
So is this one of the possible ways in which we may, quote, cure cancer?
8
SPEAKER_01
I think so.
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SPEAKER_01
Yeah, I think so.
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SPEAKER_01
I think I think the actual cure, I mean, there are other technology, you know, immune therapy, I think it s a great technology.
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SPEAKER_01
Chemotherapy, I don t think is a good is a good technology.
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SPEAKER_01
I think we got to get get off of that.
8
SPEAKER_00
So chemotherapy just kills cells.
8
SPEAKER_01
Yeah, well chemotherapy hopes to kill more of the tumor cells than of your cells.
8
SPEAKER_01
That s it, it s a fine balance.
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SPEAKER_01
The problem is the cells are very similar, because they are your cells.
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SPEAKER_01
And so if you don t have a very tight way of distinguishing between them, then the toll that chemo takes on the rest of the body is just unbelievable.
8
SPEAKER_00
And immunotherapy tries to get the immune system to do some of the work.
8
SPEAKER_01
Exactly.
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SPEAKER_01
Yeah, I think that s potentially a very good approach.
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SPEAKER_01
If the immune system can be taught to recognize enough of the cancer cells, that s a pretty good approach.
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SPEAKER_01
But I think our approach is in a way more fundamental, because if you can keep the cells harnessed towards organ level goals, as opposed to individual cell goals, then nobody will be making a tumor or metastasizing and so on.
8
SPEAKER_00
So we ve been living through a pandemic,
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What do you think about viruses in this full, beautiful, biological context we ve been talking about?
8
SPEAKER_00
Are they beautiful to you?
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SPEAKER_00
Are they terrifying?
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SPEAKER_00
Also, maybe, let s say, are they, since we ve been discriminating this whole conversation, are they living?
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SPEAKER_00
Are they embodied minds?
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SPEAKER_00
Embodied minds that are assholes?
8
SPEAKER_01
As far as I know, and I haven t been able to find this paper again, but somewhere I saw in the last couple of months, there was some paper showing an example of a virus that actually had physiology.
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SPEAKER_01
So there was something was going on.
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SPEAKER_01
I think proton flux or something on the virus itself.
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SPEAKER_01
But barring that, generally speaking, viruses are very passive.
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SPEAKER_01
They don t do anything by themselves.
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SPEAKER_01
And so I don t see any particular reason to attribute much of a mind to them.
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SPEAKER_01
I think, you know,
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SPEAKER_01
they represent a way to hijack other minds, for sure, like cells and other things.
8
SPEAKER_00
But that s an interesting interplay, though.
8
SPEAKER_00
If they re hijacking other minds, you know, the way we were talking about living organisms, that they can interact with each other and alter each other s trajectory by having interacted.
8
SPEAKER_00
I mean, that s a deep,
8
SPEAKER_00
meaningful connection between a virus and a cell.
8
SPEAKER_00
And I think both are transformed by the experience, and so in that sense, both are living.
8
SPEAKER_01
I don t, this question of what s living and what s not living, I really, I m not sure, and I know there s people that work on this and I don t want to piss anybody off, but I have not found that particularly useful as to try and make that a binary kind of distinction.
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SPEAKER_01
I think level of cognition is very interesting as a continuum, but living and non-living,
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SPEAKER_01
I really know what to do with that.
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SPEAKER_01
I don t know what you do next after making that distinction.
8
SPEAKER_00
That s why I make the very binary distinction.
8
SPEAKER_00
Can I have sex with it or not?
8
SPEAKER_00
Can I eat it or not?
8
SPEAKER_00
Because those are actionable, right?
8
SPEAKER_00
Yeah.
8
SPEAKER_01
Well, I think that s a critical point that you brought up because how you relate to something
8
SPEAKER_01
is really what this is all about, right?
8
SPEAKER_01
As an engineer, how do I control it?
8
SPEAKER_01
But maybe I shouldn t be controlling it.
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SPEAKER_01
Maybe I should be, you know, can I have a relationship with it?
