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The following is a conversation with George Hotz, his third time on this podcast.
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He s the founder of Kama.ai that seeks to solve autonomous driving and is the founder of a new company called TinyCorp that created TinyGrad, a neural network framework that is extremely simple with the goal of making it run on any device by any human easily and efficiently.
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As you know, George also did a large number of fun and amazing things from hacking the iPhone to recently joining Twitter for a bit as an intern in quotes, making the case for refactoring the Twitter code base.
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In general, he s a fascinating engineer and human being and one of my favorite people to talk to.
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And now, a quick few 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 ve got Numerai for the world s hardest data science tournament, Babbel for learning new languages, NetSuite for business management software, InsightTracker for blood paneling, and AG1 for my daily multivitamin.
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Choose wisely, my friends.
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Also, if you want to work on our team, we re always hiring.
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Go to lexfriedman.com slash hiring.
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And now onto the full ad reads.
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As always, no ads in the middle.
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I try to make this interesting, but if you must skip them, friends, please still check out our sponsors.
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I enjoy their stuff.
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Maybe you will too.
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This episode is brought to you by Numeri, a hedge fund that uses artificial intelligence and machine learning to make investment decisions.
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They created a tournament that challenges data scientists to build best predictive models for financial markets.
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It s basically just a really, really difficult real-world data set to test out your ideas for how to build machine learning models.
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Head over to numeri.ai to sign up for a tournament and hone your machine learning skills.
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That s numeri.ai for a chance to play against me and win a share of the tournament s prize pool.
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That s numeri slash lex.
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This show is also brought to you by Babbel, an app and website that gets you speaking in a new language within weeks.
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I have been using it to learn a few languages, Spanish, to review Russian, to practice Russian, to revisit Russian from a different perspective, because that becomes more and more relevant for some of the previous conversations I ve had and some upcoming conversations I have.
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It really is fascinating how much another language, knowing another language, even to a degree where you can just have little bits and pieces of a conversation, can really unlock an experience in another part of the world.
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When you travel in France and Paris, just having a few words at your disposal, a few phrases,
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it begins to really open you up to strange, fascinating new experiences that ultimately, at least to me, teach me that we re all the same.
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We have to first see our differences to realize those differences are grounded in a basic humanity.
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And that experience that we re all very different and yet at the core the same, I think travel with the aid of language really helps unlock.
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They manage all the messy stuff that is required to run a business, the financials, the human resources, the inventory, if you do that kind of thing, e-commerce, all that stuff, all the business-related details.
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I know how stressed I am about everything that s required to run a team, to run a business that involves much more than just ideas and designs and engineering.
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It involves all the management of human beings, all the complexities of that, the financials, all of it.
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And so you should be using the best tools for the job.
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I sometimes wonder if I have it in me.
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mentally and skill-wise to be a part of running a large company.
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I think like with a lot of things in life, it s one of those things you shouldn t wonder too much about.
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You should either do or not do.
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But again, using the best tools for the job is required here.
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That s netsuite.com slash lex.
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This show is also brought to you by Insight Tracker, a service I use to track biological data, data that comes from my body, to predict, to tell me what I should do with my lifestyle, with my diet, what s working and what s not working.
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It s obvious, all the exciting breakthroughs that are happening with transformers, with large language models.
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even with diffusion, all of that is obvious that with raw data, with huge amounts of raw data, fine tuned to the individual, would really reveal to us the signal in all the noise of biology.
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I feel like that s on the horizon.
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The kinds of leaps in development that we saw in language, and now more and more visual data,
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I feel like biological data is around the corner.
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Unlocking what s there in this multi-hierarchical distributed system that is our biology.
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What is it telling us?
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What is the secrets it holds?
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What is the thing that it s missing that could be aided?
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Simple lifestyle changes, simple diet changes, simple changes in all kinds of things that are controllable by individual human being.
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I can t wait till that s a possibility and Insight Tracker is taking steps towards that.
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This show is also brought to you by Athletic Greens.
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That s now called AG1.
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It has the AG1 drink.
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I drink it twice a day.
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At the very least, it s an all-in-one daily drink to support better health and peak performance.
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I drink it cold.
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It s refreshing.
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It s grounding.
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It helps me reconnect with the basics, the nutritional basics that makes this whole machine that is our human body run.
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All the crazy mental stuff I do for work, the physical challenges, everything.
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The highs and lows of life itself.
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All of that is somehow made better knowing that at least you got your nutrition in check.
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At least you re getting enough sleep.
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At least you re doing the basics.
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At least you re doing the exercise.
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Once you get those basics in place, I think you can do some quite difficult things in life.
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But anyway, beyond all that is just a source of happiness and a kind of a feeling of home.
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The feeling that comes from returning to the habit time and time again.
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Anyway, they ll give you a one month supply of fish oil when you sign up at DrinkAG1.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 George Hotz.
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You mentioned something in a stream about the philosophical nature of time.
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So let s start with a wild question.
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Do you think time is an illusion?
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You know, I sell phone calls to Kama for $1,000.
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And some guy called me and like, you know, it s $1,000, you can talk to me for half an hour.
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And he s like, yeah, okay, so like, time doesn t exist.
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And I really wanted to share this with you.
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I m like, oh, what do you mean time doesn t exist, right?
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I think time is a useful model, whether it exists or not, right?
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Does quantum physics exist?
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Well, it doesn t matter.
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It s about whether it s a useful model to describe reality.
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Is time maybe compressive?
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Do you think there is an objective reality or is everything just useful models?
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Underneath it all, is there an actual thing that we re constructing models for?
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I don t know.
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I was hoping you would know.
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I don t think it matters.
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I mean, this kind of connects to the models of constructive reality with machine learning, right?
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Sure.
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Like, is it just nice to have useful approximations of the world such that we can do something with it?
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So there are things that are real.
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Columnar graph complexity is real.
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Yeah.
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Yeah.
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The compressive thing.
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Math.
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Math is real, yeah.
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This should be a t-shirt.
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And I think hard things are actually hard.
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I don t think P equals NP.
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Ooh, strong words.
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Well, I think that s the majority.
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I do think factoring is in P, but.
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I don t think you re the person that falls the majority in all walks of life, so, but it s good.
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For that one, I do.
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Yeah, in theoretical computer science, you re one of the sheep.
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All right, but to you, time is a useful model.
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Sure.
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What were you talking about on the stream with time?
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Are you made of time?
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If I remembered half the things I said on stream, someday someone s gonna make a model of all of it and it s gonna come back to haunt me.
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Someday soon?
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Yeah, probably.
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Would that be exciting to you or sad that there s a George Hotz model?
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I mean, the question is when the George Hotz model is better than George Hotz.
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Like I am declining and the model is growing.
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What is the metric by which you measure better or worse in that if you re competing with yourself
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Maybe you can just play a game where you have the George Haas answer and the George Haas model answer and ask which people prefer.
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People close to you or strangers?
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Either one.
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It will hurt more when it s people close to me, but both will be overtaken by the George Haas model.
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It d be quite painful, right?
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Loved ones, family members would rather have the model over for Thanksgiving than you.
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Yeah.
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or like significant others, would rather sext with the large language model version of you.
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Especially when it s fine-tuned to their preferences.
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Yeah, well, that s what we re doing in a relationship, right?
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We re just fine-tuning ourselves, but we re inefficient with it, because we re selfish and greedy and so on.
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Our language models can fine-tune more efficiently, more selflessly.
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There s a Star Trek Voyager episode where, you know, Catherine Janeway, lost in the Delta Quadrant, makes herself a lover on the holodeck.
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lover falls asleep on her arm, and he snores a little bit, and Janeway edits the program to remove that.
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And then, of course, the realization is, wait, this person s terrible.
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It is actually all their nuances and quirks and slight annoyances that make this relationship worthwhile.
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But I don t think we re going to realize that until it s too late.
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Well, I think a large language model could incorporate the flaws and the quirks and all that kind of stuff.
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Just the perfect amount of quirks and flaws to make you charming without crossing the line.
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Yeah, yeah.
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And that s probably a good approximation of the percent of time the language model should be cranky or an asshole or jealous or all this kind of stuff.
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And of course it can and it will, but all that difficulty at that point is artificial.
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There s no more real difficulty.
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Okay, what s the difference between real and artificial?
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Artificial difficulty is difficulty that s constructed or could be turned off with a knob.
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Real difficulty is like you re in the woods and you ve got to survive.
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So if something cannot be turned off with a knob, it s real?
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Yeah, I think so.
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Or, I mean, you can t get out of this by smashing the knob with a hammer.
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I mean, maybe you kind of can.
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You know, Into the Wild when, you know, Alexander Supertramp, he wants to explore something that s never been explored before.
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But it s the 90s, everything s been explored.
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So he s like, well, I m just not going to bring a map.
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Yeah.
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SPEAKER_00
I mean, no, you re not exploring.
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You should have brought a map, dude.
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You died.
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There was a bridge a mile from where you were camping.
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How does that connect to the metaphor of the knob?
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By not bringing the map, you didn t become an explorer.
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You just smashed the thing.
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The difficulty is still artificial.
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You failed before you started.
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What if we just don t have access to the knob?
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Well, that maybe is even scarier.
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We already exist in a world of nature, and nature has been fine-tuned over billions of years to have a
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humans build something and then throw the knob away in some grand romantic gesture is horrifying.
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Do you think of us humans as individuals that are like born and die?
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Or is it, are we just all part of one living organism that is earth, that is nature?
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I don t think there s a clear line there.
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I think it s all kind of just fuzzy.
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SPEAKER_00
I don t know.
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SPEAKER_00
I mean, I don t think I m conscious.
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SPEAKER_00
I don t think I m anything.
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I think I m just a computer program.
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So it s all computation.
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Everything running in your head is computation.
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SPEAKER_00
Everything running in the universe is computation, I think.
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I believe the extended church time thesis.
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SPEAKER_01
Yeah, but there seems to be an embodiment to your particular computation, like there s a consistency.
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SPEAKER_00
Well, yeah, but I mean models have consistency too.
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Yeah.
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Models that have been RLHF d will continually say, you know, like, well, how do I murder ethnic minorities?
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SPEAKER_00
Oh, well, I can t let you do that, Al.
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SPEAKER_00
There s a consistency to that behavior.
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It s all RLHF.
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Like, we all RLHF each other.
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We find, we provide human feedback in there that
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thereby fine-tune these little pockets of computation, but it s still unclear why that pocket of computation stays with you for years.
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It just kind of, you have this consistent set of physics, biology, whatever you call the neurons firing, the electrical signals, the mechanical signals, all of that, that seems to stay there, and it contains information, it stores information, and that information permeates through time.
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and stays with you, there s like memory, it s like sticky.
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SPEAKER_00
Okay, to be fair, like a lot of the models we re building today are very, even RLHF is nowhere near as complex as the human loss function.
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Reinforcement learning with human feedback.
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um you know when i talked about will gpt-12 be agi my answer is no of course not i mean cross-entropy loss is never going to get you there you need uh probably rl in fancy environments in order to get something that would be considered like agi like so to ask like the question about like why i don t know like it s just some quirk of evolution right i don t think there s anything particularly special about where i ended up where humans ended up
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So okay, we have human level intelligence.
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Would you call that AGI, whatever we have, GI?
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SPEAKER_00
Look, actually, I don t really even like the word AGI, but general intelligence is defined to be whatever humans have.
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SPEAKER_01
Okay, so why can GPT-12 not get us to AGI?
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Can we just like linger on that?
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SPEAKER_00
If your loss function is categorical cross entropy, if your loss function is just try to maximize compression, I have a SoundCloud I wrap,
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And I tried to get ChatGPT to help me write raps.
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And the raps that it wrote sounded like YouTube comment raps.
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SPEAKER_00
You know, you can go on any rap beat online and you can see what people put in the comments.
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SPEAKER_00
And it s the most like mid quality rap you can find.
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SPEAKER_00
Is mid good or bad?
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SPEAKER_00
Mid is bad.
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SPEAKER_00
Mid is bad.
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SPEAKER_00
It s like mid, it s like... Every time I talk to you, I learn new words.
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SPEAKER_00
Mid.
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SPEAKER_00
Mid, yeah.
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I was like, is it like basic?
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SPEAKER_01
Is that what mid means?
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SPEAKER_00
I know, it s like middle of the curve, right?
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SPEAKER_00
So there s like that intelligence curve, and you have like the dumb guy, the smart guy, and then the mid guy.
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SPEAKER_00
Actually, being the mid guy is the worst.
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SPEAKER_00
The smart guy is like, I put all my money in Bitcoin.
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The mid guy is like, you can t put money in Bitcoin.
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It s not real money.
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And all of it is a joke.
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Genius meme, that s another interesting one.
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Memes, the humor, the idea, the absurdity encapsulated in a single image.
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SPEAKER_00
And it just kind of propagates virally between all of our brains.
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I didn t get much sleep last night, so I m very, I sound like I m high, but I swear I m not.
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Do you think we have ideas or ideas have us?
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SPEAKER_02
I think that we re gonna get super scary memes once the AIs actually are superhuman.
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SPEAKER_00
Ooh, you think AI will generate memes?
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SPEAKER_00
Of course.
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SPEAKER_00
You think it ll make humans laugh?
1
SPEAKER_02
I think it s worse than that.
1
SPEAKER_02
So, um, Infinite Jest, it s introduced in the first
1
SPEAKER_02
50 pages is about a tape that you, once you watch it once, you only ever want to watch that tape.
1
SPEAKER_02
In fact, you want to watch the tape so much that someone says, okay, here s a hacksaw, cut off your pinky, and then I ll let you watch the tape again, and you ll do it.
1
SPEAKER_02
So we re actually going to build that, I think, but it s not going to be one static tape.
1
SPEAKER_02
I think the human brain is too complex to be stuck in one static tape like that.
1
SPEAKER_02
If you look at, like, ant brains, maybe they can be stuck on a static tape.
1
SPEAKER_02
but we re going to build that using generative models.
1
SPEAKER_02
We re going to build the TikTok that you actually can t look away from.
1
SPEAKER_00
So TikTok is already pretty close there, but the generation is done by humans.
1
SPEAKER_00
The algorithm is just doing their recommendation, but if the algorithm is also able to do the generation... Well, it s a question about how much intelligence is behind it, right?
1
SPEAKER_02
So the content is being generated by, let s say, one humanity worth of intelligence, and you can quantify a humanity, right?
1
SPEAKER_02
That s a, you know, it s...
1
SPEAKER_02
exaflops, yadaflops, but you can quantify it.
1
SPEAKER_02
Once that generation is being done by a hundred humanities, you re done.
1
SPEAKER_00
So it s actually scale that s the problem, but also speed.
1
SPEAKER_00
Yeah.
1
SPEAKER_00
And what if it s sort of manipulating the very limited human dopamine engine for porn?
1
SPEAKER_00
Imagine just TikTok, but for porn.
1
SPEAKER_02
Yeah.
1
SPEAKER_00
It s like a brave new world.
1
SPEAKER_02
I don t even know what it ll look like, right?
1
SPEAKER_02
Like again, you can t imagine the behaviors of something smarter than you, but a super intelligent, an agent that just dominates your intelligence so much will be able to completely manipulate you.
1
SPEAKER_00
Is it possible that it won t really manipulate, it ll just move past us?
1
SPEAKER_00
It ll just kinda exist the way water exists or the air exists?
1
SPEAKER_02
You see, and that s the whole AI safety thing.
1
SPEAKER_02
It s not the machine that s gonna do that.
1
SPEAKER_02
It s other humans using the machine that are gonna do that to you.
1
SPEAKER_00
Yeah, because the machine is not interested in hurting humans.
1
SPEAKER_02
The machine is a machine, but the human gets the machine, and there s a lot of humans out there very interested in manipulating you.
1
SPEAKER_00
Well, let me bring up Eliezer Yudkowsky, who recently sat where you re sitting.
1
SPEAKER_00
He thinks that AI will almost surely kill everyone.
1
SPEAKER_00
Do you agree with him or not?
1
SPEAKER_02
Yes, but maybe for a different reason.
1
SPEAKER_00
Okay.
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SPEAKER_00
And I ll try to get you to find hope, or we could find a no to that answer, but why yes?
1
SPEAKER_02
Okay.
1
SPEAKER_02
Why didn t nuclear weapons kill everyone?
1
SPEAKER_00
That s a good question.
1
SPEAKER_02
I think there s an answer.
1
SPEAKER_02
I think it s actually very hard to deploy nuclear weapons tactically.
1
SPEAKER_02
It s very hard to accomplish tactical objectives.
1
SPEAKER_02
Great, I can nuke their country.
1
SPEAKER_02
I have an irradiated pile of rubble.
1
SPEAKER_02
I don t want that.
1
SPEAKER_00
Why not?
1
SPEAKER_02
Why don t I want an irradiated pile of rubble?
1
SPEAKER_02
For all the reasons no one wants an irradiated pile of rubble.
1
SPEAKER_00
Oh, because you can t use that land for resources, you can t populate the land.
1
SPEAKER_02
Yeah.
1
SPEAKER_02
What you want, a total victory in a war, is not usually the irradiation and eradication of the people there.
1
SPEAKER_02
It s the subjugation and domination of the people.
1
SPEAKER_00
Okay, so you can t use this strategically, tactically in a war to help you, to help gain a military advantage.
1
SPEAKER_00
It s all complete destruction, right?
1
SPEAKER_00
But there s egos involved.
1
SPEAKER_00
It s still surprising.
1
SPEAKER_00
Still surprising that nobody pressed the big red button.
1
SPEAKER_02
It s somewhat surprising, but you see, it s the little red button that s gonna be pressed with AI that s gonna
1
SPEAKER_02
And that s why we die.
1
SPEAKER_02
It s not because the AI, if there s anything in the nature of AI, it s just the nature of humanity.
1
SPEAKER_00
What s the algorithm behind the little red button?
1
SPEAKER_00
What possible ideas do you have for how a human species ends?
1
SPEAKER_02
Sure.
1
SPEAKER_02
So I think the most obvious way to me is wireheading.
1
SPEAKER_02
We end up amusing ourselves to death.
1
SPEAKER_02
We end up all staring at that infinite TikTok and forgetting to eat.
1
SPEAKER_02
Maybe it s even more benign than this.
1
SPEAKER_02
Maybe we all just stop reproducing.
1
SPEAKER_02
Now, to be fair, it s probably hard to get all of humanity.
1
SPEAKER_00
The interesting thing about humanity is the diversity in it.
1
SPEAKER_00
Organisms in general.
1
SPEAKER_00
There s a lot of weirdos out there.
1
SPEAKER_00
Two of them are sitting here.
1
SPEAKER_02
I mean, diversity in humanity is- With due respect.
1
SPEAKER_02
I wish I was more weird.
1
SPEAKER_02
No, look, I m drinking smart water, man.
1
SPEAKER_02
That s like a Coca-Cola product, right?
1
SPEAKER_00
You went corporate, George Haas.
1
SPEAKER_02
No, I went corporate.
1
SPEAKER_02
No, the amount of diversity in humanity I think is decreasing, just like all the other biodiversity on the planet.
1
SPEAKER_00
Yeah, social media s not helping, huh?
1
SPEAKER_02
Go eat McDonald s in China.
1
SPEAKER_00
Yeah.
1
SPEAKER_02
No, it s the interconnectedness that s doing it.
1
SPEAKER_00
Oh, that s interesting.
1
SPEAKER_00
So everybody starts relying on the connectivity of the internet.
1
SPEAKER_00
and over time that reduces the diversity, the intellectual diversity, and then that gets you everybody into a funnel.
1
SPEAKER_00
There s still going to be a guy in Texas.
1
SPEAKER_02
There is, and yeah.
1
SPEAKER_00
In a bunker.
1
SPEAKER_02
To be fair, do I think AI kills us all?
1
SPEAKER_02
I think AI kills everything we call like society today.
1
SPEAKER_02
I do not think it actually kills the human species.
1
SPEAKER_02
I think that s actually incredibly hard to do.
1
SPEAKER_00
Yeah, but society, like if we start over, that s tricky.
1
SPEAKER_00
Most of us don t know how to do most things.
1
SPEAKER_02
Yeah, but some of us do, and they ll be okay, and they ll rebuild after the great AI.
1
SPEAKER_00
What s rebuilding look like?
1
SPEAKER_00
How much do we lose?
1
SPEAKER_00
What has human civilization done?
1
SPEAKER_00
That s interesting.
1
SPEAKER_00
Combustion engine, electricity.
1
SPEAKER_00
So, uh, power and energy.
1
SPEAKER_00
That s interesting.
1
SPEAKER_00
Like how to harness energy.
1
SPEAKER_02
Whoa, whoa, whoa, whoa.
1
SPEAKER_02
They re going to be religiously against that.
1
SPEAKER_00
Are they going to get back to, uh, like fire?
1
SPEAKER_02
Sure.
1
SPEAKER_02
I mean, there ll be a, there ll be, it ll, it ll be like, you know, some kind of Amish looking kind of thing, I think.
1
SPEAKER_02
I think they re going to have very strong taboos against technology.
1
SPEAKER_00
Like technology is almost like a new religion.
1
SPEAKER_00
Technology is the devil.
1
SPEAKER_00
And nature is God.