8
SPEAKER_01
Should I be listening to its advice?
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Like all the way from, you know, I need to take it apart, all the way to, I better do what it says, because it seems to be pretty smart, and everything in between, right?
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That s really what we re asking about.
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Yeah, we need to understand our relationship to it.
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We re searching for that relationship, even in the most trivial senses.
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You came up with a lot of interesting terms.
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We ve mentioned some of them.
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A gentrile material, that s a really interesting one.
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That s a really interesting one for the future of computation and artificial intelligence.
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artificial intelligence and computer science and all of that.
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There s also, let me go through some of them, if they spark some interesting thought for you.
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There s teleophobia, the unwanted fear of erring on the side of too much agency when considering a new system.
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That s the opposite.
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I mean, being afraid of maybe anthropomorphizing the thing.
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SPEAKER_00
This will get some people ticked off, I think, but I don t think, I think the whole notion of anthropomorphizing is a holdover from a pre-scientific age where humans were magic and everything else wasn t magic, and you were anthropomorphizing when you dared suggest that something else has some features of humans.
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And I think we need to be way beyond that.
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This issue of anthropomorphizing, I think it s a cheap charge.
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I don t think it holds any water at all, other than when somebody makes a cognitive claim.
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I think all cognitive claims are engineering claims, really.
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So when somebody says, this thing knows, or this thing hopes, or this thing wants, or this thing predicts,
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All you can say is, fabulous, give me the engineering protocol that you ve derived using that hypothesis, and we will see if this thing helps us or not, and then we can make a rational decision.
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I also like anatomical compiler, a future system representing the long-term endgame of the science of morphogenesis that reminds us how far away from true understanding we are.
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Someday you will be able to sit in front of an anatomical computer, specify the shape of the animal or plant that you want, and it will convert that shape specification to a set of stimuli that will have to be given to cells to build exactly that shape.
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no matter how weird it ends up being, you have total control.
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Just imagine the possibility for memes.
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in the physical space.
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One of the glorious accomplishments of human civilizations is memes in digital space.
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Now this could create memes in physical space.
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I am both excited and terrified by that possibility.
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Cognitive light cone, I think we also talked about.
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The outer boundary in space and time of the largest goal a given system can work towards.
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Is this kind of like shaping the set of options?
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it s a little different than than options.
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It s, it s really focused on so so so back in this, this I first came up with this back in 2018.
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I want to say we had a there was a conference, a Templeton conference where they challenged us to come up with frameworks.
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I think actually, it s the it s the diverse intelligence community that summer Institute.
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SPEAKER_01
Yeah, they had a summer Institute, but I m the logos to be with some circuits.
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Yeah, it s got different life forms.
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So the whole program is called Diverse Intelligence and they challenged us to come up with a framework that was suitable for analyzing different kinds of intelligence together, right?
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Because the kinds of things you do to a human are not good with an octopus, not good with a plant and so on.
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So I started thinking about this and I asked myself, what do all cognitive agents, no matter what their provenance, no matter what their architecture is, what do cognitive agents have in common?
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And it seems to me that what they have in common is some degree of competency to pursue a goal.
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And so what you can do then is you can draw.
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And so what I ended up drawing was this thing that it s kind of like a backwards Minkowski cone diagram where
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all of space could collapse into one axis and then here and then time is this axis.
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And then what you can do is you can draw for any creature, you can semi-quantitatively estimate what are the spatial and temporal
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goals that it can, that it s capable of pursuing.
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So, for example, if you are a tick and all you can, all you really are able to pursue is maxima or bacterium, maximizing the level of some chemical in your vicinity, right, that s all you ve got, it s a tiny little lycone, then you re a simple system like a tick or a bacterium.
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If you are something like a dog, well, you ve got some ability to
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to care about some spatial region, some temporal, you know, you can remember a little bit backwards, you can predict a little bit forwards, but you re never ever going to care about what happens in the next town over four weeks from now.
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It s just, as far as we know, it s just impossible for that kind of architecture.
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If you re a human,
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you might be working towards world peace long after you re dead, right?
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So you might have a planetary scale goal that s enormous, right?
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And then there may be other greater intelligences somewhere that can care in the linear range about numbers of creatures that, you know, some sort of Buddha-like character that can like care about everybody s welfare, like really care the way that we can t.
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And so that, it s not a mapping of what you can sense, how far you can sense, right?
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It s not a mapping of how far you can act.
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It s a mapping of how big are the goals you are capable of envisioning and working towards.
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And I think that enables you to put,
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synthetic kinds of constructs, AIs, aliens, swarms, whatever, on the same diagram.
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Because we re not talking about what you re made of or how you got here.
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We re talking about what are the size and complexity of the goals towards which you can work.
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Is there any other terms that pop into mind that are interesting?
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SPEAKER_00
I m trying to remember, I have a list of them somewhere on my website.
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SPEAKER_01
Target morphology, yeah, definitely check it out.
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Morphoceutical, I like that one.
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Ionoceutical.
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SPEAKER_00
Yeah, yeah, I mean those refer to different types of interventions in the regenerative medicine space.
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So a morphoceutical is something that, it s a kind of intervention that really targets the cells
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decision-making process about what they re going to build.
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And ionoceuticals are like that, but more focused specifically on the bioelectrics.
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I mean, there s also, of course, biochemical, biomechanical, who knows what else, you know, maybe optical kinds of signaling systems there as well.
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Target morphology is interesting.
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It s designed to capture this idea that
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it s not just feed-forward emergence, and oftentimes in biology, I mean, of course, that happens too, but in many cases in biology, the system is specifically working towards a target in anatomical amorphous space, right?
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It s a navigation task, really.
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These kind of problem-solving can be, you know, formalized as navigation tasks, and that they re really going towards a particular region.
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How do you know?
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Because you deviate them and then they go back.
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SPEAKER_01
Let me ask you, because you ve
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really challenged a lot of ideas in biology in the work you do, probably because some of your rebelliousness comes from the fact that you came from a different field of computer engineering.
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But could you give advice to young people today in high school or college that are trying to pave their life story, whether it s in science or elsewhere, how they can have a career they can be proud of or a life they can be proud of?
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Advice.
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SPEAKER_00
Boy, it s dangerous to give advice because things change so fast.
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But one central thing I can say, moving up and through academia and whatnot, you will be surrounded by really smart people.
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And what you need to do is be very careful at distinguishing specific critique versus kind of meta advice.
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And what I mean by that is,
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If somebody really smart and successful and obviously competent is giving you specific critiques on what you ve done, that s gold.
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That s an opportunity to hone your craft, to get better at what you re doing, to learn, to find your mistakes, like that s great.
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If they are telling you what you ought to be studying, how you ought to approach things, what is the right way to think about things,
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you should probably ignore most of that.
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SPEAKER_00
And the reason I make that distinction is that a lot of really, really successful people are very well calibrated on their own ideas, and they in their own field in their own, you know, sort of area, and they know exactly what works and what doesn t and what s good and what s bad, but they re not calibrated on your ideas.
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SPEAKER_00
And so the things they will say, oh, this is a dumb idea, don t do this, and you shouldn t do that, that stuff is generally worse than useless.
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It can be very demoralizing and really limiting.
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So what I say to people is read very broadly, work really hard, know what you re talking about, take all specific criticism as an opportunity to improve what you re doing, and then completely ignore everything else.
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Because I just tell you from my own experience, most of what I consider to be interesting and useful things that we ve done, very smart people have said, this is a terrible idea.
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Don t do that.
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Yeah, I think we just don t know.
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We have no idea beyond our own, like at best, we know what we ought to be doing.
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We very rarely know what anybody else should be doing.
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SPEAKER_01
Yeah, and their ideas, their perspective has been also calibrated, not just on their field and specific situation, but also on a state of that field at a particular time in the past.
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SPEAKER_01
So there s not many people in this world that are able to achieve revolutionary success multiple times in their life.