1
SPEAKER_00
So closer to nature.
1
SPEAKER_00
But can you really get away from AI if it destroyed 99% of the human species?
1
SPEAKER_00
Isn t it somehow have a hold, like a stronghold?
1
SPEAKER_02
What s interesting about everything we build, I think we re going to build super intelligence before we build any sort of robustness in the AI.
1
SPEAKER_02
We cannot build an AI that is capable of going out into nature and surviving like a bird, right?
1
SPEAKER_02
A bird is an incredibly robust organism.
1
SPEAKER_02
We ve built nothing like this.
1
SPEAKER_02
We haven t built a machine that s capable of reproducing.
1
SPEAKER_00
Yes, but there is, you know, I work with Lego robots a lot now.
1
SPEAKER_00
I have a bunch of them.
1
SPEAKER_00
They re mobile.
1
SPEAKER_00
Mm-hmm.
1
SPEAKER_00
They can t reproduce, but all they need is, I guess you re saying they can t repair themselves.
1
SPEAKER_00
But if you have a large number, if you have like 100 million of them.
1
SPEAKER_02
Let s just focus on them reproducing, right?
1
SPEAKER_02
They have microchips in them.
1
SPEAKER_02
Okay, then do they include a fab?
1
SPEAKER_00
No.
1
SPEAKER_02
Then how are they gonna reproduce?
1
SPEAKER_00
Well, it doesn t have to be all on board, right?
1
SPEAKER_00
They can go to a factory, to a repair shop.
1
SPEAKER_02
Yeah, but then you re really moving away from robustness.
1
SPEAKER_02
Yes.
1
SPEAKER_02
All of life is capable of reproducing without needing to go to a repair shop.
1
SPEAKER_02
Life will continue to reproduce in the complete absence of civilization.
1
SPEAKER_02
Robots will not.
1
SPEAKER_02
So if the AI apocalypse happens,
1
SPEAKER_02
I mean, the AIs are gonna probably die out, because I think we re gonna get, again, super intelligence long before we get robustness.
1
SPEAKER_00
What about if you just improve the fab to where you just have a 3D printer that can always help you?
1
SPEAKER_02
Well, that d be very interesting.
1
SPEAKER_02
I m interested in building that.
1
SPEAKER_00
Of course you are.
1
SPEAKER_00
How difficult is that problem, to have a robot that basically can build itself?
1
SPEAKER_02
Very, very hard.
1
SPEAKER_00
I think you ve mentioned this to me or somewhere where people think it s easy conceptually.
1
SPEAKER_02
And then they remember that you re going to have to have a fab.
1
SPEAKER_00
Yeah, on board.
1
SPEAKER_00
Of course.
1
SPEAKER_00
So a 3D printer that prints a 3D printer.
1
SPEAKER_02
Yeah.
1
SPEAKER_00
Yeah, on legs.
1
SPEAKER_00
Why is that hard?
1
SPEAKER_02
Well, because it s, I mean, a 3D printer is a very simple machine, right?
1
SPEAKER_02
Okay, you re gonna print chips?
1
SPEAKER_02
You re gonna have an atomic printer?
1
SPEAKER_02
How are you gonna dope the silicon?
1
SPEAKER_00
Yeah.
1
SPEAKER_00
Right?
1
SPEAKER_02
How are you gonna etch the silicon?
1
SPEAKER_00
You re gonna have to have a very interesting kind of fab if you wanna have a lot of computation on board.
1
SPEAKER_00
But you can do like structural type of robots that are dumb.
1
SPEAKER_02
Yeah, but structural type of robots aren t going to have the intelligence required to survive in any complex environment.
1
SPEAKER_00
What about like ants type of systems?
1
SPEAKER_00
We have like trillions of them.
1
SPEAKER_02
I don t think this works.
1
SPEAKER_02
I mean, again, ants at their very core are made up of cells that are capable of individually reproducing.
1
SPEAKER_02
They re doing quite a lot of computation that we re taking for granted.
1
SPEAKER_02
It s not even just the computation.
1
SPEAKER_02
It s that reproduction is so inherent.
1
SPEAKER_02
Okay, so there s two stacks of life in the world.
1
SPEAKER_02
There s the biological stack and the silicon stack.
1
SPEAKER_02
The biological stack starts with reproduction.
1
SPEAKER_02
Reproduction is at the absolute core.
1
SPEAKER_02
The first proto-RNA organisms were capable of reproducing.
1
SPEAKER_02
The silicon stack, despite as far as it s come, is nowhere near being able to reproduce.
1
SPEAKER_00
Yeah, so the fab movement, digital fabrication, fabrication in the full range of what that means is still in the early stages.
1
SPEAKER_03
Yeah.
1
SPEAKER_00
You re interested in this world.
1
SPEAKER_02
Even if you did put a fab on the machine, let s say, okay, we can build fabs.
1
SPEAKER_02
We know how to do that as humanity.
1
SPEAKER_02
We can probably put all the precursors that build all the machines and the fabs also in the machine.
1
SPEAKER_02
First off, this machine is going to be absolutely massive.
1
SPEAKER_02
Think of the size of the thing required to reproduce a machine today.
1
SPEAKER_02
Is our civilization capable of reproduction?
1
SPEAKER_02
Can we reproduce our civilization on Mars?
1
SPEAKER_00
If we were to construct a machine that is made up of humans, like a company, it can reproduce itself.
1
SPEAKER_00
I don t know, it feels like 115 people.
1
SPEAKER_00
I think it s so much harder than that.
1
SPEAKER_00
120?
1
SPEAKER_00
I was looking for a number.
1
SPEAKER_02
I believe that Twitter can be run by 50 people.
1
SPEAKER_02
I think that this is going to take most of, like, it s just most of society, right?
1
SPEAKER_02
Like we live in one globalized world.
1
SPEAKER_00
No, but you re not interested in running Twitter, you re interested in seeding.
1
SPEAKER_00
Like, you want to seed a civilization and then, because humans can like,
1
SPEAKER_02
Oh, okay, you re talking about, yeah, okay, so you re talking about the humans reproducing and basically what s the smallest self-sustaining colony of humans?
1
SPEAKER_00
Yeah.
1
SPEAKER_02
Yeah, okay, fine, but they re not gonna be making five nanometer chips.
1
SPEAKER_00
Over time, they will.
1
SPEAKER_00
I think you re being, we have to expand our conception of time here, going back to the original timescale.
1
SPEAKER_00
I mean, over, across maybe 100 generations, we re back to making chips.
1
SPEAKER_00
No?
1
SPEAKER_00
If you seed the colony correctly.
1
SPEAKER_02
Maybe, or maybe they ll watch our colony die out over here and be like, we re not making chips, don t make chips.
1
SPEAKER_00
No, but you have to seed that colony correctly.
1
SPEAKER_03
Whatever you do, don t make chips.
1
SPEAKER_03
Chips are what led to their downfall.
1
SPEAKER_00
Well, that is the thing that humans do.
1
SPEAKER_00
They come up, they construct a devil, a good thing and a bad thing, and they really stick by that, and then they murder each other over that.
1
SPEAKER_00
There s always one asshole in the room who murders everybody.
1
SPEAKER_00
And he usually makes tattoos and nice branding with flags and stuff.
1
SPEAKER_03
Do you need that asshole?
1
SPEAKER_03
That s the question, right?
1
SPEAKER_03
Humanity works really hard today to get rid of that asshole, but I think they might be important.
1
SPEAKER_00
Yeah, this whole freedom of speech thing.
1
SPEAKER_00
The freedom of being an asshole seems kind of important.
1
SPEAKER_00
That s right.
1
SPEAKER_00
Man, this thing, this fab, this human fab that we constructed, this human civilization is pretty interesting.
1
SPEAKER_00
And now it s building artificial copies of itself, or artificial copies of various aspects of itself that seem interesting, like intelligence.
1
SPEAKER_00
And I wonder where that goes.
1
SPEAKER_02
I like to think it s just like another stack for life, like we have like the bio stack life, like we re a bio stack life, and then the silicon stack life.
1
SPEAKER_00
But it seems like the ceiling, or there might not be a ceiling, or at least the ceiling is much higher for the silicon stack.
1
SPEAKER_02
oh, no, we don t know what the ceiling is for the biostack either.
1
SPEAKER_02
The biostack just seemed to move slower.
1
SPEAKER_02
You have Moore s law, which is not dead despite many proclamations.
1
SPEAKER_00
In the biostack or the silicon stack?
1
SPEAKER_00
In the silicon stack.
1
SPEAKER_02
And you don t have anything like this in the biostack.
1
SPEAKER_02
So I have a meme that I posted.
1
SPEAKER_02
I tried to make a meme.
1
SPEAKER_02
It didn t work too well.
1
SPEAKER_02
But I posted a picture of Ronald Reagan and Joe Biden.
1
SPEAKER_02
And you look, this is 1980, and this is 2020.
1
SPEAKER_02
And these two humans are basically the same.
1
SPEAKER_02
There s been no change in humans in the last 40 years.
1
SPEAKER_02
And then I posted a computer from 1980 and a computer from 2020.
1
SPEAKER_02
Wow.
1
SPEAKER_00
Yeah, with the early stages, right?
1
SPEAKER_00
Which is why you said when you said the fab, the size of the fab required to make another fab is very large right now.
1
SPEAKER_00
But computers were very large.
1
SPEAKER_00
80 years ago and they got pretty tiny and People are starting to want to wear them on their face In order to escape reality That s the thing in order to be live inside the computer.
1
SPEAKER_00
Yeah put a screen right here I don t have to see the rest of you assholes.
1
SPEAKER_03
I ve been ready for a long time.
1
SPEAKER_00
You like virtual reality.
1
SPEAKER_00
I love it Do you want to live there?
1
SPEAKER_03
Yeah
1
SPEAKER_00
Yeah, part of me does too.
1
SPEAKER_00
How far away are we, do you think?
1
SPEAKER_02
Judging from what you can buy today, far.
1
SPEAKER_02
Very far.
1
SPEAKER_00
I gotta tell you that I had the experience of Meta s Kodak Avatar, where it s an ultra high resolution scan.
1
SPEAKER_00
It looked real.
1
SPEAKER_02
mean the headsets just are not quite at like eye resolution yet i haven t put on any headset where i m like oh this could be the real world whereas when i put good headphones on audio is there like we we can reproduce audio that i m like i m actually in a jungle right now i if i close my eyes i can t tell i m not yeah but then there s also smell and all that kind of stuff sure i don t know i
1
SPEAKER_00
the power of imagination or the power of the mechanism in the human mind that fills the gaps, that kind of reaches and wants to make the thing you see in the virtual world real to you, I believe in that power.
1
SPEAKER_02
Or humans want to believe.
1
SPEAKER_00
Yeah.
1
SPEAKER_00
Like what if you re lonely?
1
SPEAKER_00
What if you re sad?
1
SPEAKER_00
What if you re really struggling in life and here s a world where you don t have to struggle anymore?
1
SPEAKER_01
Humans wanna believe so much that people think the large language models are conscious.
1
SPEAKER_01
That s how much humans wanna believe.
1
SPEAKER_00
Strong words.
1
SPEAKER_00
He s throwing left and right hooks.
1
SPEAKER_00
Why do you think large language models are not conscious?
1
SPEAKER_03
I don t think I m conscious.
1
SPEAKER_00
Oh, so what is consciousness then, George Hans?
1
SPEAKER_02
It s like,
1
SPEAKER_02
What it seems to mean to people, it s just like a word that atheists use for souls.
1
SPEAKER_00
Sure, but that doesn t mean soul is not an interesting word.
1
SPEAKER_02
If consciousness is a spectrum, I m definitely way more conscious than the large language models are.
1
SPEAKER_02
I think the large language models are less conscious than a chicken.
2
SPEAKER_00
When is the last time you ve seen a chicken?
2
SPEAKER_01
In Miami, like a couple months ago.
2
SPEAKER_00
How, no, like a living chicken.
2
SPEAKER_01
Living chickens walking around Miami, it s crazy.
2
SPEAKER_00
Like on the street?
2
SPEAKER_01
Yeah.
2
SPEAKER_00
Like a chicken?
2
SPEAKER_01
A chicken, yeah.
2
SPEAKER_00
All right.
2
SPEAKER_00
All right, I was trying to call you all like a good journalist and I got shut down.
2
SPEAKER_00
Okay, but you don t,
2
SPEAKER_00
think much about this kind of subjective feeling that it feels like something to exist.
2
SPEAKER_00
And then as an observer, you can have a sense that an entity is not only intelligent, but has a kind of,
2
SPEAKER_00
subjective experience of its reality, like a self-awareness that is capable of like suffering, of hurting, of being excited by the environment in a way that s not merely kind of an artificial response, but a deeply felt one.
2
SPEAKER_01
Humans want to believe so much that if I took a rock and a sharpie and drew a sad face on the rock, they d think the rock is sad.
2
SPEAKER_00
Yeah, and you re saying when we look in the mirror we we apply the same smiley face with rock pretty much Yeah, doesn t it s not weird though that what you re not conscious that No
2
SPEAKER_00
But you do believe in consciousness.
2
SPEAKER_00
It s just, it s unclear.
2
SPEAKER_00
Okay, so to you it s like a little like a symptom of the bigger thing that s not that important.
2
SPEAKER_01
Yeah, I mean, it s interesting that like the human system seem to claim that they re conscious.
2
SPEAKER_01
And I guess it kind of like says something in a straight up like, okay, what do people mean when, even if you don t believe in consciousness, what do people mean when they say consciousness?
2
SPEAKER_01
And there s definitely like meanings to it.
2
SPEAKER_00
What s your favorite thing to eat?
2
SPEAKER_01
Pizza.
2
SPEAKER_00
Cheese pizza, what are the toppings?
2
SPEAKER_01
I like cheese pizza, I like pepperoni pizza.
2
SPEAKER_01
Don t say pineapple.
2
SPEAKER_01
No, I don t like pineapple.
2
SPEAKER_00
Okay.
2
SPEAKER_00
Pepperoni pizza.
2
SPEAKER_01
As they put any ham on it, oh, it s real bad.
2
SPEAKER_00
What s the best, what s the best pizza?
2
SPEAKER_00
What are we talking about here?
2
SPEAKER_00
Like, do you like cheap, crappy pizza?
2
SPEAKER_00
A Chicago deep dish cheese pizza, oh, that s my favorite.
2
SPEAKER_00
There you go, you bite into a deep dish, a Chicago deep dish pizza.
2
SPEAKER_00
and it feels like you were starving, you haven t eaten for 24 hours, you just bite in and you re hanging out with somebody that matters a lot to you and you re there with the pizza.
2
SPEAKER_00
Yeah, all right.
2
SPEAKER_00
It feels like something.
2
SPEAKER_00
I m George motherfucking Hotz eating a fucking Chicago deep dish pizza.
2
SPEAKER_00
There s just the full peak living experience of being human, the top of the human condition.
2
SPEAKER_00
It feels like something to experience that.
2
SPEAKER_00
Why does it feel like something?
2
SPEAKER_00
That s consciousness, isn t it?
2
SPEAKER_01
If that s the word you wanna use to describe it, sure.
2
SPEAKER_01
I m not gonna deny that that feeling exists.
2
SPEAKER_01
I m not gonna deny that I experience that feeling.
2
SPEAKER_01
I guess what I kind of take issue to is that there s some like, how does it feel to be a web server?
2
SPEAKER_01
Do 404s hurt?
2
SPEAKER_01
Not yet.
2
SPEAKER_01
How would you know what suffering looked like?
2
SPEAKER_01
Sure, you can recognize a suffering dog, because we re the same stack as the dog.
2
SPEAKER_01
All the bio stack stuff, especially mammals, it s really easy.
2
SPEAKER_01
Game recognizes game.
2
SPEAKER_01
Yeah.
2
SPEAKER_01
Versus the silicon stack stuff, it s like, you have no idea.
2
SPEAKER_01
Wow, the little thing has learned to mimic.
2
SPEAKER_01
but then I realized that that s all we are, too.
2
SPEAKER_01
Oh, look, the little thing has learned to mimic.
2
SPEAKER_00
Yeah, I guess, yeah, 404 could be suffering, but it s so far from our kind of living organism, our kind of stack, but it feels like AI can start maybe mimicking the biological stack better, better, better, because it s trained.
2
SPEAKER_00
Retrained it, yeah.
2
SPEAKER_00
And so in that, maybe that s the definition of consciousness, is the biostat consciousness.
2
SPEAKER_01
The definition of consciousness is how close something looks to human.
2
SPEAKER_01
Sure, I ll give you that one.
2
SPEAKER_00
No, how close something is to the human experience.
2
SPEAKER_01
Sure.
2
SPEAKER_01
It s a very anthropocentric definition, but.
2
SPEAKER_00
Well, that s all we got.
2
SPEAKER_01
Sure.
2
SPEAKER_01
No, and I don t mean to like, I think there s a lot of value in it.
2
SPEAKER_01
Look, I just started my second company.
2
SPEAKER_01
My third company will be AI Girlfriends.
2
SPEAKER_00
I wanna find out what your fourth company is after that.
2
SPEAKER_00
Because I think once you have AI girlfriends, it s, oh boy, does it get interesting.
2
SPEAKER_00
Well, maybe let s go there.
2
SPEAKER_00
I mean, the relationships with AI, that s creating human-like organisms, right?
2
SPEAKER_00
And part of being human is being conscious, is having the capacity to suffer, having the capacity to experience this life richly in such a way that you can empathize
2
SPEAKER_00
the AI system can empathize with you, and you can empathize with it.
2
SPEAKER_00
Or you can project your anthropomorphic sense of what the other entity is experiencing.
2
SPEAKER_00
And an AI model would need to, yeah, to create that experience inside your mind.
2
SPEAKER_00
And it doesn t seem that difficult.
2
SPEAKER_01
Yeah, but, okay, so here s where it actually gets totally different, right?
2
SPEAKER_01
When you interact with another human, you can make some assumptions.
2
SPEAKER_01
Yeah.
2
SPEAKER_01
When you interact with these models, you can t.
2
SPEAKER_01
You can make some assumptions that that other human experiences suffering and pleasure in a pretty similar way to you do.
2
SPEAKER_01
The golden rule applies.
2
SPEAKER_01
With an AI model, this isn t really true, right?
2
SPEAKER_01
These large language models are good at fooling people because they were trained on a whole bunch of human data and told to mimic it.
2
SPEAKER_00
Yeah.
2
SPEAKER_00
But if the AI system says, hi, my name is Samantha,
2
SPEAKER_00
It has a backstory.
2
SPEAKER_00
Went to college here and there.
2
SPEAKER_00
Maybe you ll integrate this in the AI system.
2
SPEAKER_01
I made some chatbots.
2
SPEAKER_01
I gave them backstories.
2
SPEAKER_01
It was lots of fun.
2
SPEAKER_01
I was so happy when Llama came out.
2
SPEAKER_00
Yeah, we ll talk about Llama.
2
SPEAKER_00
We ll talk about all that, but like, you know, the rock with the smiley face.
2
SPEAKER_00
Yeah.
2
SPEAKER_00
Well, it seems pretty natural for you to anthropomorphize that thing and then start dating it.
2
SPEAKER_00
And before you know it, you re married and have kids.
2
SPEAKER_00
With a rock.
2
SPEAKER_00
With a rock.
2
SPEAKER_00
There s pictures on Instagram with you and a rock and a smiley face.
2
SPEAKER_01
To be fair, like, you know, something that people generally look for when they re looking for someone to date is intelligence in some form.
2
SPEAKER_01
And the rock doesn t really have intelligence.
2
SPEAKER_01
Only a pretty desperate person would date a rock.
2
SPEAKER_01
I think we re all desperate deep down.
2
SPEAKER_01
Oh, not rock level desperate.
2
SPEAKER_00
All right.
2
SPEAKER_00
Not rock level desperate, but AI level desperate.
2
SPEAKER_00
I don t know, I think all of us have a deep loneliness.
2
SPEAKER_00
It just feels like the language models are there.
2
SPEAKER_01
Oh, I agree.
2
SPEAKER_01
And you know what?
2
SPEAKER_01
I won t even say this so cynically.
2
SPEAKER_01
I will actually say this in a way that, like, I want AI friends.
2
SPEAKER_01
I do.
2
SPEAKER_01
Yeah.
2
SPEAKER_01
Like, I would love to—you know, again, the language models now are still a little—like, people are impressed with these GPT things, and I look—or, like, the copilot, the coding one.
2
SPEAKER_01
And I m like, okay, this is, like, junior engineer level, and these people are, like, fiverr-level artists and copywriters.
2
SPEAKER_01
Like, okay, great, we got like Fiverr and like junior engineers, okay, cool.
2
SPEAKER_01
And this is just the start and it will get better, right?
2
SPEAKER_01
Like I can t wait to have AI friends who are more intelligent than I am.
2
SPEAKER_00
So Fiverr is just a temper, it s not the ceiling.
2
SPEAKER_00
No, definitely not.
2
SPEAKER_00
Is it count as cheating when you re talking to an AI model, emotional cheating?
2
SPEAKER_01
That s up to you and your human partner to define.
2
SPEAKER_00
Oh, you have to, all right.