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So whenever you say somebody very smart, usually what that means is somebody who s smart, who achieved the success,
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at a certain point in their life, and people often get stuck in that place where they found success.
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To be constantly challenging your worldview is a very difficult thing.
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So yeah, also at the same time, probably if a lot of people tell, that s the weird thing about life, if a lot of people tell you that something is stupid or is not gonna work,
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that either means it s stupid, it s not gonna work, or it s actually a great opportunity to do something new.
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and you don t know which one it is, and it s probably equally likely to be either.
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SPEAKER_01
Well, I don t know, the probabilities.
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SPEAKER_01
Depends how lucky you are, depends how brilliant you are.
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But you don t know, and so you can t take that advice as actual data.
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SPEAKER_00
Yeah, you have to, and this is kinda hard to describe and fuzzy, but I m a firm believer that you have to build up your own intuition.
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SPEAKER_00
So over time, right, you have to take your own risks that seem like they make sense to you and then learn from that and build up so that you can trust your own gut about what s a good idea, even when and then sometimes you ll make mistakes and it ll turn out to be a dead end.
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And that s fine.
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That s that s science.
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But but, you know, what I tell my students is is life is hard and science is hard and you re going to sweat and bleed and everything.
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And you should be doing that for ideas that that really fire you up inside.
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and really don t let the common denominator of standardized approaches to things slow you down.
9
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So you mentioned planaria being, in some sense, immortal.
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What s the role of death in life?
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What s the role of death in this whole process we have?
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Is it, when you look at biological systems, is death an important feature, especially as you climb up the hierarchy?
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of competency?
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SPEAKER_00
Boy, that s an interesting question.
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I think that it s certainly a factor that promotes change and turnover and an opportunity to do something different the next time for a larger scale system.
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So apoptosis, you know, it s really interesting.
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I mean, death is really interesting in a number of ways.
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One is, like, you could think about, like, what was the first thing to die?
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know that s that s an interesting question what was the first creature that you could say actually died it s a tough it s a tough thing because we don t have a great definition for it so if you bring a cabbage home and you put it in your fridge
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what point are you going to say it s died, right?
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So it s kind of hard to know.
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There s also one paper in which I talk about this idea that, I mean, think about this and imagine that you have a creature that s aquatic, let s say it s a
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frog or something, or a tadpole, and the animal dies in the pond, it dies for whatever reason, most of the cells are still alive.
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So you could imagine that if when it died there was some sort of breakdown of the connectivity between the cells, a bunch of cells crawled off,
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They could have a life as amoebas.
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Some of them could join together and become a xenobot and toodle around, right?
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So we know from planaria that there are cells that don t obey the Hayflick limit and just sort of live forever.
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So you could imagine an organism that when the organism dies, it doesn t disappear.
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Rather, the individual cells that are still alive crawl off and have a completely different kind of lifestyle and maybe come back together as something else, or maybe they don t.
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So all of this, I m sure, is happening somewhere on some planet.
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So death, in any case, I mean, we already kind of knew this because the molecules, we know that when something dies, the molecules go through the ecosystem, but even the cells don t necessarily die at that point.
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They might have another life in a different way.
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And you can think about something like HeLa, right, the HeLa cell line, you know, that has this, that s had this incredible life.
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There are way more HeLa cells now than there ever been, than there were when she was alive.
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It seems like as the organisms become more and more complex, like if you look at the mammals, their relationship with death becomes more and more complex.
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So the survival imperative starts becoming interesting and humans,
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are arguably the first species that have invented the fear of death, the understanding that you re going to die, let s put it this way.
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So not like instinctual, like I need to run away from the thing that s gonna eat me, but starting to contemplate the finiteness of life.
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SPEAKER_00
I mean one thing, so one thing about the human light, cognitive light cone, is that for the first, as far as we know, for the first time you might have goals that are longer than your lifespan, that are not achievable, right?