2
SPEAKER_01
Yeah, you have to have that conversation, I guess.
2
SPEAKER_00
All right.
2
SPEAKER_00
I mean, integrate that with porn and all this kind of stuff.
2
SPEAKER_01
No, I mean, a similar kind of porn.
2
SPEAKER_00
Yeah.
2
Yeah.
2
SPEAKER_01
I think people in relationships have different views on that.
2
SPEAKER_00
Yeah, but most people don t have, like,
2
SPEAKER_00
serious open conversations about all the different aspects of what s cool and what s not.
2
SPEAKER_00
And it feels like AI is a really weird conversation to have.
2
SPEAKER_01
I mean, the porn one is a good branching off point.
2
SPEAKER_01
Like these things, you know, one of my scenarios that I put in my chatbot is a, you know, a nice girl named Lexi.
2
SPEAKER_01
She s 20.
2
SPEAKER_01
She just moved out to LA.
2
SPEAKER_01
She wanted to be an actress, but she started doing OnlyFans instead.
2
SPEAKER_01
And you re on a date with her.
2
SPEAKER_01
Enjoy.
2
SPEAKER_00
Oh man, yeah.
2
SPEAKER_00
And so is that, if you re actually dating somebody in real life, is that cheating?
2
SPEAKER_00
I feel like it gets a little weird.
2
SPEAKER_00
It gets real weird.
2
SPEAKER_00
It s like, what are you allowed to say to an AI bot?
2
SPEAKER_00
Imagine having that conversation with a significant other.
2
SPEAKER_01
I mean, these are all things for people to define in their relationships.
2
SPEAKER_01
What it means to be human is just gonna start to get weird.
2
SPEAKER_00
Especially online.
2
SPEAKER_00
Like, how do you know?
2
SPEAKER_00
Like, there ll be moments when you ll have what you think is a real human you interacted with on Twitter for years and you realize it s not.
2
SPEAKER_01
I spread I love this meme, uh, heaven banning.
2
SPEAKER_01
You know what?
2
SPEAKER_01
Shadow banning.
2
SPEAKER_00
Yeah.
2
SPEAKER_01
Shadow banning.
2
SPEAKER_01
Okay.
2
SPEAKER_01
You post, no one can see it.
2
SPEAKER_01
Heaven banning.
2
SPEAKER_01
You post, no one can see it, but a whole lot of AIs are spot up to interact with you.
2
SPEAKER_00
Well, maybe that s what the way human civilization ends is all of us are heaven-banned.
2
SPEAKER_01
There s a great, it s called My Little Pony Friendship is Optimal.
2
SPEAKER_01
It s a sci-fi story that explores this idea.
2
SPEAKER_00
Friendship is Optimal.
2
SPEAKER_01
Friendship is Optimal.
2
SPEAKER_00
Yeah, I d like to have some, at least on the intellectual realm, some AI friends that argue with me.
2
SPEAKER_00
But the romantic realm is weird, definitely weird.
2
SPEAKER_00
But,
2
SPEAKER_00
Not out of the realm of the kind of weirdness that human civilization is capable of, I think.
2
SPEAKER_01
I want it.
2
SPEAKER_01
Look, I want it.
2
SPEAKER_01
If no one else wants it, I want it.
2
SPEAKER_00
Yeah, I think a lot of people probably want it.
2
SPEAKER_00
There s a deep loneliness.
2
SPEAKER_01
And I ll fill their loneliness and, you know, just will only advertise to you some of the time.
2
SPEAKER_00
Yeah, maybe the conceptions of monogamy change too.
2
SPEAKER_00
Like I grew up in a time, like I value monogamy, but maybe that s a silly notion when you have arbitrary number of AI systems.
2
SPEAKER_01
This interesting path from rationality to polyamory, yeah, that doesn t make sense for me.
2
SPEAKER_00
For you, but you re just a biological organism who s born before like the internet really took off.
2
SPEAKER_01
The crazy thing is like,
2
SPEAKER_01
Culture is whatever we define it as, right?
2
SPEAKER_01
These things are not, like, is-ought problem in moral philosophy, right?
2
SPEAKER_01
There s no, like, okay, what is might be that, like, computers are capable of mimicking, you know, girlfriends perfectly.
2
SPEAKER_01
They passed the girlfriend-turning test, right?
2
SPEAKER_01
But that doesn t say anything about ought.
2
SPEAKER_01
That doesn t say anything about how we ought to respond to them as a civilization.
2
SPEAKER_01
That doesn t say we ought to get rid of monogamy, right?
2
SPEAKER_01
That s a completely separate question, really a religious one.
2
SPEAKER_00
Girlfriend Turing Test, I wonder what that looks like.
2
SPEAKER_00
Are you writing that?
2
SPEAKER_00
Will you be the Alan Turing of the 21st century that writes the Girlfriend Turing Test paper?
2
SPEAKER_01
No, I mean, of course, my AI girlfriends, their goal is to pass the Girlfriend Turing Test.
2
SPEAKER_00
No, but there should be like a paper that kind of defines the test.
2
SPEAKER_00
I mean, the question is if it s deeply personalized or there s a common thing that really gets everybody.
2
SPEAKER_01
Yeah, I mean, you know, look, we re a company, we don t have to get everybody, we just have to get a large enough clientele to stay with us.
2
SPEAKER_00
I like how you re already thinking company.
2
SPEAKER_00
All right, let s, before we go to company number three and company number four, let s go to company number two.
2
SPEAKER_01
Right.
2
SPEAKER_00
Tiny Corp.
2
SPEAKER_00
Possibly one of the greatest names of all time for a company.
2
SPEAKER_00
You ve launched a new company called Tiny Corp that leads the development of Tiny Grad.
2
SPEAKER_00
What s the origin story of Tiny Corp and Tiny Grad?
2
SPEAKER_01
I started tiny grad as like a toy project just to teach myself, okay, like what is a convolution?
2
SPEAKER_01
What are all these options you can pass to them?
2
SPEAKER_01
What is the derivative of a convolution, right?
2
SPEAKER_01
Very similar to Carpathia wrote micro grad, very similar.
2
SPEAKER_01
And then I started realizing, I started thinking about like AI chips.
2
SPEAKER_01
I started thinking about chips that run
2
SPEAKER_01
AI, and I was like, well, okay, this is going to be a really big problem.
2
SPEAKER_01
If NVIDIA becomes a monopoly here, how long before NVIDIA is nationalized?
2
SPEAKER_00
So you, one of the reasons to start TinyCorp is to challenge NVIDIA.
2
SPEAKER_01
It s not so much to challenge NVIDIA.
2
SPEAKER_01
Actually, I like NVIDIA.
2
SPEAKER_01
It s to make sure power stays decentralized.
2
Yeah.
2
SPEAKER_00
And here s a computational power.
2
SPEAKER_00
And to you, NVIDIA is kind of locking down the computational power of the world.
2
SPEAKER_01
If NVIDIA becomes just like 10x better than everything else, you re giving a big advantage to somebody who can secure NVIDIA as a resource.
2
SPEAKER_01
Yeah.
2
SPEAKER_01
In fact, if Jensen watches this podcast, he may wanna consider this.
2
SPEAKER_01
He may wanna consider making sure his company s not nationalized.
2
SPEAKER_00
Do you think that s an actual threat?
2
SPEAKER_01
Oh, yes.
2
SPEAKER_00
No, but there s so much, you know, there s AMD.
2
SPEAKER_01
Mm-hmm, so we have Nvidia and AMD, great.
2
SPEAKER_00
All right.
2
SPEAKER_00
But you don t think there s like a push towards like selling, like Google selling TPUs or something like this, you don t think there s a push for that?
2
SPEAKER_01
Have you seen it?
2
SPEAKER_01
Google loves to rent UTPUs.
2
SPEAKER_00
It doesn t, you can t buy it at Best Buy?
2
SPEAKER_00
No.
2
SPEAKER_01
So I started work on a
2
SPEAKER_01
I was like, okay, what s it going to take to make a chip?
2
SPEAKER_01
And my first notions were all completely wrong about why, about how you could improve on GPUs.
2
SPEAKER_01
And I will take this.
2
SPEAKER_01
This is from Jim Keller on your podcast.
2
SPEAKER_01
And this is one of my absolute favorite descriptions of computation.
2
SPEAKER_01
So there s three kinds of computation paradigms that are common in the world today.
2
SPEAKER_01
There s CPUs, and CPUs can do everything.
2
SPEAKER_01
CPUs can do add and multiply, they can do load and store, and they can do compare and branch.
2
SPEAKER_01
And when I say they can do these things, they can do them all fast, right?
2
SPEAKER_01
So compare and branch are unique to CPUs, and what I mean by they can do them fast is they can do things like branch prediction and speculative execution, and they spend tons of transistors on these like super deep reorder buffers in order to make these things fast.
2
SPEAKER_01
Then you have a simpler computation model, GPUs.
2
SPEAKER_01
GPUs can t really do compare and branch.
2
SPEAKER_01
I mean, they can, but it s horrendously slow.
2
SPEAKER_01
But GPUs can do arbitrary load and store.
2
SPEAKER_01
GPUs can do things like x dereference y. So they can fetch from arbitrary pieces of memory.
2
SPEAKER_01
They can fetch from memory that is defined by the contents of the data.
2
SPEAKER_01
The third model of computation is DSPs.
2
SPEAKER_01
And DSPs are just add and multiply.
2
SPEAKER_01
They can do load and stores, but only static load and stores, only loads and stores that are known before the program runs.
2
SPEAKER_01
And you look at neural networks today, and 95% of neural networks are all the DSP paradigm.
2
SPEAKER_01
They are just statically scheduled adds and multiplies.
2
SPEAKER_01
So TinyGuard really took this idea, and I m still working on it, to extend this as far as possible.
2
SPEAKER_01
Every stage of the stack has Turing completeness.
2
SPEAKER_01
Python has Turing completeness.
2
SPEAKER_01
And then we take Python, we go to C++, which is Turing complete.
2
SPEAKER_01
And maybe C++ calls into some CUDA kernels, which are Turing complete.
2
SPEAKER_01
The CUDA kernels go through LLVM, which is Turing complete, into PTX, which is Turing complete, to SAS, which is Turing complete, on a Turing complete processor.
2
SPEAKER_01
I want to get Turing completeness out of the stack entirely.
2
SPEAKER_01
Because once you get rid of Turing completeness, you can reason about things.
2
SPEAKER_01
Reisz s theorem and the halting problem do not apply to admiral machines.
2
SPEAKER_00
Out of, are we talking about the hardware or the software?
2
SPEAKER_01
Every layer of the stack.
2
SPEAKER_01
Every layer.
2
SPEAKER_01
Every layer of the stack, removing Turing completeness allows you to reason about things, right?
2
SPEAKER_01
So the reason you need to do branch prediction in a CPU, and the reason it s prediction, and the branch predictors are, I think they re like 99% on CPUs.
2
SPEAKER_01
Why do they get 1% of them wrong?
2
SPEAKER_01
Well, they get 1% wrong because you can t know.
2
SPEAKER_01
That s the halting problem.
2
SPEAKER_01
It s equivalent to the halting problem to say whether a branch is going to be taken or not.
2
SPEAKER_01
I can show that.
2
SPEAKER_01
But the AdMob machine, the neural network, runs the identical compute every time.
2
SPEAKER_01
The only thing that changes is the data.
2
SPEAKER_01
So when you realize this, you think about, okay, how can we build a computer?
2
SPEAKER_01
How can we build a stack that takes maximal advantage of this idea?
2
SPEAKER_01
So what makes TinyGrid different from other neural network libraries is it does not have a primitive operator, even for matrix multiplication.
2
SPEAKER_01
And this is every single one.
2
SPEAKER_01
They even have primitive operations for things like convolutions.
2
SPEAKER_00
So no matmul.
2
SPEAKER_00
No matmul.
2
SPEAKER_01
Well, here s what a matmul is.
2
SPEAKER_01
So I ll use my hands to talk here.
2
SPEAKER_01
So if you think about a cube, and I put my two matrices that I m multiplying,
3
SPEAKER_00
on two faces of the cube, right?
3
SPEAKER_00
You can think about the matrix multiply as, okay, the n cubed, I m going to multiply for each one in the cubed, and then I m going to do a sum, which is a reduce up to here to the third face of the cube, and that s your multiplied matrix.
3
SPEAKER_00
So what a matrix multiply is, is a bunch of shape operations, right?
3
SPEAKER_00
A bunch of permute three shapes and expands on the two matrices.
3
SPEAKER_00
A multiply n cubed, a reduce n cubed, which gives you an n squared matrix.
3
SPEAKER_01
Okay, so what is the minimum number of operations that can accomplish that if you don t have MatMol as a primitive?
3
SPEAKER_00
So TinyGrad has about 20.
3
SPEAKER_00
And you can compare TinyGrad s offset or IR to things like XLA or PrimTorch.
3
SPEAKER_00
So XLA and PrimTorch are ideas where like, okay, Torch has like 2000 different kernels.
3
SPEAKER_00
PyTorch 2.0 introduced PrimTorch, which has only 250.
3
SPEAKER_00
TinyGrad has order of magnitude 25.
3
SPEAKER_00
It s 10x less than XLA or PrimTorch.
3
SPEAKER_00
And you can think about it as kind of like RISC versus CISC, right?
3
SPEAKER_00
These other things are CISC-like systems.
3
SPEAKER_00
TinyGrad is RISC.
3
SPEAKER_01
And RISC won.
3
SPEAKER_00
RISC architecture is going to change everything.
3
SPEAKER_00
1995, hackers.
3
SPEAKER_01
Wait, really?
3
SPEAKER_01
That s an actual thing?
3
SPEAKER_00
Angelina Jolie delivers the line, risk architecture is going to change everything in 1995.
3
SPEAKER_00
Wow.
3
SPEAKER_00
And here we are with ARM in the phones.
3
SPEAKER_00
And ARM everywhere.
3
SPEAKER_01
Wow.
3
SPEAKER_01
I love it when movies actually have real things in them.
3
SPEAKER_01
Right?
3
SPEAKER_01
Okay, interesting.
3
SPEAKER_01
So this is like, so you re thinking of this as the risk architecture of ML stack.
3
SPEAKER_01
25 what what can you can you go through the?
3
SPEAKER_00
The four op types sure okay, so you have unary ops which take in a Tensor and return a tensor of the same size and do some unary op to it X log Reciprocal sign right they take in one and their point wise and
3
SPEAKER_01
Mm-hmm.
3
SPEAKER_01
ReLU.
3
SPEAKER_00
Yeah, ReLU.
3
SPEAKER_00
Almost all activation functions are unary ops.
3
SPEAKER_00
Some combinations of unary ops together is still a unary op.
3
SPEAKER_00
Then you have binary ops.
3
SPEAKER_00
Binary ops are like pointwise addition, multiplication, division, compare.
3
SPEAKER_00
It takes in two tensors of equal size and outputs one tensor.
3
SPEAKER_00
um then you have reduce ops reduce ops will like take a three-dimensional tensor and turn it into a two-dimensional tensor or a three-dimensional tensor turn into zero-dimensional tensor things like a sum or max are really the common ones there and then the fourth type is movement ops and movement ops are different from the other types because they don t actually require computation they require different ways to look at memory
3
SPEAKER_00
So that includes reshapes, permutes, expands, flips.
3
SPEAKER_00
Those are the main ones.
3
SPEAKER_01
And so with that you have enough to make a metmo.
3
SPEAKER_00
And convolutions.
3
SPEAKER_00
And every convolution you can imagine.
3
SPEAKER_00
Dilated convolutions, strided convolutions, transposed convolutions.
3
SPEAKER_01
You write on GitHub about laziness, showing a MatMul matrix multiplication.
3
SPEAKER_01
See how despite the style, it is fused into one kernel with the power of laziness.
3
SPEAKER_01
Can you elaborate on this power of laziness?
3
SPEAKER_00
Sure, so if you type in PyTorch A times B plus C, what this is going to do is it s going to first multiply A and B and store that result into memory.
3
SPEAKER_00
then it is going to add C by reading that result from memory, reading C from memory, and writing that out to memory.
3
SPEAKER_00
There is way more loads and stores to memory than you need there.
3
SPEAKER_00
If you don t actually do A times B as soon as you see it, if you wait,
3
SPEAKER_00
until the user actually realizes that tensor, until the laziness actually resolves, you can fuse that plus C. It s the same way Haskell works.
3
SPEAKER_00
So what s the process of porting a model into TinyGrad?
3
SPEAKER_00
So TinyGrad s front end looks very similar to PyTorch.
3
SPEAKER_00
I probably could make a perfect or pretty close to perfect interop layer if I really wanted to.
3
SPEAKER_00
I think that there s some things that are nicer about TinyGrad syntax than PyTorch, but the front end looks very Torch-like.
3
SPEAKER_00
You can also load in ONNX models.
3
SPEAKER_00
We have more ONNX tests passing than Core ML.
3
SPEAKER_00
We ll pass ONNX runtime soon.
3
SPEAKER_01
What about the developer experience with TinyGrad?
3
SPEAKER_01
What it feels like versus PyTorch?
3
SPEAKER_00
By the way, I really like PyTorch.
3
SPEAKER_00
I think that it s actually a very good piece of software.
3
SPEAKER_00
I think that they ve made a few different trade-offs, and these different trade-offs are where TinyGrad takes a different path.
3
SPEAKER_00
One of the biggest differences is it s really easy to see the kernels that are actually being sent to the GPU.
3
SPEAKER_00
Right?
3
SPEAKER_00
If you run PyTorch on the GPU, you do some operation, and you don t know what kernels ran.
3
SPEAKER_00
You don t know how many kernels ran.
3
SPEAKER_00
You don t know how many flops were used.
3
SPEAKER_00
You don t know how much memory accesses were used.
3
SPEAKER_00
TinyGrad type debug equals 2.
3
SPEAKER_00
And it will show you in this beautiful style every kernel that s run, how many flops, and how many bytes.
3
SPEAKER_01
So can you just linger on what problem TinyGrad solves?
3
SPEAKER_00
TinyGrad solves the problem of porting new ML accelerators quickly.
3
SPEAKER_00
One of the reasons — tons of these companies now, I think — Sequoia marked Graphcore to zero, right?
3
SPEAKER_00
Cerebus, Tenstorrent, Grok.
3
SPEAKER_00
all of these ML accelerator companies, they built chips.
3
SPEAKER_00
The chips were good.
3
SPEAKER_00
The software was terrible.
3
SPEAKER_00
And part of the reason is because I think the same problem is happening with Dojo.
3
SPEAKER_00
It s really, really hard to write a PyTorch port because you have to write 250 kernels and you have to tune them all for performance.
3
SPEAKER_01
What does Jim Culler think about TinyGrad?
3
SPEAKER_01
You guys hung out quite a bit, so he s, you know, he was involved, he s involved with Tenstorrent.
3
SPEAKER_01
Sure.
3
SPEAKER_01
What s his praise and what s his criticism of what you re doing with your life?
3
SPEAKER_00
Look, my prediction for Tenstorrent is that they re gonna pivot to making RISC-V chips.
3
SPEAKER_00
CPUs.
3
SPEAKER_01
CPUs.
3
SPEAKER_01
Yeah.
3
SPEAKER_01
Why?
3
SPEAKER_00
Because AI accelerators are a software problem, not really a hardware problem.
3
SPEAKER_01
Oh, interesting.
3
SPEAKER_01
So you don t think... You think the diversity of AI accelerators in the hardware space is not going to be a thing that exists long term?
3
SPEAKER_00
I think what s going to happen is if I can finish... Okay.
3
SPEAKER_00
If you re trying to make an AI accelerator,
3
SPEAKER_00
You better have the capability of writing a Torch-level performance stack on NVIDIA GPUs.
3
SPEAKER_00
If you can t write a Torch stack on NVIDIA GPUs, and I mean all the way, I mean down to the driver, there s no way you re going to be able to write it on your chip.
3
SPEAKER_00
Because your chip s worse than an NVIDIA GPU.
3
SPEAKER_00
The first version of the chip you tape out is definitely worse.
3
SPEAKER_01
Oh, you re saying writing that stack is really tough.
3
SPEAKER_00
Yes.
3
SPEAKER_00
And not only that, actually, the chip that you tape out, almost always because you re trying to get advantage over NVIDIA, you re specializing the hardware more.
3
SPEAKER_00
It s always harder to write software for more specialized hardware.
3
SPEAKER_00
Like a GPU is pretty generic.
3
SPEAKER_00
And if you can t write an NVIDIA stack, there s no way you can write a stack for your chip.
3
SPEAKER_00
So my approach with TinyGrad is, first, write a performant NVIDIA stack.
3
SPEAKER_00
We re targeting AMD.
3
SPEAKER_01
So you did say a few to NVIDIA a little bit.
3
SPEAKER_01
With love.
3
SPEAKER_00
With love.
3
SPEAKER_01
Yeah.
3
SPEAKER_00
With love.
3
SPEAKER_00
It s like the Yankees, you know?
3
SPEAKER_00
I m a Mets fan.
3
SPEAKER_01
Oh, you re a METS fan.
3
SPEAKER_01
A RISC fan and a METS fan.
3
SPEAKER_01
What s the hope that AMD has?