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SPEAKER_00
So if you re, let s say, and I don t know if this is true, but if you re a goldfish and you have a 10-minute attention span, I m not sure if that s true, but let s say there s some organism with a short, you know, kind of cognitive light cone that way,
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all of your goals are potentially achievable, because you re probably going to live the next 10 minutes.
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So whatever goals you have, they are totally achievable.
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If you re a human, you could have all kinds of goals that are guaranteed not achievable, because they just take too long.
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Guaranteed, you re not going to achieve them.
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So I wonder, is that a perennial thorn in our psychology that drives some psychoses or whatever?
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I have no idea.
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Another interesting thing about that, actually, and I ve been thinking about this a lot in the last couple of weeks, this notion of giving up.
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So you would think that evolutionarily, the most adaptive way of being is that you go, you fight as long as you physically can, and then when you can t, you can t.
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And there s this photograph, there s videos you can find of insects crawling around where like, you know, like most of it is already gone and it s still sort of crawling, you know, like Terminator style, right?
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Like as far as, as long as you physically can, you keep going.
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Mammals don t do that.
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So a lot of mammals, including rats, have this thing where when they think it s a hopeless situation, they literally give up and die when physically they could have kept going.
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I mean, humans certainly do this.
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And there s some really unpleasant experiments that this guy, I forget his name, did with drowning rats where rats normally drown after a couple of minutes.
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But if you teach them that if you just tread water for a couple of minutes, you ll get rescued, they can tread water for like an hour.
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SPEAKER_00
And so, right, and so they literally just give up and die.
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SPEAKER_00
And so, evolutionarily, that doesn t seem like a good strategy at all.
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SPEAKER_00
Evolutionarily, why would you, like, what s the benefit ever of giving up?
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SPEAKER_00
You just do what you can and, you know, one time out of a thousand, you ll actually get rescued, right?
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SPEAKER_00
But this issue of actually giving up suggests some very interesting metacognitive controls where you ve now gotten to the point where survival actually isn t the top drive.
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and that for whatever, you know, there are other considerations that have taken over.
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And I think that s uniquely a mammalian thing, but I don t know.
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SPEAKER_01
Yeah, the Camus.
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SPEAKER_01
The existentialist question of why live, just the fact that humans commit suicide, is a really fascinating question from an evolutionary perspective.
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And what was the first, and that s the other thing, what is the simplest system, whether evolved or natural or whatever, that is able to do that?
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SPEAKER_00
You can think, what other
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animals are actually able to do that, I m not sure.
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SPEAKER_00
Maybe you could see animals over time, for some reason, lowering the value of survive at all costs gradually until other objectives might become more important.
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SPEAKER_01
Maybe, I don t know how evolutionarily how that gets off the ground.
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SPEAKER_01
That just seems like that would have such a strong pressure against it, you know.
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SPEAKER_01
Just imagine a population with a lower, if you were a mutant in a population that had less of a survival imperative, would your genes outperform the others?
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SPEAKER_00
It seems not.
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SPEAKER_00
Is there such a thing as population selection?
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SPEAKER_00
Because maybe suicide is a way for organisms to decide themselves that they re not fit for the environment somehow.
10
SPEAKER_01
Yeah, that s a really, population level selection is a kind of a deep controversial area, but it s tough because on the face of it, if that was your genome, it wouldn t get propagated because you would die and then your neighbor who didn t have that would have all the kids.
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SPEAKER_00
It feels like there could be some deep truth there that we re not understanding.
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SPEAKER_00
What about you yourself as one biological system?
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SPEAKER_00
Are you afraid of death?
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SPEAKER_01
To be honest, I m more concerned with, especially now getting older and having helped a couple of people pass, I think about what s a...
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SPEAKER_01
what s a good way to go, basically.
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Like nowadays, I don t know what that is.
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SPEAKER_01
Sitting in a facility that sort of tries to stretch you out as long as you can, that doesn t seem good.
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SPEAKER_01
And there s not a lot of opportunities to sort of, I don t know, sacrifice yourself for something useful, right?
10
SPEAKER_01
There s not terribly many opportunities for that in modern society.