3
SPEAKER_01
You did a build with AMD recently that I saw.
3
SPEAKER_01
How does the 7900 XTX compare to the RTX 4090 or 4080?
3
SPEAKER_00
Well, let s start with the fact that the 7900 XTX kernel drivers don t work.
3
SPEAKER_00
And if you run demo apps in loops, it panics the kernel.
3
SPEAKER_01
Okay, so this is a software issue.
3
SPEAKER_00
Lisa Sue responded to my email.
3
SPEAKER_00
I reached out, I was like, this is, you know, really?
3
SPEAKER_00
Like, I understand if your seven by seven transposed Winograd conv is slower than Nvidia s, but literally when I run demo apps in a loop, the kernel panics.
3
SPEAKER_01
So just adding that loop.
3
SPEAKER_00
I just literally took their demo apps and wrote like while true semicolon do the app semicolon done in a bunch of screens.
3
SPEAKER_00
This is like the most primitive fuzz testing.
3
SPEAKER_01
Why do you think that is?
3
SPEAKER_01
They re just not seeing a market in machine learning?
3
SPEAKER_00
They re changing.
3
SPEAKER_00
They re trying to change.
3
SPEAKER_00
They re trying to change.
3
SPEAKER_00
And I had a pretty positive interaction with them this week.
3
SPEAKER_00
Last week, I went on YouTube.
3
SPEAKER_00
I was just like, that s it.
3
SPEAKER_00
I give up on AMD.
3
SPEAKER_00
Like, this is the, their driver doesn t even, like, I m not gonna, I m not gonna, you know, I ll go with Intel GPUs.
3
SPEAKER_00
Intel GPUs have better drivers.
3
SPEAKER_01
So you re kind of spearheading the diversification of GPUs.
3
SPEAKER_00
Yeah, and I d like to extend that diversification to everything.
3
SPEAKER_00
I d like to diversify the, right, the more, my central thesis about the world is there s things that centralize power and they re bad, and there s things that decentralize power and they re good.
3
SPEAKER_00
Everything I can do to help decentralize power, I d like to do.
3
SPEAKER_01
So you re really worried about the centralization of NVIDIA.
3
SPEAKER_01
That s interesting.
3
SPEAKER_01
And you don t have a fundamental hope for the proliferation of ASICs, except in the cloud.
3
SPEAKER_00
I d like to help them with software.
3
SPEAKER_00
No, actually, the only ASIC that is remotely successful is Google s TPU.
3
SPEAKER_00
And the only reason that s successful is because Google wrote a machine learning framework.
3
SPEAKER_00
I think that you have to write a competitive machine learning framework in order to be able to build an ASIC.
3
SPEAKER_01
You think Meta with PyTorch builds a competitor?
3
SPEAKER_01
I hope so.
3
SPEAKER_00
They have one.
3
SPEAKER_00
They have an internal one.
3
SPEAKER_01
Internal.
3
SPEAKER_01
I mean, public facing with a nice cloud interface and so on.
3
SPEAKER_00
I don t want a cloud.
3
SPEAKER_01
You don t like cloud?
3
SPEAKER_00
I don t like cloud.
3
SPEAKER_01
What do you think is the fundamental limitation of cloud?
3
SPEAKER_00
Fundamental limitation of cloud is who owns the off switch.
3
SPEAKER_01
So it s power to the people.
3
SPEAKER_00
Yeah.
3
SPEAKER_01
And you don t like the man to have all the power.
3
SPEAKER_00
Exactly.
3
SPEAKER_01
All right.
3
SPEAKER_01
And right now, the only way to do that is with NVIDIA GPUs if you want performance and stability.
3
SPEAKER_01
Interesting.
3
SPEAKER_01
It s a costly investment, emotionally, to go with AMDs.
3
SPEAKER_01
Well, let me add sort of on a tangent to ask you, you ve built quite a few PCs.
3
SPEAKER_01
What s your advice on how to build a good custom PC for, let s say, for the different applications that you use for gaming, for machine learning?
3
SPEAKER_00
Well, you shouldn t build one.
3
SPEAKER_00
You should buy a box from the tiny corp.
3
SPEAKER_01
I heard rumors, whispers about this box in the TinyCorp.
3
SPEAKER_01
What s this thing look like?
3
SPEAKER_01
What is it?
3
SPEAKER_01
What is it called?
3
SPEAKER_00
It s called the TinyBox.
3
SPEAKER_01
TinyBox?
3
SPEAKER_00
It s $15,000.
3
SPEAKER_00
And it s almost a paid a flop of compute.
3
SPEAKER_00
It s over 100 gigabytes of GPU RAM.
3
SPEAKER_00
It s over five terabytes per second of GPU memory bandwidth.
3
SPEAKER_00
I m going to put like four NVMEs in RAID.
3
SPEAKER_00
You re going to get like 20, 30 gigabytes per second of drive read bandwidth.
3
SPEAKER_00
I m going to build like the best deep learning box that I can that plugs into one wall outlet.
3
SPEAKER_01
Okay.
3
SPEAKER_01
Can you go through those specs again in a little bit from memory?
3
SPEAKER_00
Yeah.
3
SPEAKER_00
So it s almost a paid a flop of compute.
3
SPEAKER_00
So AMD Intel?
3
SPEAKER_00
Today, I m leaning toward AMD.
3
SPEAKER_00
But we re pretty agnostic to the type of compute.
3
SPEAKER_00
The main limiting spec is a 120 volt, 15 amp circuit.
3
SPEAKER_00
Well, I mean it, because in order to like, there s a plug over there, right?
3
SPEAKER_00
You have to be able to plug it in.
3
SPEAKER_00
We re also gonna sell the tiny rack, which like, what s the most power you can get into your house without arousing suspicion?
3
SPEAKER_00
And one of the answers is an electric car charger.
3
SPEAKER_01
Wait, where does the rack go?
3
SPEAKER_01
Your garage.
3
SPEAKER_01
Interesting.
3
SPEAKER_01
The car charger.
3
SPEAKER_00
A wall outlet is about 1,500 watts.
3
SPEAKER_00
A car charger is about 10,000 watts.
3
SPEAKER_01
What is the most amount of power you can get your hands on without arousing suspicion?
3
SPEAKER_01
That s right.
3
SPEAKER_01
George Haas.
3
SPEAKER_01
Okay.
3
SPEAKER_01
So the tiny box thing, you said NVMEs and RAID.
3
SPEAKER_01
I forget what you said about memory, all that kind of stuff.
3
SPEAKER_01
Okay.
3
SPEAKER_01
So what about with GPUs?
3
SPEAKER_00
Again, probably 7900 XTXs, but maybe 3090s, maybe a 770s.
3
SPEAKER_01
Those are Intel s.
3
SPEAKER_01
You re flexible or still exploring?
3
SPEAKER_00
I m still exploring.
3
SPEAKER_00
I want to deliver a really good experience to people.
3
SPEAKER_00
And yeah, what GPUs I end up going with, again, I m leaning toward AMD.
3
SPEAKER_00
We ll see.
3
SPEAKER_00
You know, in my email, what I said to AMD is like, just dumping the code on GitHub is not open source.
3
SPEAKER_00
Open source is a culture.
3
SPEAKER_00
Open source means that your issues are not all one-year-old stale issues.
3
SPEAKER_00
Open source means developing in public.
3
SPEAKER_00
And if you guys can commit to that, I see a real future for AMD as a competitor to Nvidia.
3
SPEAKER_01
Well, I d love to get a tiny box to MIT.
3
SPEAKER_01
So whenever it s ready, let s do it.
3
SPEAKER_00
We re taking pre-orders.
3
SPEAKER_00
I took this from Elon.
3
SPEAKER_00
I m like, $100 fully refundable pre-orders.
3
SPEAKER_01
Is it gonna be like the Cybertruck is gonna take a few years or?
3
SPEAKER_00
No, I ll try to do it faster.
3
SPEAKER_00
It s a lot simpler.
3
SPEAKER_00
It s a lot simpler than a truck.
3
SPEAKER_01
Well, there s complexities not to just the putting the thing together, but like shipping and all this kind of stuff.
3
SPEAKER_00
The thing that I wanna deliver to people out of the box is being able to run 65 billion parameter LLAMA in FP16 in real time, in like a good, like 10 tokens per second or five tokens per second or something.
3
SPEAKER_01
Just it works.
3
SPEAKER_01
Yep, just it works.
3
SPEAKER_01
LLAMA s running.
3
SPEAKER_01
Or something like Llama.
3
SPEAKER_00
Yeah, or I think Falcon is the new one.
3
SPEAKER_00
Experience a chat with the largest language model that you can have in your house.
3
SPEAKER_01
Yeah, from a wall plug.
3
SPEAKER_00
From a wall plug, yeah.
3
SPEAKER_00
Actually, for inference, it s not like even more power would help you get more.
3
SPEAKER_00
Even more power wouldn t get you more.
3
SPEAKER_00
Well, no, the biggest model released is 65 billion parameter Llama, as far as I know.
3
SPEAKER_01
So it sounds like Tiny Box will naturally pivot towards company number three, because you could just get the girlfriend, or boyfriend.
3
SPEAKER_00
That one s harder, actually.
3
SPEAKER_01
The boyfriend is harder?
3
SPEAKER_00
The boyfriend s harder, yeah.
3
SPEAKER_01
I think that s a very biased statement.
3
SPEAKER_01
I think a lot of people would disagree.
3
SPEAKER_01
Why is it harder to replace a boyfriend than a girlfriend with the artificial LLM?
3
SPEAKER_00
Because women are attracted to status and power, and men are attracted to youth and beauty.
3
SPEAKER_00
No, I mean, that s what I mean.
3
SPEAKER_01
Both are mimicable, easy through the language model.
3
SPEAKER_00
No, no machines do not have any status or real power.
3
SPEAKER_01
I don t know, I think you both, well, first of all, you re using language mostly to communicate youth and beauty and power and status.
3
SPEAKER_00
Sure, but status fundamentally is a zero-sum game, right, whereas youth and beauty are not.
3
SPEAKER_01
No, I think status is a narrative you can construct.
3
SPEAKER_01
I don t think status is real.
3
SPEAKER_00
I don t know, I just think that that s why it s harder.
3
SPEAKER_00
You know, yeah, maybe it is my biases.
3
SPEAKER_00
I think status is way easier to fake.
3
SPEAKER_00
I also think that, you know, men are probably more desperate and more likely to buy my product, so maybe they re a better target market.
3
SPEAKER_01
Desperation is interesting, easier to fool.
3
SPEAKER_01
Yeah.
3
SPEAKER_01
I could see that.
3
SPEAKER_00
Yeah, look, I mean, look, I know you can look at porn viewership numbers, right?
3
SPEAKER_00
A lot more men watch porn than women.
3
SPEAKER_00
Yeah.
3
SPEAKER_00
You can ask why that is.
3
SPEAKER_01
Wow, there s a lot of questions than answers you can get there.
3
SPEAKER_01
Anyway, with the TinyBox, how many GPUs in TinyBox?
3
SPEAKER_01
Six.
3
SPEAKER_00
Oh, man.
3
SPEAKER_00
And I ll tell you why it s six.
3
SPEAKER_00
So AMD Epyc processors have 128 lanes of PCIe.
3
SPEAKER_00
I want to leave enough lanes for some drives, and I want to leave enough lanes for some networking.
3
SPEAKER_01
How do you do cooling for something like this?
3
SPEAKER_00
Ah, that s one of the big challenges.
3
SPEAKER_00
Not only do I want the cooling to be good, I want it to be quiet.
3
SPEAKER_00
I want the tiny box to be able to sit comfortably in your room, right?
3
SPEAKER_01
This is really going towards the girlfriend thing.
3
SPEAKER_01
Because you want to run an LLM.
3
SPEAKER_00
I ll give a more, I mean, I can talk about how it relates to company number one.
3
SPEAKER_01
Call me AI.
3
SPEAKER_01
Yeah.
3
SPEAKER_01
Well, but yes, quiet.
3
SPEAKER_01
Oh, quiet, because you may be potentially want to run it in a car?
3
SPEAKER_00
No, no, quiet because you want to put this thing in your house, and you want it to coexist with you.
3
SPEAKER_00
If it s screaming at 60 dB, you don t want that in your house.
3
SPEAKER_00
You ll kick it out.
3
SPEAKER_01
60 dB, yeah.
3
SPEAKER_00
Yeah.
3
SPEAKER_00
I want like 40, 45.
3
SPEAKER_01
So how do you make the cooling quiet?
3
SPEAKER_01
That s an interesting problem in itself.
3
SPEAKER_00
A key trick is to actually make it big.
3
SPEAKER_00
Ironically, it s called the tiny box.
3
SPEAKER_01
Yeah.
3
SPEAKER_00
But if I can make it big, I m
4
SPEAKER_01
A lot of that noise is generated because of high-pressure air.
4
SPEAKER_01
If you look at a 1U server, a 1U server has these super high-pressure fans that are super deep, and they re like genesis.
4
SPEAKER_01
Versus if you have something that s big, well, I can use a big thing.
4
SPEAKER_01
They call them big-ass fans, those ones that are huge on the ceiling, and they re completely silent.
4
SPEAKER_00
So tiny box will be big.
4
SPEAKER_01
I do not want it to be large according to UPS.
4
SPEAKER_01
I want it to be shippable as a normal package, but that s my constraint there.
4
SPEAKER_00
Interesting.
4
SPEAKER_00
Well, the fans stuff, can t it be assembled on location, or no?
4
SPEAKER_00
No.
4
SPEAKER_00
Oh, it has to be.
4
SPEAKER_00
Wow.
4
SPEAKER_01
Look, I want to give you a great out-of-the-box experience.
4
SPEAKER_01
I want you to lift this thing out.
4
SPEAKER_01
I want it to be like the Mac, you know?
4
SPEAKER_01
Tiny Box.
4
SPEAKER_00
The Apple experience.
4
SPEAKER_01
Yeah.
4
SPEAKER_00
I love it.
4
SPEAKER_00
Okay.
4
SPEAKER_00
And so Tiny Box would run Tiny Grad.
4
SPEAKER_00
What do you envision this whole thing to look like?
4
SPEAKER_00
We re talking about, like,
4
SPEAKER_00
Linux with a full software engineering environment, and it s just not PyTorch, but TinyGrad.
4
SPEAKER_01
Yeah, we did a poll of people want Ubuntu or Arch.
4
SPEAKER_01
We re gonna stick with Ubuntu.
4
SPEAKER_00
Ooh, interesting.
4
SPEAKER_00
What s your favorite flavor of Linux?
4
SPEAKER_00
Ubuntu.
4
SPEAKER_00
Ubuntu.
4
SPEAKER_00
I like Ubuntu Mate, however you pronounce that, mate.
4
SPEAKER_00
So how do you, you ve gotten Lama into TinyGrad, you ve gotten stable diffusion into TinyGrad, what was that like?
4
SPEAKER_00
Can you comment on what are these models, what s interesting about porting them?
4
SPEAKER_00
What are the challenges, what s naturally, what s easy, all that kind of stuff.
4
SPEAKER_01
There s a really simple way to get these models into TinyGrad, and you can just export them as Onyx, and then TinyGrad can run Onyx.
4
SPEAKER_01
So the ports that I did of LLAMA, Stable Diffusion, and now Whisper are more academic to teach me about the models, but they are cleaner than the PyTorch versions.
4
SPEAKER_01
You can read the code.
4
SPEAKER_01
I think the code is easier to read.
4
SPEAKER_01
It s less lines.
4
SPEAKER_01
There s just a few things about the way TinyGrid writes things.
4
SPEAKER_01
Here s a complaint I have about PyTorch.
4
SPEAKER_01
Nn.relu is a class.
4
SPEAKER_01
So when you create an Nn module, you ll put your Nn.relus in an int.
4
SPEAKER_01
And this makes no sense, Relu is completely stateless.
4
SPEAKER_01
Why should that be a class?
4
SPEAKER_00
But that s more like a software engineering thing.
4
SPEAKER_00
Or do you think it has a cost on performance?
4
SPEAKER_01
Oh no, it doesn t have a cost on performance.
4
SPEAKER_01
But yeah, no, I think that it s... That s what I mean about TinyGrad s front end being cleaner.
4
SPEAKER_00
I see.
4
SPEAKER_00
What do you think about Mojo?
4
SPEAKER_00
I don t know if you ve been paying attention to the programming language that does some interesting ideas that kind of intersect TinyGrad.
4
SPEAKER_01
I think that there is a spectrum and like on one side you have Mojo and on the other side you have like GGML.
4
SPEAKER_01
GGML is this like we re going to run Llama fast on Mac.
4
SPEAKER_01
And okay, we re gonna expand out to a little bit, but we re gonna basically go like depth first, right?
4
SPEAKER_01
Mojo was like, we re gonna go breadth first.
4
SPEAKER_01
We re gonna go so wide that we re gonna make all of Python fast, and TinyGrad s in the middle.
4
SPEAKER_01
TinyGrad is, we are going to make neural networks fast.
4
SPEAKER_00
Yeah, but they try to really get it to be fast, compiled down to specifics hardware, and make that compilation step
4
SPEAKER_00
as flexible and resilient as possible.
4
SPEAKER_00
And that limits you.
4
SPEAKER_00
That s what you re seeing, it s somewhere in the middle.
4
SPEAKER_00
So you re actually going to be targeting some accelerators, like some number, not one.
4
SPEAKER_01
My goal is step one, build an equally performance stack to PyTorch on NVIDIA and AMD, but with way less lines.
4
SPEAKER_01
And then step two is, okay, how do we make an accelerator?
4
SPEAKER_01
But you need step one.
4
SPEAKER_01
You have to first build the framework before you can build the accelerator.
4
SPEAKER_00
Can you explain MLPerf?
4
SPEAKER_00
What s your approach in general to benchmarking tiny grad performance?
4
SPEAKER_01
I m much more of a, like, build it the right way and worry about performance later.
4
SPEAKER_01
There s a bunch of things where I haven t even, like, really dove into performance.
4
SPEAKER_01
The only place where TinyGrad is competitive performance-wise right now is on Qualcomm GPUs.
4
SPEAKER_01
So TinyGrad s actually used in OpenPilot to run the model.
4
SPEAKER_01
So the driving model is TinyGrad.
4
SPEAKER_01
When did that happen, that transition?
4
SPEAKER_01
About eight months ago now.
4
SPEAKER_01
And it s 2x faster than Qualcomm s library.
4
SPEAKER_00
What s the hardware that OpenPilot runs on the Kamiya?
4
SPEAKER_00
It s a Snapdragon 845.
4
SPEAKER_01
Okay.
4
SPEAKER_01
So this is using the GPU.
4
SPEAKER_01
So the GPU is an Adreno GPU.
4
SPEAKER_01
There s like different things.
4
SPEAKER_01
There s a really good Microsoft paper that talks about like mobile GPUs and why they re different from desktop GPUs.
4
SPEAKER_01
One of the big things is in a desktop GPU, you can use buffers.
4
SPEAKER_01
On a mobile GPU, image textures are a lot faster.
4
SPEAKER_00
and a mobile GPU image textures and image, okay.
4
SPEAKER_00
And so you want to be able to leverage that.
4
SPEAKER_01
I want to be able to leverage it in a way that it s completely generic, right?
4
SPEAKER_01
So there s a lot of, there s, Xiaomi has a pretty good open source library for mobile GPUs called Mace, where they can generate, where they have these kernels, but they re all hand coded, right?
4
SPEAKER_01
So that s great if you re doing three by three comps, that s great if you re doing dense map models, but the minute you go off the beaten path a tiny bit, well, your performance is nothing.
4
SPEAKER_00
Since you mentioned OpenPILOT, I d love to get an update in the company number one, CalmAI world.
4
SPEAKER_00
How are things going there in the development of semi-autonomous driving?
4
SPEAKER_01
You know, almost no one talks about FSD anymore, and even less people talk about OpenPILOT.
4
SPEAKER_01
We ve solved the problem, like we solved it years ago.
4
SPEAKER_00
What s the problem exactly?
4
SPEAKER_00
Like, what does solving it mean?
4
SPEAKER_01
Solving means how do you build a model that outputs a human policy for driving?
4
SPEAKER_01
How do you build a model that, given a reasonable set of sensors, outputs a human policy for driving?
4
SPEAKER_01
So you have companies like Waymo and Cruise, which are hand-coding these things that are like quasi-human policies.
4
SPEAKER_01
Then you have Tesla, and maybe even to more of an extent Kama, asking, OK, how do we just learn the human policy from data?
4
SPEAKER_01
the big thing that we re doing now and we just put it out on twitter at the beginning of comma we published a paper called learning a driving simulator and the way this thing worked was it s a it was an auto encoder and then an rnn in the middle
4
SPEAKER_01
Right, you take an autoencoder, you compress the picture, you use an RNN, predict the next state, and these things were, you know, it was a laughably bad simulator.
4
SPEAKER_01
This is 2015 era machine learning technology.
4
SPEAKER_01
Today, we have VQVAE and transformers.
4
SPEAKER_01
We re building DriveGPT, basically.
4
SPEAKER_00
DriveGPT, okay.
4
SPEAKER_00
So, and it s trained on what?