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SPEAKER_01
So I don t know, that s more of, I m not particularly worried about death itself, but I ve seen it happen
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And it s not pretty.
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And I don t know what a better alternative is.
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SPEAKER_00
So the existential aspect of it does not worry you deeply?
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SPEAKER_00
The fact that this ride ends?
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SPEAKER_01
No, it began, I mean, the ride began, right?
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SPEAKER_01
So there was, I don t know how many billions of years before that I wasn t around.
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SPEAKER_01
So that s okay.
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SPEAKER_00
But isn t the experience of life, it s almost like feels like you re immortal?
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SPEAKER_00
Because the way you make plans, the way you think about the future, I mean, if you look at your own personal rich experience, yes, you can understand, okay, eventually I die, there s people I love that have died, so surely I will die and it hurts and so on.
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SPEAKER_00
But like it sure doesn t, it s so easy to get lost in feeling like this is gonna go on forever.
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SPEAKER_01
Yeah, it s a little bit like the people who say they don t believe in free will, right?
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SPEAKER_01
I mean, you can say that, but but when you go to a restaurant, you still have to pick a soup and stuff.
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SPEAKER_01
So right.
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SPEAKER_01
So so I don t know if I know I ve I ve actually seen that that happened at lunch with a with a well-known philosopher and he didn t believe in free will.
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SPEAKER_01
And, you know, the waitress came around and he was like, well, let me see.
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SPEAKER_01
I was like, what are you doing here?
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SPEAKER_01
You re going to choose a sandwich, right?
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SPEAKER_01
So it s I think it s one of those things.
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SPEAKER_01
I think you can know that, you know, you re not going to live forever, but
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SPEAKER_01
you can t, it s not practical to live that way unless, you know, so you buy insurance and then you do some stuff like that.
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SPEAKER_01
But mostly, you know, I think you just live as if you can make plans.
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SPEAKER_00
We talked about all kinds of life.
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SPEAKER_00
We talked about all kinds of embodied minds.
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SPEAKER_00
What do you think is the meaning of it all?
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SPEAKER_00
What s the meaning of all the biological lives we ve been talking about here on Earth?
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Why are we here?
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SPEAKER_01
I don t know that that s a well-posed question other than the existential question you posed before.
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Is that question hanging out with the question of what is consciousness and they re at a retreat somewhere?
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SPEAKER_00
Not sure because- Sipping pina coladas and because they re ambiguously defined.
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SPEAKER_01
Maybe.
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I m not sure that any of these things really ride on the correctness of our scientific understanding, but I mean, just for an example, right?
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I ve always found it weird that people
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get really worked up to find out realities about their bodies.
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SPEAKER_01
For example, have you seen Ex Machina?
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So there s this great scene where he s cutting his hand to find out if he s full of cock.
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SPEAKER_01
Now, to me,
10
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If I open up and I find a bunch of cogs, my conclusion is not, oh crap, I must not have true cognition, that sucks.
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SPEAKER_01
My conclusion is, wow, cogs can have true cognition, great.
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SPEAKER_01
So it seems to me, I guess I m with Descartes on this one, that whatever the truth ends up being of what is consciousness, how it can be conscious, none of that is going to alter my primary experience, which is this is what it is.
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SPEAKER_01
And if a bunch of molecular networks can do it, fantastic.
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SPEAKER_01
If it turns out that there s a non-corporeal soul, great, we ll study that, whatever.
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SPEAKER_01
But the fundamental existential aspect of it is, you know, if somebody told me today that, yeah, you were created yesterday and all your memories are, you know, sort of fake, you know, kind of like Boltzmann brains, right?
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SPEAKER_01
And Hume s skepticism and all that.
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SPEAKER_01
Yeah okay well so so but but here i am now so so let s experience.
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SPEAKER_00
It s primal, so that s the thing that matters.
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SPEAKER_00
So the backstory doesn t matter, the explanation.
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SPEAKER_01
I think so, from a first person perspective.
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SPEAKER_01
Now, from a third person, like scientifically, it s all very interesting.