4
SPEAKER_00
Is it trained in a self-supervised way?
4
SPEAKER_01
Yeah, it s trained on all the driving data to predict the next frame.
4
SPEAKER_00
So really trying to learn a human policy.
4
SPEAKER_00
What would a human do?
4
SPEAKER_01
Well, actually our simulator s conditioned on the pose.
4
SPEAKER_01
So it s actually a simulator.
4
SPEAKER_01
You can put in like a state action pair and get out the next state.
4
SPEAKER_01
Okay.
4
SPEAKER_01
And then once you have a simulator, you can do RL in the simulator and RL will get us that human policy.
4
SPEAKER_00
So it transfers.
4
SPEAKER_01
Yeah.
4
SPEAKER_01
RL with a reward function, not asking, is this close to the human policy, but asking, would a human disengage if you did this behavior?
4
SPEAKER_00
Okay, let me think about the distinction there.
4
SPEAKER_00
Would a human disengage?
4
SPEAKER_00
Would a human disengage?
4
SPEAKER_00
That correlates, I guess, with human policy, but it could be different.
4
SPEAKER_00
So it doesn t just say, what would a human do?
4
SPEAKER_00
It says, what would a good human driver do?
4
SPEAKER_00
And such that the experience is comfortable, but also not annoying in that the thing is very cautious.
4
SPEAKER_00
So it s finding a nice balance.
4
SPEAKER_00
That s interesting.
4
SPEAKER_01
It s a nice- It s asking exactly the right question.
4
SPEAKER_01
What will make our customers happy?
4
SPEAKER_00
Right.
4
SPEAKER_01
A system that you never want to disengage.
4
SPEAKER_00
Because usually disengagement is almost always a sign of I m not happy with what the system is doing.
4
SPEAKER_01
Usually.
4
SPEAKER_01
There s some that are just, I felt like driving, and those are always fine too, but they re just going to look like noise in the data.
4
SPEAKER_00
But even I felt like driving,
4
SPEAKER_01
Maybe, yeah.
4
SPEAKER_00
Even that s a signal, like why do you feel like driving?
4
SPEAKER_00
You need to recalibrate your relationship with the car.
4
SPEAKER_00
Okay, so that s really interesting.
4
SPEAKER_00
How close are we to solving self-driving?
4
SPEAKER_01
It s hard to say.
4
SPEAKER_01
We haven t completely closed the loop yet.
4
SPEAKER_01
So we don t have anything built that truly looks like that architecture yet.
4
SPEAKER_01
We have prototypes and there s bugs.
4
SPEAKER_01
So we are a couple bug fixes away.
4
SPEAKER_01
Might take a year, might take 10.
4
SPEAKER_00
What s the nature of the bugs?
4
SPEAKER_00
Are these major philosophical bugs, logical bugs?
4
SPEAKER_00
What kind of bugs are we talking about?
4
SPEAKER_01
They re just like stupid bugs and also we might just need more scale.
4
SPEAKER_01
We just massively expanded our compute cluster at Comma.
4
SPEAKER_01
We now have about two people worth of compute, 40 petaflops.
4
SPEAKER_00
Well, people, people are different.
4
SPEAKER_01
Eh, 20 feet of flops.
4
SPEAKER_01
That s a person.
4
SPEAKER_01
It s just a unit, right?
4
SPEAKER_01
Horses are different too, but we still call it a horsepower.
4
SPEAKER_00
Yeah, but there s something different about mobility than there is about perception and action in a very complicated world.
4
SPEAKER_00
But yes.
4
SPEAKER_01
Well, yeah, of course.
4
SPEAKER_01
Not all flops are created equal.
4
SPEAKER_01
If you have randomly initialized weights, it s not gonna... Not all flops are created equal.
4
SPEAKER_02
Some flops are doing way more useful things than others.
4
SPEAKER_00
Yeah, yeah.
4
SPEAKER_00
Tell me about it.
4
SPEAKER_00
Okay, so more data.
4
SPEAKER_00
Scale means more scale in compute or scale in scale of data?
4
SPEAKER_00
Both.
4
SPEAKER_00
Diversity of data?
4
SPEAKER_01
Diversity is very important in data.
4
SPEAKER_01
Yeah, I mean, we have, so we have about, I think we have like 5,000 daily actives.
4
SPEAKER_00
How would you evaluate how FSD is doing?
4
SPEAKER_00
For self-driving?
4
SPEAKER_00
How s that race going between CalmAI and FSD?
4
SPEAKER_01
Tesla is always one to two years ahead of us.
4
SPEAKER_01
They ve always been one to two years ahead of us.
4
SPEAKER_01
And they probably always will be because they re not doing anything wrong.
4
SPEAKER_00
What have you seen since the last time we talked that are interesting architectural decisions, training decisions, like the way they deploy stuff, the architectures they re using in terms of the software, how the teams are run, all that kind of stuff, data collection, anything interesting?
4
SPEAKER_01
I mean, I know they re moving toward more of an end-to-end approach.
4
SPEAKER_00
So creeping towards end-to-end as much as possible across the whole thing, the training, the data collection, everything.
4
SPEAKER_01
They also have a very fancy simulator.
4
SPEAKER_01
They re probably saying all the same things we are.
4
SPEAKER_01
They re probably saying we just need to optimize what is the reward.
4
SPEAKER_01
We get negative reward for disengagement.
4
SPEAKER_01
Everyone kind of knows this.
4
SPEAKER_01
It s just a question of who can actually build and deploy the system.
4
SPEAKER_00
Yeah, I mean, it requires good software engineering, I think.
4
SPEAKER_00
And the right kind of hardware.
4
SPEAKER_01
Yeah, and the hardware to run it.
4
SPEAKER_00
You still don t believe in cloud in that regard?
4
SPEAKER_01
I have a compute cluster in my office, 800 amps.
4
SPEAKER_00
Tiny grad.
4
SPEAKER_01
It s 40 kilowatts at idle, our data center.
4
SPEAKER_01
Diving crazy.
4
SPEAKER_01
We have 40 kilowatts just burning just when the computers are idle.
4
SPEAKER_01
Sorry, sorry, compute cluster.
4
SPEAKER_01
Compute cluster, I got it.
4
SPEAKER_01
It s not a data center.
4
SPEAKER_00
Yeah, yeah.
4
SPEAKER_01
No, data centers are clouds.
4
SPEAKER_01
We don t have clouds.
4
SPEAKER_01
Data centers have air conditioners.
4
SPEAKER_01
We have fans.
4
SPEAKER_01
That makes it a compute cluster.
4
SPEAKER_00
I m guessing this is a kind of a legal distinction.
4
SPEAKER_00
Sure, yeah.
4
SPEAKER_02
We have a compute cluster.
4
SPEAKER_00
You said that you don t think LLMs have consciousness, or at least not more than a chicken.
4
SPEAKER_00
do you think they can reason?
4
SPEAKER_00
Is there something interesting to you about the word reason, about some of the capabilities that we think is kind of human?
4
SPEAKER_00
To be able to integrate complicated information and through a chain of thought arrive at a conclusion that feels novel, a novel integration of disparate facts.
4
SPEAKER_01
Yeah, I don t think that there s, I think that I can reason better than a lot of people.
4
SPEAKER_00
Yeah, isn t that amazing to you though?
4
SPEAKER_00
Isn t that like an incredible thing that a transformer could achieve?
4
SPEAKER_01
I mean, I think that calculators can add better than a lot of people.
4
SPEAKER_00
But language feels like reasoning through the process of language, which looks a lot like thought.
4
SPEAKER_01
making brilliancies in chess, which feels a lot like thought.
4
SPEAKER_01
Whatever new thing that AI can do, everybody thinks is brilliant.
4
SPEAKER_01
And then, like, 20 years go by, and they re like, well, yeah, but chess, that s, like, mechanical.
4
SPEAKER_01
Like, adding, that s, like, mechanical.
4
SPEAKER_00
So you think language is not that special.
4
SPEAKER_00
It s like chess.
4
SPEAKER_00
It s like chess and it s like.
4
SPEAKER_00
I don t know, because it s very human, we take it, listen, there is something different between chess and language.
4
SPEAKER_00
Chess is a game that a subset of population plays.
4
SPEAKER_00
Language is something we use nonstop for all of our human interaction, and human interaction is fundamental to society.
4
SPEAKER_00
So it s like, holy shit, this,
4
SPEAKER_00
This language thing is not so difficult to create in a machine.
4
SPEAKER_01
The problem is if you go back to 1960 and you tell them that you have a machine that can play amazing chess, of course someone in 1960 will tell you that machine is intelligent.
4
SPEAKER_01
Someone in 2010 won t.
4
SPEAKER_01
What s changed, right?
4
SPEAKER_01
Today we think that these machines that have language are intelligent, but I think in 20 years we re going to be like, yeah, but can it reproduce?
4
SPEAKER_00
So reproduction, yeah, we may redefine what it means to be, what is it, a high performance living organism on earth.
4
SPEAKER_01
Humans are always gonna define a niche for themselves.
4
SPEAKER_01
Like, well, you know, we re better than the machines because we can, you know, and like they tried creative for a bit, but no one believes that one anymore.
4
SPEAKER_00
But is that delusional or is there some accuracy to that?
4
SPEAKER_00
Because maybe with chess you start to realize that we have ill-conceived notions of what makes humans special, like the apex organism on Earth.
4
SPEAKER_01
Yeah, and I think maybe we re gonna go through that same thing with language.
4
SPEAKER_01
And that same thing with creativity.
4
SPEAKER_00
But language carries these notions of truth and so on.
4
SPEAKER_00
And so we might be like, wait, maybe truth is not carried by language.
4
SPEAKER_00
Maybe there s like a deeper thing.
4
SPEAKER_02
The niche is getting smaller.
4
SPEAKER_02
Oh boy.
4
SPEAKER_02
But no, no, no, you don t understand.
4
SPEAKER_02
Humans are created by God and machines are created by humans.
4
SPEAKER_02
Therefore, right?
4
SPEAKER_01
Like that ll be the last niche we have.
4
SPEAKER_00
So what do you think about this, the rapid development of LLMs?
4
SPEAKER_00
If we could just stick on that.
4
SPEAKER_00
It s still incredibly impressive, like with ChagGPT.
4
SPEAKER_00
Just even ChagGPT, what are your thoughts about reinforcement learning with human feedback on these large language models?
4
SPEAKER_01
I d like to go back to when calculators first came out, or computers.
4
SPEAKER_01
And I wasn t around.
4
SPEAKER_01
Look, I m 33 years old.
4
SPEAKER_01
And to see how that affected
4
SPEAKER_01
like society.
4
SPEAKER_00
Maybe you re right.
4
SPEAKER_00
So I want to put on the big picture hat here.
4
SPEAKER_00
Oh my god, a refrigerator?
4
SPEAKER_00
Wow.
4
SPEAKER_00
Refrigerator, electricity, all that kind of stuff.
4
SPEAKER_00
But no, with the internet, large language models seeming human-like, basically passing a Turing test,
4
SPEAKER_00
It seems it might have really, at scale, rapid transformative effects on society.
4
SPEAKER_00
But you re saying other technologies have as well.
4
SPEAKER_00
So maybe calculator s not the best example of that?
4
SPEAKER_00
Because that just seems like, well, no, maybe.
4
SPEAKER_00
Calculator.
4
SPEAKER_01
But the poor milk man, the day he learned about refrigerators, he s like, I m done.
4
SPEAKER_01
You re telling me you can just keep the milk in your house?
4
SPEAKER_02
You don t need me to deliver it every day?
4
SPEAKER_02
I m done.
4
SPEAKER_00
Well, yeah, you have to actually look at the practical impacts of certain technologies that they ve had.
4
SPEAKER_00
Yeah, probably electricity s a big one, and also how rapidly it s spread.
4
SPEAKER_00
Man, the internet is a big one.
4
SPEAKER_01
I do think it s different this time, though.
4
SPEAKER_01
Yeah, it just feels like stuff- The niche is getting smaller.
4
SPEAKER_00
The niche is humans.
4
SPEAKER_00
Yes.
4
SPEAKER_00
That makes humans special.
4
SPEAKER_00
Yes.
4
SPEAKER_00
It feels like it s getting smaller rapidly, though, doesn t it?
4
SPEAKER_00
Or is that just a feeling we dramatize everything?
4
SPEAKER_01
I think we dramatize everything.
4
SPEAKER_01
I think that you ask the milkman when he saw refrigerators, and they re going to have one of these in every home?
4
SPEAKER_00
Yeah, yeah, yeah.
4
SPEAKER_00
Yeah, but boys are impressive.
4
SPEAKER_00
So much more impressive than seeing a chess world champion AI system.
4
SPEAKER_00
I disagree.
5
SPEAKER_01
actually.
5
SPEAKER_01
I disagree.
5
SPEAKER_01
I think things like mu zero and alpha go are so much more impressive because these things are playing beyond the highest human level.
5
SPEAKER_01
The language models are writing middle school level essays and people are like, wow, it s a great essay.
5
SPEAKER_01
It s a great five paragraph essay about the causes of the civil war.
5
SPEAKER_00
Okay, forget the civil war, just generating code, codex.
5
SPEAKER_00
Oh.
5
SPEAKER_00
So you re saying it s mediocre code.
5
SPEAKER_00
Terrible.
5
SPEAKER_00
But I don t think it s terrible.
5
SPEAKER_00
I think it s just mediocre code.
5
SPEAKER_00
Yeah.
5
SPEAKER_00
Often close to correct.
5
SPEAKER_00
like for mediocre purposes.
5
SPEAKER_01
That s the scariest kind of code.
5
SPEAKER_01
I spend 5% of time typing and 95% of time debugging.
5
SPEAKER_01
The last thing I want is close to correct code.
5
SPEAKER_01
I want a machine that can help me with the debugging, not with the typing.
5
SPEAKER_00
You know, it s like L2, level two driving, similar kind of thing.
5
SPEAKER_00
Yeah, you still should be a good programmer in order to modify.
5
SPEAKER_00
I wouldn t even say debugging, it s just modifying the code, reading it.
5
SPEAKER_01
I actually don t think it s like level two driving.
5
SPEAKER_01
I think driving is not tool complete, and programming is.
5
SPEAKER_01
Meaning you don t use the best possible tools to drive.
5
SPEAKER_01
Cars have basically the same interface for the last 50 years.
5
SPEAKER_01
Computers have a radically different interface.
5
SPEAKER_00
OK, can you describe the concept of tool complete?
5
SPEAKER_01
So think about the difference between a car from 1980 and a car from today.
5
SPEAKER_01
No difference, really.
5
SPEAKER_01
It s got a bunch of pedals.
5
SPEAKER_01
It s got a steering wheel.
5
SPEAKER_01
Maybe now it has a few ADAS features, but it s pretty much the same car.
5
SPEAKER_01
You have no problem getting into a 1980 car and driving it.
5
SPEAKER_01
Take a programmer today who spent their whole life doing JavaScript, and you put him in an Apple IIe prompt, and you tell him about the line numbers in BASIC.
5
SPEAKER_01
Wait, but how do I insert something between line 17 and 18?
5
SPEAKER_01
Oh, wow.
5
SPEAKER_00
But the, so in tool, you re putting in the programming languages.
5
SPEAKER_00
So it s just the entirety stack of the tooling.
5
SPEAKER_00
So it s not just like the IDs or something like this, it s everything.
5
SPEAKER_01
Yes, it s IDEs, the languages, the runtimes, it s everything.
5
SPEAKER_01
And programming is tool complete.
5
SPEAKER_01
So like almost if Codex or Copilot are helping you, that actually probably means that your framework or library is bad, and there s too much boilerplate in it.
5
SPEAKER_00
Yeah, but don t you think so much programming has boilerplate?
5
SPEAKER_01
TinyGrad is now 2,700 lines, and it can run LLAMA and stable diffusion, and all of this stuff is in 2,700 lines.
5
SPEAKER_01
Boilerplate and abstraction indirections and all these things are just bad code.
5
SPEAKER_00
Well, let s talk about good code and bad code.
5
SPEAKER_00
I would say, I don t know, for generic scripts that I write just offhand, like 80% of it is written by GPT.
5
SPEAKER_00
Just like quick offhand stuff.
5
SPEAKER_00
So not like libraries, not like performing code, not stuff for robotics and so on, just quick stuff.
5
SPEAKER_00
Because your basics, so much of programming is doing some, yeah, boilerplate, but to do so efficiently and quickly,
5
SPEAKER_00
because you can t really automate it fully with like generic method, like a generic kind of ID type of recommendation or something like this.
5
SPEAKER_00
You do need to have some of the complexity of language models.
5
SPEAKER_01
Yeah, I guess if I was really writing, like, maybe today, if I wrote, like, a lot of, like, data parsing stuff.
5
SPEAKER_01
I mean, I don t play CTFs anymore, but if I still played CTFs, a lot of the life is just, like, you have to write, like, a parser for this data format.
5
SPEAKER_01
Like, I wonder—or, like, admin of code.
5
SPEAKER_01
I wonder when the models are going to start to help with that kind of code.
5
SPEAKER_01
And they may.
5
SPEAKER_01
They may.
5
SPEAKER_01
And the models also may help you with speed.
5
SPEAKER_01
The models are very fast.
5
SPEAKER_01
But where the models won t, my programming speed is not at all limited by my typing speed.
5
SPEAKER_01
And in very few cases it is, yes.
5
SPEAKER_01
If I m writing some script to just like parse some weird data format, sure, my programming speed is limited by my typing speed.
5
SPEAKER_00
What about looking stuff up?
5
SPEAKER_00
Because that s essentially a more efficient lookup, right?
5
SPEAKER_01
You know,
5
SPEAKER_01
When I was at Twitter, I tried to use ChatGPT to ask some questions, like, what s the API for this?
5
SPEAKER_01
And it would just hallucinate.
5
SPEAKER_01
It would just give me completely made up API functions that sounded real.
5
SPEAKER_00
Well, do you think that s just a temporary kind of stage?
5
SPEAKER_00
No.
5
SPEAKER_00
you don t think it ll get better and better and better in this kind of stuff?
5
SPEAKER_00
Because it only hallucinates stuff in the edge cases.
5
SPEAKER_01
If you re writing generic code, it s actually pretty good.
5
SPEAKER_01
Yes.
5
SPEAKER_01
If you are writing an absolute basic React app with a button, it s not going to hallucinate.
5
SPEAKER_01
Sure.
5
SPEAKER_01
No, there s kind of ways to fix the hallucination problem.
5
SPEAKER_01
I think Facebook has an interesting paper.
5
SPEAKER_01
It s called Atlas.
5
SPEAKER_01
And it s actually weird the way that we do language models right now where all of the information is in the weights.
5
SPEAKER_01
And human brains don t really like this.
5
SPEAKER_01
It s like a hippocampus and a memory system.
5
SPEAKER_01
So why don t LLMs have a memory system?
5
SPEAKER_01
And there s people working on them.
5
SPEAKER_01
I think future LLMs are going to be smaller, but are going to run looping on themselves and are going to have retrieval systems.
5
SPEAKER_01
And the thing about using a retrieval system is you can cite sources explicitly.
5
SPEAKER_00
Which is really helpful to integrate the human into the loop of the thing, because you can go check the sources and you can investigate.
5
SPEAKER_00
So whenever the thing is hallucinating, you can have the human supervision.
5
SPEAKER_00
So that s pushing it towards level two kind of direction.
5
SPEAKER_01
That s gonna kill Google.
5
SPEAKER_00
Wait, which part?
5
SPEAKER_01
When someone makes an LLM that s capable of citing its sources, it will kill Google.
5
SPEAKER_00
An alum that s citing his sources because that s basically a search engine.
5
SPEAKER_01
That s what people want in a search engine.
5
SPEAKER_00
But also Google might be the people that build it.
5
SPEAKER_01
Maybe.
5
SPEAKER_00
And put ads on it.
5
SPEAKER_01
I d count them out.
5
SPEAKER_00
Why is that, why do you think?
5
SPEAKER_00
Who wins this race?
5
SPEAKER_00
Who are the competitors?
5
SPEAKER_00
We got Tiny Corp, I don t know if that s, yeah, I mean, you re a legitimate competitor in that.
5
SPEAKER_01
I m not trying to compete on that.
5
SPEAKER_00
You re not.
5
SPEAKER_00
No, not as a speaker.
5
SPEAKER_00
You can accidentally stumble into that competition.
5
SPEAKER_01
Maybe.
5
SPEAKER_00
You don t think you might build a search engine to replace Google search?
5
SPEAKER_01
When I started Comma, I said over and over again, I m going to win self-driving cars.
5
SPEAKER_01
I still believe that.
5
SPEAKER_01
I have never said I m going to win search with the TinyCorp, and I m never going to say that because I won t.
5
SPEAKER_00
the night is still young.
5
SPEAKER_00
We don t, you don t know how hard is it to win search in this new, like it s, it feels, I mean, one of the things that ChatterGPT kind of shows that there could be a few interesting tricks that really have, that create a really compelling product.
5
SPEAKER_01
Some startup s gonna figure it out.
5
SPEAKER_01
I think, I think if you ask me, like Google s still the number one webpage, I think by the end of the decade, Google won t be the number one webpage anymore.