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From a third person perspective, I could say, wow, that s amazing that this happens, and how does it happen, and whatever.
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SPEAKER_01
But from a first person perspective, I could care less.
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What I learned from any of these scientific facts is, okay, well I guess then that s what,
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SPEAKER_01
is sufficient to give me my amazing first person perspective.
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SPEAKER_00
I think if you dig deeper and deeper and get surprising answers to why the hell we re here, it might give you some guidance on how to live.
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SPEAKER_01
Maybe, maybe, I don t know.
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SPEAKER_01
That would be nice.
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SPEAKER_01
On the one hand, you might be right, because on the one hand, I don t know what else could possibly give you that guidance, right?
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SPEAKER_01
So you would think that it would have to be that, or it would have to be science because there isn t anything else.
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So maybe, on the other hand,
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I am really not sure how you go from any, you know, what they call from an is to an ought, right?
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From any factual description of what s going on.
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This goes back to the natural, right?
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Just because somebody says, oh man, that s completely not natural.
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That s never happened on Earth before.
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I m not impressed by that whatsoever.
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I think whatever has or hasn t happened, we are now in a position to do better if we can, right?
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Well, that s also good, because you said there s science and there s nothing else.
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It s really tricky to know how to intellectually deal with a thing that science doesn t currently understand.
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The thing is, if you believe that science solves everything, you can too easily in your mind think
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our current understanding, like we ve solved everything.
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It jumps really quickly to not science as a mechanism, as a process, but more like the science of today.
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You could just look at human history, and throughout human history, just physicists and everybody would claim we ve solved everything.
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There s a few small things to figure out, and we basically solved everything.
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where in reality, I think asking like, what is the meaning of life is resetting the palette of like, we might be tiny and confused and don t have anything figured out.
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It s almost going to be hilarious a few centuries from now when they look back at how dumb we were.
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Yeah, I 100% agree.
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So when I say science and nothing else, I certainly don t mean the science of today, because I think overall, I think we know very little.
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I think most of the things that we re sure of now are going to be, as you said, are going to look hilarious down the line.
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So I think we re just at the beginning of a lot of really important things.
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When I say nothing but science, I also include the kind of first person, what I call science that you do.
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So the interesting thing about, I think about consciousness and studying consciousness and things like that in the first person is unlike doing science in the third person, where you as the scientist are minimally changed by it, maybe not at all.
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So when I do an experiment, I m still me.
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There s the experiment, whatever I ve done, I ve learned something.
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So that s a small change, but overall, that s it.
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In order to really study consciousness,
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you are part of the experiment.
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You will be altered by that experiment, right?
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Whatever it is that you re doing, whether it s some sort of contemplative practice or some sort of psychoactive, whatever, you are now your own experiment and you are right in.
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So I fold that in.
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I think that s part of it.
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I think that exploring our own mind and our own consciousness is very important.
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I think much of it is not captured by what currently is third-person science, for sure.
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But ultimately, I include all of that in science with a capital S in terms of like a rational investigation of both first and third person aspects of our world.
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We are our own experiment, as beautifully put.
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And when two systems get to interact with each other, that s a kind of experiment.
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So I m deeply honored that you would do this experiment with me today.
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Michael, I m a huge fan of your work.
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Thank you for doing everything you re doing.
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I can t wait to see the kind of incredible things you build.
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So thank you for talking today.
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Really appreciate being here, thank you.
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Thank you for listening to this conversation with Michael Levin.
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To support this podcast, please check out our sponsors in the description.
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And now, let me leave you with some words from Charles Darwin in The Origin of Species.
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From the war of nature, from famine and death, the most exalted object which we re capable of conceiving, namely the production of the higher animals, directly follows.
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There s grandeur in this view of life, with its several powers, having been originally breathed into a few forms, or into one, and that, whilst this planet has gone cycling on according to the fixed laws of gravity, from a so simple a beginning, endless forms, most beautiful and most wonderful, have been and are being evolved.
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Thank you for listening.
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I hope to see you next time.