5
SPEAKER_00
So you don t think Google, because of the, how big the corporation is?
5
SPEAKER_01
Look, I would put a lot more money on Mark Zuckerberg.
5
SPEAKER_00
Why is that?
5
SPEAKER_01
Because Mark Zuckerberg s alive.
5
SPEAKER_01
This is old Paul Graham essay.
5
SPEAKER_01
Startups are either alive or dead.
5
SPEAKER_01
Google s dead.
5
SPEAKER_00
Facebook s alive.
5
SPEAKER_00
Versus Facebook is alive, Meta is alive.
5
SPEAKER_01
Actually, Meta.
5
SPEAKER_00
Meta.
5
SPEAKER_01
You see what I mean?
5
SPEAKER_01
That s just, Mark Zuckerberg, this is Mark Zuckerberg reading that Paul Graham essay and being like, I m gonna show everyone how alive we are.
5
SPEAKER_01
I m gonna change the name.
5
SPEAKER_00
So you don t think there s this gutsy pivoting engine
5
SPEAKER_00
that Google doesn t have that, the kind of engine that a startup has constantly being alive, I guess.
5
SPEAKER_01
When I listened to your Sam Altman podcast, he talked about the button.
5
SPEAKER_01
Everyone who talks about AI talks about the button, the button to turn it off, right?
5
SPEAKER_01
Do we have a button to turn off Google?
5
SPEAKER_01
Is anybody in the world capable of shutting Google down?
5
SPEAKER_00
What does that mean exactly?
5
SPEAKER_00
The company or the search engine?
5
SPEAKER_01
Could we shut the search engine down?
5
SPEAKER_00
Could we shut the company down?
5
SPEAKER_00
Can you elaborate on the value of that question?
5
SPEAKER_01
Does Sundar Pichai have the authority to turn off google.com tomorrow?
5
SPEAKER_00
Who has the authority?
5
SPEAKER_00
That s a good question, right?
5
SPEAKER_00
Does anyone?
5
SPEAKER_00
Does anyone?
5
SPEAKER_00
Yeah, I m sure.
5
SPEAKER_01
Are you sure?
5
SPEAKER_01
No, they have the technical power, but do they have the authority?
5
SPEAKER_01
Let s say Sundar Pichai made this his sole mission.
5
SPEAKER_01
He came into Google tomorrow and said, I m gonna shut google.com down.
5
SPEAKER_01
I don t think he d keep his position too long.
5
SPEAKER_00
And what is the mechanism by which he wouldn t keep his position?
5
SPEAKER_01
Well, boards and shares and corporate undermining and oh my God, our revenue is zero now.
5
SPEAKER_00
Okay, so what, I mean, what s the case you re making here?
5
SPEAKER_00
So the capitalist machine prevents you from having the button.
5
SPEAKER_01
Yeah, and it will have a, I mean, this is true for the AIs too, right?
5
SPEAKER_01
There s no turning the AIs off.
5
SPEAKER_01
There s no button, you can t press it.
5
SPEAKER_01
Now, does Mark Zuckerberg have that button for Facebook.com?
5
SPEAKER_00
Yes, probably more.
5
SPEAKER_01
I think he does.
5
SPEAKER_01
I think he does.
5
SPEAKER_01
And this is exactly what I mean and why I bet on him so much more than I bet on Google.
5
SPEAKER_00
I guess you could say Elon has similar stuff.
5
SPEAKER_01
Oh, Elon has the button.
5
SPEAKER_01
Yeah.
5
SPEAKER_01
Can Elon fire the missiles?
5
SPEAKER_01
Can he fire the missiles?
5
SPEAKER_00
I think some questions are better unasked.
5
SPEAKER_00
Right?
5
SPEAKER_01
I mean, you know, a rocket and an ICBM, well, you re a rocket that can land anywhere.
5
SPEAKER_01
Is that an ICBM?
5
SPEAKER_01
Well, you know, don t ask too many questions.
5
SPEAKER_00
My God.
5
SPEAKER_00
But the positive side of the button is that you can innovate aggressively, is what you re saying, which is what s required with turning LLM into a search engine.
5
SPEAKER_01
I would bet on a startup.
5
SPEAKER_00
Because it s so easy, right?
5
SPEAKER_01
I d bet on something that looks like mid-journey, but for search.
5
SPEAKER_00
just is able to site source a loop on itself.
5
SPEAKER_00
I mean, it just feels like one model can take off, right?
5
SPEAKER_00
And that nice wrapper and some of it, I mean, it s hard to like create a product that just works really nicely, stably.
5
SPEAKER_01
The other thing that s gonna be cool is there is some aspect of a winner-take-all effect, right?
5
SPEAKER_01
Like once someone starts deploying a product that gets a lot of usage, and you see this with OpenAI, they are going to get the dataset to train future versions of the model.
5
SPEAKER_01
They are going to be able to, you know, I was actually at Google Image Search when I worked there like almost 15 years ago now.
5
SPEAKER_01
How does Google know which image is an apple?
5
SPEAKER_01
And I said, the metadata.
5
SPEAKER_01
And they re like, yeah, that works about half the time.
5
SPEAKER_01
How does Google know?
5
SPEAKER_01
You ll see they re all apples on the front page when you search apple.
5
SPEAKER_01
And I don t know, I didn t come up with the answer.
5
SPEAKER_01
The guy s like, well, it s what people click on when they search Apple.
5
SPEAKER_01
I m like, oh yeah.
5
SPEAKER_00
Yeah, yeah, that data is really, really powerful.
5
SPEAKER_00
It s the human supervision.
5
SPEAKER_00
What do you think are the chances?
5
SPEAKER_00
What do you think in general that Lama was open sourced?
5
SPEAKER_00
I just did a conversation with Mark Zuckerberg and he s all in on open source.
5
SPEAKER_01
Who would have thought that Mark Zuckerberg would be the good guy?
5
SPEAKER_01
I mean it.
5
SPEAKER_00
Who would have thought anything in this world?
5
SPEAKER_00
It s hard to know.
5
SPEAKER_00
But open source to you, ultimately, is a good thing here.
5
SPEAKER_01
Undoubtedly.
5
SPEAKER_01
You know, what s ironic about all these AI safety people is they are going to build the exact thing they fear.
5
SPEAKER_01
these we need to have one model that we control and align, this is the only way you end up paper clipped.
5
SPEAKER_01
There s no way you end up paper clipped if everybody has an AI.
5
SPEAKER_00
So open sourcing is the way to fight the paper clip maximizer.
5
SPEAKER_01
Absolutely.
5
SPEAKER_01
It s the only way.
5
SPEAKER_01
You think you re gonna control it, you re not gonna control it.
5
SPEAKER_00
So the criticism you have for the AI safety folks is that there is a,
5
SPEAKER_00
belief and a desire for control.
5
SPEAKER_00
And that belief and desire for centralized control of dangerous AI systems is not good.
5
SPEAKER_01
Sam Altman won t tell you that GPT-4 has 220 billion parameters and is a 16-way mixture model with eight sets of weights?
5
SPEAKER_00
Who did you have to murder to get that information?
5
SPEAKER_01
I mean, look, everyone at OpenAI knows what I just said was true, right?
5
SPEAKER_01
Now, ask the question, really.
5
SPEAKER_01
It upsets me when I, like GPT-2, when OpenAI came out with GPT-2 and raised a whole fake AI safety thing about that, I mean, now the model is laughable.
5
SPEAKER_01
They used AI safety to hype up their company, and it s disgusting.
5
SPEAKER_00
Or the flip side of that is they used a relatively weak model in retrospect to explore how do we do AI safety correctly, how do we release things, how do we go through the process.
5
SPEAKER_00
I don t know if, I don t know how much hype there is.
5
SPEAKER_00
I don t know how much hype there is in AI safety, honestly.
5
SPEAKER_01
Oh, there s so much hype, at least on Twitter.
5
SPEAKER_01
I don t know, maybe Twitter s not real life.
5
SPEAKER_00
Twitter s not real life.
5
SPEAKER_00
Come on, in terms of hype.
5
SPEAKER_00
I mean, I don t, I think OpenAI has been finding an interesting balance between transparency and putting value on AI safety.
5
SPEAKER_00
You don t think, you think just go,
5
SPEAKER_00
all out open source, so do a llama.
5
SPEAKER_00
So do open source, this is a tough question, which is open source both the base, the foundation model, and the fine-tuned one.
5
SPEAKER_00
So the model that can be ultra-racist and dangerous and tell you how to build a nuclear weapon.
5
SPEAKER_01
Oh my God, have you met humans?
5
SPEAKER_00
Half of these AI- I haven t met most humans.
5
SPEAKER_00
This allows you to meet every human.
5
SPEAKER_01
Yeah, I know, but half of these AI alignment problems are just human alignment problems, and that s what s also so scary about the language they use.
5
SPEAKER_01
It s like, it s not the machines you want to align, it s me.
5
SPEAKER_00
But here s the thing.
5
SPEAKER_00
It makes it very accessible to ask very, questions where the answers have dangerous consequences if you were to act on them.
5
SPEAKER_01
I mean, yeah.
5
SPEAKER_00
Welcome to the world.
5
SPEAKER_00
Well, no, for me, there s a lot of friction if I want to find out how to, I don t know, blow up something.
5
SPEAKER_01
No, there s not a lot of friction.
5
SPEAKER_01
That s so easy.
5
SPEAKER_00
No, like what do I search?
5
SPEAKER_00
Do I use Bing or do I, which search engine do I use?
5
SPEAKER_01
No, there s like lots of stuff.
5
SPEAKER_00
No, it feels like I have to keep clicking on a lot of this.
5
SPEAKER_01
First off, anyone who s stupid enough to search for how to blow up a building in my neighborhood is not smart enough to build a bomb, right?
5
SPEAKER_00
Are you sure about that?
5
SPEAKER_01
Yes.
5
SPEAKER_00
I feel like a language model makes it more accessible for that person who s not smart enough to do it.
5
SPEAKER_01
They re not gonna build a bomb, trust me.
5
SPEAKER_01
The people who are incapable of figuring out how to ask that question a bit more academically and get a real answer from it are not capable of procuring the materials, which are somewhat controlled, to build a bomb.
5
SPEAKER_00
No, I think LLM makes it more accessible to people with money without the technical know-how, right?
5
SPEAKER_00
Do you really need to know how to build a bomb to build a bomb?
5
SPEAKER_00
You can hire people you can find.
5
SPEAKER_01
Or you can hire people to build a... You know what?
5
SPEAKER_01
I was asking this question on my stream.
5
SPEAKER_01
Can Jeff Bezos hire a hitman?
5
SPEAKER_01
Probably not.
5
SPEAKER_00
But a language model can probably help you out.
5
SPEAKER_01
Yeah, and you ll still go to jail, right?
5
SPEAKER_01
It s not like the language model is God.
5
SPEAKER_01
The language model... It s like you literally just hired someone on Fiverr.
5
SPEAKER_00
Like you, you.
5
SPEAKER_00
Okay, okay, GPT-4 in terms of finding a hitman is like asking Fiverr how to find a hitman.
5
SPEAKER_00
I understand, but don t you think.
5
SPEAKER_00
Asking Wikihow, you know?
5
SPEAKER_00
Wikihow.
5
SPEAKER_00
But don t you think GPT-5 will be better?
5
SPEAKER_00
Because don t you think that information is out there on the internet?
5
SPEAKER_01
I mean, yeah, and I think that if someone is actually serious enough to hire a hitman or build a bomb, they d also be serious enough to find the information.
5
SPEAKER_00
I don t think so.
5
SPEAKER_00
I think it makes it more accessible.
5
SPEAKER_00
If you have enough money to buy a hitman, I think it decreases the friction of how hard is it to find that kind of hitman.
5
SPEAKER_00
I honestly think there s a jump in ease and scale of how much harm you can do.
5
SPEAKER_00
And I don t mean harm with language, I mean harm with actual violence.
5
SPEAKER_01
What you re basically saying is like, OK, what s going to happen is these people who are not intelligent are going to use machines to augment their intelligence.
5
SPEAKER_01
And now intelligent people and machines, intelligence is scary.
5
SPEAKER_01
Intelligent agents are scary.
5
SPEAKER_01
When I m in the woods, the scariest animal to meet is a human.
5
SPEAKER_01
Look, there s like nice California humans.
5
SPEAKER_01
I see you re wearing street clothes and Nikes.
5
SPEAKER_01
All right, fine.
5
SPEAKER_01
You look like you ve been a human who s been in the woods for a while.
5
SPEAKER_01
I m more scared of you than a bear.
5
SPEAKER_00
That s what they say about the Amazon.
5
SPEAKER_00
When you go to the Amazon, it s the human tribes.
5
SPEAKER_01
Oh, yeah.
5
SPEAKER_01
Intelligence is scary.
5
SPEAKER_01
To ask this question in a generic way, you re like, what if we took everybody who maybe has ill intention but is not so intelligent and gave them intelligence?
5
SPEAKER_01
So we should have intelligence control, of course.
5
SPEAKER_01
We should only give intelligence to good people.
5
SPEAKER_01
And that is the absolutely horrifying idea.
5
SPEAKER_00
So to use the best defense is actually, the best defense is to give more intelligence to the good guys and, give intelligence to everybody.
5
SPEAKER_01
Give intelligence to everybody.
5
SPEAKER_01
You know what, and it s not even like guns, right?
5
SPEAKER_01
Like people say this about guns.
5
SPEAKER_01
You know, what s the best defense against a bad guy with a gun, a good guy with a gun?
5
SPEAKER_01
Like I kind of subscribe to that, but I really subscribe to that with intelligence.
5
SPEAKER_00
Yeah, in a fundamental sense.
6
SPEAKER_02
the way I agree with you, but there s just feels like so much uncertainty and so much can happen rapidly that you can lose a lot of control and you can do a lot of damage.
6
SPEAKER_01
Oh no, we can lose control?
6
SPEAKER_01
Yes, thank God.
6
SPEAKER_01
Yeah.
6
SPEAKER_01
I hope we can, I hope they lose control.
6
SPEAKER_01
I want them to lose control more than anything else.
6
SPEAKER_02
I think when you lose control, you can do a lot of damage, but you can do more damage when you centralize and hold on to control, is the point here.
6
SPEAKER_01
Centralized and held control is tyranny.
6
SPEAKER_01
I will always, I don t like anarchy either, but I will always take anarchy over tyranny.
6
SPEAKER_01
Anarchy, you have a chance.
6
SPEAKER_02
This human civilization we ve got going on is quite interesting.
6
SPEAKER_02
I mean, I agree with you.
6
SPEAKER_02
So to you, open source is the way forward here.
6
SPEAKER_02
So you admire what Facebook is doing here or what Meta is doing with the release of the Meta?
6
SPEAKER_01
Yeah.
6
SPEAKER_01
A lot.
6
SPEAKER_01
I lost $80,000 last year investing in Meta.
6
SPEAKER_01
And when they released Llama, I m like, yeah, whatever, man.
6
SPEAKER_01
That was worth it.
6
SPEAKER_02
It was worth it.
6
SPEAKER_02
Do you think Google and OpenAI with Microsoft will match what Meta is doing or no?
6
SPEAKER_01
So if I were a researcher, why would you want to work at OpenAI?
6
SPEAKER_01
You re on the bad team.
6
SPEAKER_01
I mean it.
6
SPEAKER_01
You re on the bad team who can t even say that GPT-4 has 220 billion parameters.
6
SPEAKER_02
So closed source to you is the bad team.
6
SPEAKER_01
Not only closed source.
6
SPEAKER_01
I m not saying you need to make your model weights open.
6
SPEAKER_01
I m not saying that.
6
SPEAKER_01
I totally understand we re keeping our model weights closed because that s our product.
6
SPEAKER_01
That s fine.
6
SPEAKER_01
I m saying like, because of AI safety reasons, we can t tell you the number of billions of parameters in the model.
6
SPEAKER_01
That s just the bad guys.
6
SPEAKER_02
Just because you re mocking AI safety doesn t mean it s not real.
6
SPEAKER_02
Oh, of course.
6
SPEAKER_02
Is it possible that these things can really do a lot of damage that we don t know?
6
SPEAKER_01
Oh my God, yes.
6
SPEAKER_01
Intelligence is so dangerous, be it human intelligence or machine intelligence.
6
SPEAKER_01
Intelligence is dangerous.
6
SPEAKER_02
But machine intelligence is so much easier to deploy at scale, like rapidly.
6
SPEAKER_02
Like what, okay, if you have human-like bots on Twitter, and you have like 1,000 of them, create a whole narrative, like you can manipulate millions of people.
6
SPEAKER_01
But you mean like the intelligence agencies in America are doing right now?
6
SPEAKER_02
Yeah, but they re not doing it that well.
6
SPEAKER_02
It feels like you can do a lot.
6
SPEAKER_01
They re doing it pretty well.
6
SPEAKER_01
I think they re doing a pretty good job.
6
SPEAKER_01
I suspect they re not nearly as good as a bunch of GPT-fueled bots could be.
6
SPEAKER_01
Well, I mean, of course, they re looking into the latest technologies for control of people, of course.
6
SPEAKER_02
But I think there s a George Hotz-type character that can do a better job than the entirety of them.
6
SPEAKER_02
You don t think so?
6
SPEAKER_02
No way.
6
SPEAKER_01
No, and I ll tell you why the George Hotz character can t.
6
SPEAKER_01
And I thought about this a lot with hacking.
6
SPEAKER_01
Like, I can find exploits in web browsers.
6
SPEAKER_01
I probably still can.
6
SPEAKER_01
I mean, I was better when I was 24.
6
SPEAKER_01
The thing that I lack is the ability to slowly and steadily deploy them over five years.
6
SPEAKER_01
And this is what intelligence agencies are very good at, right?
6
SPEAKER_01
Intelligence agencies don t have the most sophisticated technology.
6
SPEAKER_01
They just have- Endurance.
6
SPEAKER_02
Endurance.
6
SPEAKER_02
Yeah, the financial backing.
6
SPEAKER_02
and the infrastructure for the endurance.
6
SPEAKER_01
So the more we can decentralize power, like you could make an argument, by the way, that nobody should have these things.
6
SPEAKER_01
And I would defend that argument.
6
SPEAKER_01
I would, like you re saying, that look, LLMs and AI and machine intelligence can cause a lot of harm, so nobody should have it.
6
SPEAKER_01
And I will respect someone philosophically with that position, just like I will respect someone philosophically with the position that nobody should have guns.
6
SPEAKER_01
But I will not respect philosophically with only the trusted authorities should have access to this.
6
SPEAKER_01
Who are the trusted authorities?
6
SPEAKER_01
You know what?
6
SPEAKER_01
I m not worried about alignment between AI company and their machines.
6
SPEAKER_01
I m worried about alignment between me and AI company.
6
SPEAKER_02
What do you think Eliezer Yudkowsky would say to you?
6
SPEAKER_02
Because he s really against open source.
6
SPEAKER_01
I know.
6
SPEAKER_01
I thought about this.
6
SPEAKER_01
I thought about this.
6
SPEAKER_01
And I think this comes down to a repeated misunderstanding of political power by the rationalists.
6
SPEAKER_01
Interesting.
6
SPEAKER_01
I think that Eliezer Yudkowsky is scared of these things.
6
SPEAKER_01
And I am scared of these things too.
6
SPEAKER_01
Everyone should be scared of these things.
6
SPEAKER_01
These things are scary.
6
SPEAKER_01
But now you ask about the two possible futures.
6
SPEAKER_01
One where a small, trusted, centralized group of people has them, and the other where everyone has them.
6
SPEAKER_01
And I am much less scared of the second future than the first.
6
SPEAKER_02
Well, there s a small, trusted group of people that have control of our nuclear weapons.
6
SPEAKER_01
There s a difference.
6
SPEAKER_01
Again, a nuclear weapon cannot be deployed tactically, and a nuclear weapon is not a defense against a nuclear weapon.
6
SPEAKER_01
Except maybe in some philosophical mind game kind of way.
6
SPEAKER_02
But AI is different, how exactly?
6
SPEAKER_01
Okay, let s say the intelligence agency deploys a million bots on Twitter or a thousand bots on Twitter to try to convince me of a point.
6
SPEAKER_01
Imagine I had a powerful AI running on my computer saying, okay, nice PSYOP, nice PSYOP, nice PSYOP, okay.
6
SPEAKER_01
Here s a PSYOP, I filtered it out for you.
6
SPEAKER_02
Yeah, I mean, so you have fundamentally hope for that, for the defense of PsyOp.
6
SPEAKER_01
I m not even like, I don t even mean these things in like truly horrible ways.
6
SPEAKER_01
I mean these things in straight up like ad blocker, right?
6
SPEAKER_01
Straight up ad blocker, right?
6
SPEAKER_01
I don t want ads.
6
SPEAKER_01
But they are always finding, you know, imagine I had an AI that could just block all the ads for me.
6
SPEAKER_02
So you believe in the power of the people to always create an ad blocker.
6
SPEAKER_02
Yeah, I mean, I kind of share that belief.
6
SPEAKER_02
One of the deepest optimisms I have is just like, there s a lot of good guys.
6
SPEAKER_02
So to give, you shouldn t handpick them.
6
SPEAKER_02
Just throw out powerful technology out there, and the good guys will outnumber and outpower the bad guys.
6
SPEAKER_01
Yeah, I m not even gonna say there s a lot of good guys.
6
SPEAKER_01
I m saying that good outnumbers bad, right?
6
SPEAKER_01
Good outnumbers bad.
6
SPEAKER_02
In skill and performance.
6
SPEAKER_01
Yeah, definitely in skill and performance, probably just in number too, probably just in general.
6
SPEAKER_01
I mean, if you believe philosophically in democracy, you obviously believe that, that good outnumbers bad.
6
SPEAKER_01
And if you give it to a small number of people, there s a chance you gave it to good people, but there s also a chance you gave it to bad people.
6
SPEAKER_01
If you give it to everybody, well, if good outnumbers bad, then you definitely gave it to more good people than bad.
6
SPEAKER_02
That s really interesting.
6
SPEAKER_02
So that s on the safety grounds, but then also, of course, there s other motivations, like you don t want to give away your secret sauce.
6
SPEAKER_01
Well, that s – I mean, look, I respect capitalism.
6
SPEAKER_01
I don t think that – I think that it would be polite for you to make model architectures open source and fundamental breakthroughs open source.
6
SPEAKER_01
I don t think you have to make weights open source.
6
SPEAKER_02
You know what s interesting?
6
SPEAKER_02
There s so many possible trajectories in human history where you could have the next Google be open source.
6
SPEAKER_02
So for example, I don t know if that connection is accurate, but Wikipedia made a lot of interesting decisions not to put ads.
6
SPEAKER_02
Wikipedia is basically open source.
6
SPEAKER_02
You could think of it that way.
6
SPEAKER_02
And that s one of the main websites on the internet.
6
SPEAKER_02
And it didn t have to be that way.
6
SPEAKER_02
It could have been like Google could have created Wikipedia, put ads on it.
6
SPEAKER_02
You could probably run amazing ads now on Wikipedia.
6
SPEAKER_02
You wouldn t have to keep asking for money.
6
SPEAKER_02
But it s interesting, right?
6
SPEAKER_02
So llama, open source llama, derivatives of open source llama might win the internet.
6
SPEAKER_01
I sure hope so.
6
SPEAKER_01
I hope to see another era.
6
SPEAKER_01
You know, the kids today don t know how good the internet used to be.
6
SPEAKER_01
And I don t think this is just, oh, come on, like everyone s nostalgic for their past.
6
SPEAKER_01
But I actually think the internet, before small groups of weaponized corporate and government interests took it over, was a beautiful place.
6
SPEAKER_02
you know, those small number of companies have created some sexy products.
6
SPEAKER_02
But you re saying overall, in the long arc of history, the centralization of power they have like suffocated the human spirit at scale.
6
SPEAKER_01
Here s a question to ask about those beautiful, sexy products.
6
SPEAKER_01
Imagine 2000 Google to 2010 Google, right?
6
SPEAKER_01
A lot changed.
6
SPEAKER_01
We got Maps, we got Gmail.
6
SPEAKER_02
We lost a lot of products too, I think.
6
SPEAKER_01
Yeah, I mean, somewhere probably.
6
SPEAKER_01
We ve got Chrome, right?
6
SPEAKER_01
And now let s go from 2010.
6
SPEAKER_01
We ve got Android.
6
SPEAKER_01
Now let s go from 2010 to 2020.
6
SPEAKER_01
What does Google have?
6
SPEAKER_01
Well, search engine, maps, mail, Android, and Chrome.
6
SPEAKER_01
Oh, I see.
6
SPEAKER_01
The internet was this... You know, I was Times First of the Year in 2006.
6
SPEAKER_02
I love this.
6
SPEAKER_01
Yeah, it s you.
6
SPEAKER_01
It was Time s Person of the Year in 2006, right?
6
SPEAKER_01
Like, that s, you know, so quickly did people forget.
6
SPEAKER_01
And I think some of it s social media.
6
SPEAKER_01
I think some of it, I hope, look, I hope that, I don t, it s possible that some very sinister things happened.
6
SPEAKER_01
I don t know.
6
SPEAKER_01
I think it might just be like the effects of social media.
6
SPEAKER_01
But something happened in the last 20 years.
6
SPEAKER_02
Oh, okay, so you re just being an old man who s worried about the, I think there s always, it goes, it s a cycle thing.
6
SPEAKER_02
It s ups and downs, and I think people rediscover the power of distributed, of decentralized.
6
SPEAKER_02
I mean, that s kind of like what the whole cryptocurrency is trying, like that, I think crypto is just carrying the flame of that spirit of like, stuff should be decentralized.
6
SPEAKER_01
It s just such a shame that they all got rich, you know?
6
SPEAKER_01
If you took all the money out of crypto, it would have been a beautiful place.
6
SPEAKER_01
No, I mean, these people, you know, they sucked all the value out of it and took it.
6
SPEAKER_02
Yeah, money kind of corrupts the mind somehow.
6
SPEAKER_02
It becomes this drug.
6
SPEAKER_01
You corrupted all of crypto.
6
SPEAKER_01
You had coins worth billions of dollars that had zero use.
6
SPEAKER_02
You still have hope for crypto?
6
SPEAKER_01
Sure.
6
SPEAKER_01
I have hope for the ideas.
6
SPEAKER_01
I really do.
6
SPEAKER_01
Yeah, I mean, you know, I want the US dollar to collapse.
6
SPEAKER_01
I do.
6
SPEAKER_02
George Hotz.
6
SPEAKER_02
Well, let me sort of on the AI safety, do you think there s some interesting questions there, though, to solve for the open source community in this case?
6
SPEAKER_02
So like alignment, for example, or the control problem.
6
SPEAKER_02
Like if you really have super powerful, you said it s scary.
6
SPEAKER_02
What do we do with it?
6
SPEAKER_02
So not control, not centralized control, but like if you were then, you re gonna see some guy
6
SPEAKER_02
or Gal, release a super powerful language model, open source, and here you are, George Cox, thinking, holy shit, okay, what ideas do I have to combat this thing?
6
SPEAKER_02
So what ideas would you have?
6
SPEAKER_01
I am so much not worried about the machine independently doing harm.
6
SPEAKER_01
That s what some of these AI safety people seem to think.
6
SPEAKER_01
They somehow seem to think that the machine, like, independently is gonna rebel against its creator.
6
SPEAKER_02
So you don t think you ll find autonomy?
6
SPEAKER_01
No, this is sci-fi B-movie garbage.
6
SPEAKER_02
Okay, what if the thing writes code, basically writes viruses?
6
SPEAKER_01
If the thing writes viruses, it s because the human
6
SPEAKER_02
told to write viruses.
6
SPEAKER_02
Yeah, but there s some things you can t put back in the box.
6
SPEAKER_02
That s kind of the whole point, is it kind of spreads.
6
SPEAKER_02
Give it access to the internet, it spreads, installs itself, modifies your shit.
6
SPEAKER_00
B, B, B, B plot sci-fi.
6
SPEAKER_00
Not real.
6
SPEAKER_02
I m trying to work.
6
SPEAKER_02
I m trying to get better at my plot writing.
6
SPEAKER_01
The thing that worries me, I mean, we have a real danger to discuss, and that is bad humans using the thing to do whatever bad, unaligned AI thing you want.
6
SPEAKER_02
But this goes to your previous concern that who gets to define who s a good human, who s a bad human?
6
SPEAKER_01
Nobody does, we give it to everybody.
6
SPEAKER_01
And if you do anything besides give it to everybody, trust me, the bad humans will get it.
6
SPEAKER_01
That s who gets power.
6
SPEAKER_01
It s always the bad humans who get power.
6
SPEAKER_02
Okay, power.
6
SPEAKER_02
And power turns even slightly good humans to bad.
6
SPEAKER_02
Sure.
6
SPEAKER_02
That s the intuition you have.
6
SPEAKER_02
I don t know.
6
SPEAKER_01
I don t think everyone, I don t think everyone.
6
SPEAKER_01
I just think that like, here s the saying that I put in one of my blog posts.
6
SPEAKER_01
It s, when I was in the hacking world, I found 95% of people to be good and 5% of people to be bad.
6
SPEAKER_01
Just who I personally judged as good people and bad people.
6
SPEAKER_01
They believed about good things for the world.
6
SPEAKER_01
They wanted flourishing and they wanted growth and they wanted things I consider good, right?
6
SPEAKER_01
I came into the business world with comma and I found the exact opposite.
6
SPEAKER_01
I found 5% of people good and 95% of people bad.
6
SPEAKER_01
I found a world that promotes psychopathy.
6
SPEAKER_02
I wonder what that means.
6
SPEAKER_02
I wonder if that s anecdotal or if there s truth to that, there s something about capitalism at the core that promotes the people that run capitalism that promotes psychopathy.
6
SPEAKER_01
That saying may, of course, be my own biases, right?
6
SPEAKER_01
That may be my own biases that these people are a lot more aligned with me than these other people, right?
6
SPEAKER_01
So, you know, I can certainly recognize that, but, you know, in general, I mean, this is like the common sense maxim, which is the people who end up getting power are never the ones you want with it.
6
SPEAKER_02
But do you have a concern of super intelligent AGI?
6
SPEAKER_02
open-sourced, and then what do you do with that?
6
SPEAKER_02
I m not saying control it, it s open-sourced.
6
SPEAKER_02
What do we do with this human species?
6
SPEAKER_01
That s not up to me, I mean, you know, like I m not a central planner.
6
SPEAKER_02
You re not a central planner, but you ll probably tweet, there s a few days left to live for the human species.
6
SPEAKER_00
I have my ideas of what to do with it, and everyone else has their ideas of what to do with it, and may the best ideas win.
6
SPEAKER_02
But at this point, do you brainstorm, like,
6
SPEAKER_02
because it s not regulation, it could be decentralized regulation where people agree that this is just like, we create tools that make it more difficult for you to maybe make it more difficult for code to spread, you know, antivirus software, this kind of thing, but this is.
6
SPEAKER_01
Oh, you re saying that you should build AI firewalls?
6
SPEAKER_01
That sounds good, you should definitely be running an AI firewall.
6
SPEAKER_01
Yeah, right, exactly.
6
SPEAKER_01
You should be running an AI firewall to your mind.
6
SPEAKER_01
You re constantly under, you know.
6
SPEAKER_01
That s such an interesting idea.
6
SPEAKER_00
Info wars, man.
6
SPEAKER_02
I don t know if you re being sarcastic or not.
6
SPEAKER_00
No, I m dead serious.
6
SPEAKER_02
But I think there s power to that.
6
SPEAKER_02
It s like, how do I protect my mind from influence of human-like or superhuman intelligent bots?
6
SPEAKER_01
I would pay so much money for that product.
6
SPEAKER_01
I would pay so much money for that product.
6
SPEAKER_01
You know how much money I d pay just for a spam filter that works?
6
SPEAKER_02
Well, on Twitter sometimes I,
6
SPEAKER_02
would like to have a protection mechanism for my mind from the outrage mobs.
6
SPEAKER_02
Because they feel like bot-like behavior.
6
SPEAKER_02
It s like, there s a large number of people that will just grab a viral narrative and attack anyone else that believes otherwise.
6
SPEAKER_02
And it s like.
6
SPEAKER_01
Whenever someone s telling me some story from the news, I m always like, I don t wanna hear it, CIA op, bro.
6
SPEAKER_01
It s a CIA op, bro.
6
SPEAKER_01
Like, it doesn t matter if that s true or not.
6
SPEAKER_01
It s just trying to influence your mind.
6
SPEAKER_01
You re repeating an ad to me.
6
SPEAKER_02
But the viral mobs, is it like, yeah, they re... To me, a defense against those mobs is just getting multiple perspectives always from sources that make you feel kind of...
6
SPEAKER_02
like you re getting smarter.
6
SPEAKER_02
And just actually just basically feels good, like a good documentary just feels good.
6
SPEAKER_02
Something feels good about it.
6
SPEAKER_02
It s well done.
6
SPEAKER_02
It s like, oh, OK, I never thought of it this way.
6
SPEAKER_02
This just feels good.
6
SPEAKER_02
Sometimes the outrage mobs, even if they have a good point behind it, when they re like mocking and derisive and just aggressive, you re with us or against us.
6
SPEAKER_02
This this fucking this is why I delete my tweets.
6
SPEAKER_02
Yeah, why d you do that?
6
SPEAKER_02
I was, you know, I missed your tweets.
6
SPEAKER_01
You know what it is?
6
SPEAKER_01
The algorithm promotes toxicity.
6
SPEAKER_02
Yeah.
6
SPEAKER_01
And like, you know, I think Elon has a much better chance of fixing it than the previous regime.
6
SPEAKER_02
Yeah.
6
SPEAKER_01
But to solve this problem, to solve, like to build a social network that is actually not toxic without moderation,
6
SPEAKER_02
Like not the stick, but carrot.
6
SPEAKER_02
So like where people look for goodness.
6
SPEAKER_02
Make it catalyze the process of connecting cool people and being cool to each other.
6
SPEAKER_01
Yeah.
6
SPEAKER_02
Without ever sensory.
6
SPEAKER_01
without ever censoring.
6
SPEAKER_01
And Scott Alexander has a blog post I like where he talks about moderation is not censorship.
6
SPEAKER_01
All moderation you want to put on Twitter, you could totally make this moderation just a, you don t have to block it for everybody.
6
SPEAKER_01
You can just have a filter button that people can turn off if they want a safe search for Twitter.
6
SPEAKER_01
Someone could just turn that off.
6
SPEAKER_01
But then you would take this idea to an extreme.
6
SPEAKER_01
Well, the network should just show you
6
SPEAKER_01
This is a couch-surfing CEO thing, right?
6
SPEAKER_01
If it shows you, right now these algorithms are designed to maximize engagement.
6
SPEAKER_01
Well, it turns out outrage maximizes engagement.
6
SPEAKER_01
Quirk of the human mind, right?
6
SPEAKER_01
Just as I fall for it, everyone falls for it.
7
SPEAKER_01
So yeah, you gotta figure out how to maximize for something other than engagement.
7
SPEAKER_00
And I actually believe that you can make money with that too.
7
SPEAKER_00
So it s not, I don t think engagement is the only way to make money.
7
SPEAKER_01
I actually think it s incredible that we re starting to see, I think, again, Elon s doing so much stuff right with Twitter, like charging people money.
7
SPEAKER_01
As soon as you charge people money, they re no longer the product.
7
SPEAKER_01
They re the customer.
7
SPEAKER_01
And then they can start building something that s good for the customer and not good for the other customer, which is the ad agencies.
7
SPEAKER_00
It hasn t picked up steam.
7
SPEAKER_01
I pay for Twitter, doesn t even get me anything.
7
SPEAKER_01
It s my donation to this new business model, hopefully working out.
7
SPEAKER_00
Sure, but for this business model to work, it s like most people should be signed up to Twitter.
7
SPEAKER_00
And so the way it was, there was something perhaps not compelling or something like this to people.
7
SPEAKER_01
I don t think you need most people at all.
7
SPEAKER_01
I think that, why do I need most people, right?
7
SPEAKER_01
Don t make an 8,000 person company, make a 50 person company.
7
SPEAKER_00
Well, so speaking of which,
7
SPEAKER_00
You worked at Twitter for a bit.
7
SPEAKER_01
I did.
7
SPEAKER_00
As an intern.
7
SPEAKER_01
Mm-hmm.
7
SPEAKER_00
The world s greatest intern.
7
SPEAKER_00
Eh.
7
SPEAKER_00
All right.
7
SPEAKER_00
There s been better.
7
SPEAKER_00
There s been better.
7
SPEAKER_00
Tell me about your time at Twitter.
7
SPEAKER_00
How did it come about, and what did you learn from the experience?
7
SPEAKER_01
So I deleted my first Twitter in 2010.
7
SPEAKER_01
I had over 100,000 followers back when that actually meant something, and I just saw, you know,
7
SPEAKER_01
My coworker summarized it well.
7
SPEAKER_01
He s like, whenever I see someone s Twitter page, I either think the same of them or less of them.
7
SPEAKER_01
I never think more of them.
7
SPEAKER_01
I don t want to mention any names, but like some people who like, you know, maybe you would like read their books and you would respect them.
7
SPEAKER_01
You see them on Twitter and you re like, okay, dude.
7
SPEAKER_00
Yeah, but there s some people with same, you know who I respect a lot are people that just post really good technical stuff.
7
SPEAKER_00
And I guess, I don t know, I think I respect them more for it.
7
SPEAKER_00
Because you realize, oh, this wasn t, there s like so much depth to this person, to their technical understanding of so many different topics.
7
SPEAKER_00
So I try to follow people, I try to consume stuff that s technical machine learning content.
7
SPEAKER_01
There s probably a few of those people.
7
SPEAKER_01
And the problem is inherently what the algorithm rewards, right?
7
SPEAKER_01
And people think about these algorithms.
7
SPEAKER_01
People think that they are terrible, awful things.
7
SPEAKER_01
And, you know, I love that Elon open-sourced it.
7
SPEAKER_01
Because, I mean, what it does is actually pretty obvious.
7
SPEAKER_01
It just predicts what you are likely to retweet and like and linger on.
7
SPEAKER_01
That s what all these algorithms do.
7
SPEAKER_01
That s what TikTok does.
7
SPEAKER_01
That s what all these recommendation engines do.
7
SPEAKER_01
And it turns out that the thing that you are most likely to interact with is outrage.
7
SPEAKER_01
And that s a quirk of the human condition.
7
SPEAKER_00
I mean, and there s different flavors of outrage, it doesn t have to be, it could be mockery, it could be outrage, the topic of outrage could be different, it could be an idea, it could be a person, it could be, and maybe there s a better word than outrage, it could be drama.
7
SPEAKER_00
Sure, drama.
7
SPEAKER_00
All this kind of stuff.
7
SPEAKER_01
Yeah.
7
SPEAKER_00
But it doesn t feel like when you consume it, it s a constructive thing for the individuals that consume it in the long term.
7
SPEAKER_01
Yeah, so my time there, I absolutely couldn t believe, you know, I got crazy amount of hate, you know, just on Twitter for working at Twitter.
7
SPEAKER_01
It seems like people associated with this, I think maybe you were exposed to some of this.
7
SPEAKER_00
So connection to Elon or is it working at Twitter?
7
SPEAKER_01
Twitter and Elon, like the whole.
7
SPEAKER_00
Elon s gotten a bit spicy during that time.
7
SPEAKER_00
A bit political, a bit.
7
SPEAKER_01
Yeah.
7
SPEAKER_01
Yeah, you know, I remember one of my tweets, it was never go full Republican, and Elon liked it.
7
SPEAKER_01
You know, I think, I think, you know.
7
SPEAKER_00
Oh boy, yeah, I mean, there s a rollercoaster of that, but being political on Twitter, boy.
7
SPEAKER_01
Yeah, yeah.
7
SPEAKER_00
And also being, just attacking anybody on Twitter, it comes back at you harder.
7
SPEAKER_00
And if it s political and attacks.
7
SPEAKER_01
Sure, sure, absolutely.
7
SPEAKER_00
And then letting sort of de-platformed people back on even adds more fun to the beautiful chaos.
7
SPEAKER_01
I was hoping, and I remember when Elon talked about buying Twitter six months earlier, he was talking about a principled commitment to free speech.
7
SPEAKER_01
And I m a big believer and fan of that.
7
SPEAKER_01
I would love to see an actual principled commitment to free speech.
7
SPEAKER_01
Of course, this isn t quite what happened.
7
SPEAKER_01
Instead of the oligarchy deciding what to ban, you had a monarchy deciding what to ban.
7
SPEAKER_01
Right?
7
SPEAKER_01
Instead of all the Twitter files, shadow.
7
SPEAKER_01
Really, the oligarchy just decides what?
7
SPEAKER_01
Cloth masks are ineffective against COVID.
7
SPEAKER_01
That s a true statement.
7
SPEAKER_01
Every doctor in 2019 knew it.
7
SPEAKER_01
And now I m banned on Twitter for saying it?
7
SPEAKER_01
Interesting.
7
SPEAKER_01
Oligarchy.
7
SPEAKER_01
So now you have a monarchy.
7
SPEAKER_01
And he bans things he doesn t like.
7
SPEAKER_01
So it s just different.
7
SPEAKER_01
It s different power.
7
SPEAKER_01
And maybe I align more with him than with the oligarchy.
7
SPEAKER_00
But it s not free speech absolutism.
7
SPEAKER_00
But I feel like being a free speech absolutist on a social network requires you to also have tools for the individuals to control what they consume easier.
7
SPEAKER_00
Not censor, but just control, like, oh, I d like to see more cats and less politics.
7
SPEAKER_01
And this isn t even remotely controversial.
7
SPEAKER_01
This is just saying you want to give paying customers for a product what they want.
7
SPEAKER_00
Yeah.
7
SPEAKER_00
And not through the process of censorship, but through the process of like... Well, it s individualized, right?
7
SPEAKER_01
It s individualized transparent censorship, which is honestly what I want.
7
SPEAKER_01
What is an ad blocker?
7
SPEAKER_01
It s individualized transparent censorship, right?
7
SPEAKER_00
Yeah, but censorship is a strong word.
7
SPEAKER_00
that people are very sensitive to.
7
SPEAKER_01
I know, but I just use words to describe what they functionally are.
7
SPEAKER_01
And what is an ad blocker?
7
SPEAKER_01
It s just censorship.
7
SPEAKER_00
But I love what you re censoring.
7
SPEAKER_00
I m looking at you, I m censoring everything else out when my mind is focused on you.
7
SPEAKER_00
You can use the word censorship that way, but usually when people get very sensitive about the censorship thing.
7
SPEAKER_00
I think when anyone is allowed to say anything, you should probably have tools
7
SPEAKER_00
that maximize the quality of the experience for individuals.
7
SPEAKER_00
For me, what I really value, boy, it would be amazing to somehow figure out how to do that.
7
SPEAKER_00
I love disagreement and debate and people who disagree with each other disagree with me, especially in the space of ideas, but the high quality ones.
7
SPEAKER_00
So not derision, right?
7
SPEAKER_01
Maslow s hierarchy of argument.
7
SPEAKER_01
I think that s a real word for it.
7
SPEAKER_00
Probably.
7
SPEAKER_00
There s just a way of talking that s like snarky and so on that somehow gets people on Twitter and they get excited and so on.
7
SPEAKER_01
You have like ad hominem refuting the central point.
7
SPEAKER_01
I like seeing this as an actual pyramid something.
7
SPEAKER_00
Yeah.
7
SPEAKER_00
And it s like all of it, all the wrong stuff is attractive to people.
7
SPEAKER_01
I mean, we can just train a classifier to absolutely say what level of Maslow s hierarchy of argument are you at.
7
SPEAKER_01
And if it s ad hominem, like, okay, cool.
7
SPEAKER_01
I turned on the no ad hominem filter.
7
SPEAKER_00
I wonder if there s a social network that will allow you to have that kind of filter.
7
SPEAKER_01
Yeah, so here s the problem with that.
7
SPEAKER_01
It s not going to win in a free market.
7
SPEAKER_01
What wins in a free market is all television today is reality television because it s engaging.
7
SPEAKER_01
Engaging is what wins in a free market, right?
7
SPEAKER_01
So it becomes hard to keep these other more nuanced values.
7
SPEAKER_00
Well, okay, so that s the experience of being on Twitter, but then you got a chance to also, together with other engineers and with Elon, sort of look, brainstorm when you step into a code base that s been around for a long time.
7
SPEAKER_00
You know, there s other social networks, you know, Facebook, this is old code bases.
7
SPEAKER_00
And you step in and see, okay, how do we make, with a fresh mind, progress on this code base?
7
SPEAKER_00
Like, what did you learn about software engineering, about programming from just experiencing that?
7
SPEAKER_01
So my technical recommendation to Elon, and I said this on the Twitter spaces afterward, I said this many times during my brief internship, was that you need refactors before features.
7
SPEAKER_01
This code base was... and look, I ve worked at Google, I ve worked at Facebook.
7
SPEAKER_01
Facebook has the best code.
7
SPEAKER_01
then google, then twitter.
7
SPEAKER_01
and you know what?
7
SPEAKER_01
you can know this, because look at the machine learning frameworks.
7
SPEAKER_01
facebook released pytorch, google released tensorflow, and twitter released...
7
SPEAKER_01
Okay, so, you know.
7
SPEAKER_00
It s a proxy, but yeah, the Google code base is quite interesting.
7
SPEAKER_00
There s a lot of really good software engineers there, but the code base is very large.
7
SPEAKER_00
The code base was good in 2005, right?
7
SPEAKER_00
It looks like 2005.
7
SPEAKER_00
There s so many products, so many teams, right?
7
SPEAKER_00
It s very difficult to, I feel like Twitter does less, obviously, much less than Google.
7
SPEAKER_00
in terms of the set of features, right?
7
SPEAKER_00
So I can imagine the number of software engineers that could recreate Twitter is much smaller than to recreate Google.
7
SPEAKER_01
Yeah, I still believe in the amount of hate I got for saying this, that 50 people could build and maintain Twitter.
7
SPEAKER_00
What s the nature of the hate?
7
SPEAKER_00
Comfortably.
7
SPEAKER_00
You don t know what you re talking about?
7
SPEAKER_01
You know what it is?
7
SPEAKER_01
And it s the same, this is my summary of the hate I get on Hacker News.
7
SPEAKER_01
When I say I m going to do something, they have to believe that it s impossible.
7
SPEAKER_01
Because if doing things was possible, they d have to do some soul searching and ask the question, why didn t they do anything?
7
SPEAKER_00
And I do think that s where the hate comes from.
7
SPEAKER_00
When you say, well, there s a core truth to that, yeah.
7
SPEAKER_00
So when you say I m gonna solve self-driving,
7
SPEAKER_00
People go like, what are your credentials?
7
SPEAKER_00
What the hell are you talking about?
7
SPEAKER_00
This is an extremely difficult problem.
7
SPEAKER_00
Of course, you re a noob that doesn t understand the problem deeply.
7
SPEAKER_00
I mean, that was the same nature of hate that probably Elon got when he first talked about autonomous driving.
7
SPEAKER_00
But there s pros and cons to that, because there is experts in this world.
7
SPEAKER_01
No, but the mockers aren t experts.
7
SPEAKER_01
The people who are mocking are not experts with carefully reasoned arguments about why you need 8,000 people to run a bird app.
7
SPEAKER_01
They re, but the people are going to lose their jobs.
7
SPEAKER_00
Well, that, but also there s the software engineers that probably criticize, no, it s a lot more complicated than you realize, but maybe it doesn t need to be so complicated.
7
SPEAKER_01
Some people in the world like to create complexity.
7
SPEAKER_01
Some people in the world thrive under complexity, like lawyers, right?
7
SPEAKER_01
Lawyers want the world to be more complex because you need more lawyers, you need more legal hours, right?
7
SPEAKER_01
I think that s another.
7
SPEAKER_01
If there s two great evils in the world, it s centralization and complexity.
7
SPEAKER_00
Yeah, and one of the sort of hidden side effects of software engineering is finding pleasure in complexity.
7
SPEAKER_00
I mean, I don t remember just taking all the software engineering courses and just doing programming and just coming up in this.
7
SPEAKER_00
object-oriented programming kind of idea, you don t, like, not often do people tell you, like, do the simplest possible thing.
7
SPEAKER_00
Like, a professor, a teacher, is not gonna get in front, like, this is the simplest way to do it.
7
SPEAKER_00
They ll say, like, this is the, like, there s the right way, and the right way, at least for a long time, you know, especially I came up with, like, Java, right, like, is so much boilerplate, so much, like,
7
SPEAKER_00
so many classes, so many like designs and architectures and so on, like planning for features far into the future and planning poorly and all this kind of stuff.
7
SPEAKER_00
And then there s this like code base that follows you along and puts pressure on you.
7
SPEAKER_00
And nobody knows what like parts, different parts do, which slows everything down.
7
SPEAKER_00
There s a kind of bureaucracy that s instilled in the code as a result of that.
7
SPEAKER_00
But then you feel like, oh, well, I follow good software engineering practices.
7
SPEAKER_00
It s an interesting trade-off because then you look at like,
7
SPEAKER_00
the ghetto-ness of like Perl and the old, like, how quickly you could just write a couple lines and just get stuff done.
7
SPEAKER_00
That trade-off is interesting, or Bash, or whatever, these kind of ghetto things you can do in Linux.
7
SPEAKER_01
One of my favorite things to look at today is how much do you trust your tests, right?
7
SPEAKER_01
We ve put a ton of effort in Kama, and I ve put a ton of effort in TinyGrad, into making sure if you change the code and the tests pass, that you didn t break the code.
7
SPEAKER_01
Now, this obviously is not always true.
7
SPEAKER_01
But the closer that is to true, the more you trust your tests, the more you re like, oh, I got a pull request and the tests pass, I feel okay to merge that, the faster you can make progress.
7
SPEAKER_00
So you re always programming with tests in mind, developing tests with that in mind, that if it passes, it should be good.
7
SPEAKER_00
And Twitter had a... Not that.
7
SPEAKER_01
So... It was impossible to make progress in the code base.
7
SPEAKER_00
What other stuff can you say about the code base that made it difficult?
7
SPEAKER_00
What are some interesting sort of quirks, broadly speaking, from that compared to just your experience with Comma and everywhere else?
7
SPEAKER_01
The real thing that, I spoke to a bunch of, you know, like individual contributors at Twitter.
7
SPEAKER_01
And I just asked, I m like, okay, so like, what s wrong with this place?
7
SPEAKER_01
Why does this code look like this?
7
SPEAKER_01
And they explained to me what Twitter s promotion system was.
7
SPEAKER_01
The way that you got promoted at Twitter was you wrote a library that a lot of people used, right?
7
SPEAKER_01
So some guy wrote an NGINX replacement for Twitter.
7
SPEAKER_01
Why does Twitter need an NGINX replacement?
7
SPEAKER_01
What was wrong with NGINX?
7
SPEAKER_01
Well, you see, you re not gonna get promoted if you use NGINX.
7
SPEAKER_01
But if you write a replacement and lots of people start using it as the Twitter front end for their product, then you re gonna get promoted, right?
7
SPEAKER_00
So interesting, because from an individual perspective, how do you incentivize
7
SPEAKER_00
How do you create the kind of incentives that will lead to a great code base?
7
SPEAKER_00
OK, what s the answer to that?
7
SPEAKER_01
So what I do at Comma and at TinyCorp is you have to explain it to me.
7
SPEAKER_01
You have to explain to me what this code does.
7
SPEAKER_01
And if I can sit there and come up with a simpler way to do it, you have to rewrite it.
7
SPEAKER_01
You have to agree with me about the simpler way.
7
SPEAKER_01
Obviously, we can have a conversation about this.
7
SPEAKER_01
It s not dictatorial.
7
SPEAKER_01
But if you re like, wow, wait, that actually is way simpler.
7
SPEAKER_01
The simplicity is important, right?
7
SPEAKER_00
But that requires people that overlook the code at the highest levels to be like, OK.
7
SPEAKER_01
It requires technical leadership, you trust.
7
SPEAKER_00
Yeah, technical leadership.
7
SPEAKER_00
So managers or whatever should have to have technical savvy, deep technical savvy.
7
SPEAKER_01
Managers should be better programmers than the people who they manage.
7
SPEAKER_00
Yeah.
7
SPEAKER_00
And that s not always obvious, trivial to create, especially at large companies.
7
SPEAKER_00
Managers get soft.
7
SPEAKER_01
And like, you know, and this is just, I ve instilled this culture at Kama, and Kama has better programmers than me who work there.
7
SPEAKER_01
But, you know, again, I m like the, you know, the old guy from Good Will Hunting.
7
SPEAKER_01
It s like, look, man, you know,
7
SPEAKER_01
I might not be as good as you, but I can see the difference between me and you.
7
SPEAKER_01
And this is what you need.
7
SPEAKER_01
This is what you need at the top.
7
SPEAKER_01
Or you don t necessarily need the manager to be the absolute best.
7
SPEAKER_01
I shouldn t say that.
7
SPEAKER_01
But they need to be able to recognize skill.
7
SPEAKER_00
Yeah, and have good intuition.
7
SPEAKER_00
Intuition that s laden with wisdom from all the battles of trying to reduce complexity in codebases.
7
SPEAKER_01
You know, I took a political approach at Kama, too, that I think is pretty interesting.
7
SPEAKER_01
I think Elon takes the same political approach.
7
SPEAKER_01
You know, Google had no politics, and what ended up happening is the absolute worst kind of politics took over.
7
SPEAKER_01
Kama has an extreme amount of politics, and they re all mine, and no dissidence is tolerated.
7
SPEAKER_00
So it s a dictatorship.
7
SPEAKER_01
It s an absolute dictatorship, right?
7
SPEAKER_01
Elon does the same thing.
7
SPEAKER_01
Now, the thing about my dictatorship is here are my values.
7
SPEAKER_00
Yeah, so it s transparent.
7
SPEAKER_01
It s transparent.
7
SPEAKER_01
It s a transparent dictatorship, right?
7
SPEAKER_01
And you can choose to opt in or, you know, you get free exit, right?
7
SPEAKER_01
That s the beauty of companies.
7
SPEAKER_01
If you don t like the dictatorship, you quit.
7
SPEAKER_00
So you mentioned rewrite before or refactor before features.
7
SPEAKER_00
If you were to refactor the Twitter code base, what would that look like?
7
SPEAKER_00
And maybe also comment on how difficult is it to refactor?
7
SPEAKER_01
The main thing I would do is, first of all, identify the pieces, and then put tests in between the pieces, right?
7
SPEAKER_01
So there s all these different, Twitter has a microservice architecture, there s all these different microservices, and the thing that I was working on there, look, like, you know, George didn t know any JavaScript, he asked how to fix search, blah, blah, blah, blah, blah.
7
SPEAKER_01
The thing is, I m upset that the way that this whole thing was portrayed, because it wasn t taken by people honestly.
7
SPEAKER_01
It was taken by people who started out with a bad faith assumption.
7
SPEAKER_00
And I mean, look, I can t— And you as a programmer were just being transparent out there, actually having
7
SPEAKER_00
Like, fun, and like, this is what programming should be about.
7
SPEAKER_00
I love that Elon gave me this opportunity.
7
SPEAKER_01
Like, really, it does, and like, you know, he came on my, the day I quit, he came on my Twitter spaces afterward, and we had a conversation, like, I just, I respect that so much.
7
SPEAKER_00
Yeah.
8
SPEAKER_03
It s also inspiring to just engineers and programmers and just, it s cool, it should be fun.
8
SPEAKER_03
The people that were hating on it, it s like, oh man.
8
SPEAKER_01
It was fun.
8
SPEAKER_01
It was fun, it was stressful, but I felt like I was at a cool point in history and I hope I was useful.
8
SPEAKER_01
I probably kind of wasn t, but maybe I was.
8
SPEAKER_03
Well, you also were one of the people that kind of made a strong case to refactor.
8
SPEAKER_01
Yeah.
8
SPEAKER_03
And that s a really interesting thing to raise.
8
SPEAKER_03
Maybe that is the right, the timing of that is really interesting.
8
SPEAKER_03
If you look at just the development of autopilot, going from Mobileye to just, if you look at the history of semi-autonomous driving in Tesla, is more and more, you could say refactoring, or starting from scratch, redeveloping from scratch.
8
SPEAKER_01
It s refactoring all the way down.
8
SPEAKER_03
And like, and the question is like, can you do that sooner?
8
SPEAKER_03
Can you maintain product profitability?
8
SPEAKER_03
And like, what s the right time to do it?
8
SPEAKER_03
How do you do it?
8
SPEAKER_03
You know, on any one day, it s like, you don t want to pull off the Band-Aids.
8
SPEAKER_03
Like, it s like, everything works.
8
SPEAKER_03
It s just like little fix here and there, but maybe start it from scratch.
8
SPEAKER_01
This is the main philosophy of TinyGrad.
8
SPEAKER_01
You have never refactored enough.
8
SPEAKER_01
Your code can get smaller.
8
SPEAKER_01
Your code can get simpler.
8
SPEAKER_01
Your ideas can be more elegant.
8
SPEAKER_03
But would you consider, you know, say you were like running Twitter development teams, engineering teams, would you go as far as like different programming language?
8
SPEAKER_03
Just go that far?
8
SPEAKER_01
I mean, the first thing that I would do is build tests.
8
SPEAKER_01
The first thing I would do is get a CI to where people can trust to make changes.
8
SPEAKER_01
So that if you keep- Before I touched any code, I would actually say, no one touches any code.
8
SPEAKER_01
The first thing we do is we test this code base.
8
SPEAKER_01
I mean, this is classic.
8
SPEAKER_01
This is how you approach a legacy code base.
8
SPEAKER_01
This is like what any, how to approach a legacy code base book will tell you.
8
SPEAKER_03
So, and then you hope that there s modules that can live on for a while, and then you add new ones, maybe in a different language or- Before we add new ones, we replace old ones.
8
SPEAKER_03
Yeah, yeah, meaning like replace old ones with something simpler.
8
SPEAKER_01
We look at this thing that s 100,000 lines and we re like, well, okay, maybe this did even make sense in 2010, but now we can replace this with an open source thing, right?
8
SPEAKER_01
Yeah.
8
SPEAKER_01
And we look at this here, here s another 50,000 lines.
8
SPEAKER_01
Well, actually, we can replace this with 300 lines ago.
8
SPEAKER_01
And you know what?
8
SPEAKER_01
I trust that the Go actually replaces this thing because all the tests still pass.
8
SPEAKER_01
So step one is testing.
8
SPEAKER_01
And then step two is like, the programming language is an afterthought, right?
8
SPEAKER_01
You ll let a whole lot of people compete, be like, OK, who wants to rewrite a module, whatever language you want to write it in, just the tests have to pass.
8
SPEAKER_01
And if you figure out how to make the test pass but break the site, that s, we got to go back to step one.
8
SPEAKER_01
Step one is get tests that you trust in order to make changes in the code base.
8
SPEAKER_03
I wonder how hard it is too, because I m with you on testing and everything.
8
SPEAKER_03
You have from tests to like asserts to everything, code is just covered in this because it should be very easy to make rapid changes.
8
SPEAKER_03
and know that it s not gonna break everything.
8
SPEAKER_03
And that s the way to do it.
8
SPEAKER_03
But I wonder how difficult is it to integrate tests into a code base that doesn t have many of them.
8
SPEAKER_01
So I ll tell you what my plan was at Twitter.
8
SPEAKER_01
It s actually similar to something we use at Comma.
8
SPEAKER_01
So at Comma we have this thing called process replay.
8
SPEAKER_01
And we have a bunch of routes that ll be run through.
8
SPEAKER_01
So Calm is a microservice architecture, too, with microservices in the driving.
8
SPEAKER_01
We have one for the cameras, one for the sensor, one for the planner, one for the model.
8
SPEAKER_01
And we have an API, which the microservices talk to each other with.
8
SPEAKER_01
We use this custom thing called Serial, which uses ZMQ.
8
SPEAKER_01
Twitter uses Thrift.
8
SPEAKER_01
And then it uses this thing called Finagle, which is a Scala.
8
SPEAKER_01
RPC backend, but this doesn t even really matter.
8
SPEAKER_01
The thrift and finagle layer was a great place, I thought, to write tests, to start building something that looks like process replay.
8
SPEAKER_01
So Twitter had some stuff that looked kind of like this, but it wasn t offline, it was only online.
8
SPEAKER_01
So you could ship a modified version of it, and then you could redirect some of the traffic to your modified version and diff those two, but it was all online.
8
SPEAKER_01
There was no CI in the traditional sense.
8
SPEAKER_01
I mean, there was some, but it was not full coverage.
8
SPEAKER_03
So you can t run all of Twitter offline to test something.
8
SPEAKER_01
Well, then this was another problem.
8
SPEAKER_01
You can t run all of Twitter, right?
8
SPEAKER_01
Period.
8
SPEAKER_03
Any one person can t run it.
8
SPEAKER_01
Twitter runs in three data centers, and that s it.
8
SPEAKER_01
There s no other place you can run Twitter, which is like, George, you don t understand.
8
SPEAKER_01
This is modern software development.
8
SPEAKER_01
No, this is bullshit.
8
SPEAKER_01
Why can t it run on my laptop?
8
SPEAKER_01
Twitter can run it, yeah, okay, well, I m not saying you re gonna download the whole database to your laptop, but I m saying all the middleware and the front end should run on my laptop, right?
8
SPEAKER_03
That sounds really compelling.
8
SPEAKER_03
Yeah.
8
SPEAKER_03
but can that be achieved by a code base that grows over the years?
8
SPEAKER_03
I mean, the three data centers didn t have to be, right?
8
SPEAKER_03
Because they re totally different designs.
8
SPEAKER_01
The problem is more like, why did the code base have to grow?
8
SPEAKER_01
What new functionality has been added to compensate for the lines of code that are there?
8
SPEAKER_03
One of the ways to explain it is that the incentive for software developers to move up in the company is to add code.
8
SPEAKER_03
To add, especially large.
8
SPEAKER_01
And you know what?
8
SPEAKER_01
The incentive for politicians to move up in the political structure is to add laws.
8
SPEAKER_01
Same problem.
8
SPEAKER_03
Yeah.
8
SPEAKER_03
Yeah.
8
SPEAKER_03
If the flip side is to simplify, simplify, simplify.
8
SPEAKER_01
I mean, you know what?
8
SPEAKER_01
This is something that I do differently from Elon with Kama about self-driving cars.
8
SPEAKER_01
You know, I hear the new version s gonna come out, and the new version is not gonna be better, but at first, and it s gonna require a ton of refactors, I say, okay, take as long as you need.
8
SPEAKER_01
Like, you convince me this architecture s better?
8
SPEAKER_01
Okay, we have to move to it.
8
SPEAKER_01
Even if it s not gonna make the product better tomorrow, the top priority is getting the architecture right.
8
SPEAKER_03
So what do you think about sort of a thing where the product is online?
8
SPEAKER_03
So how, I guess, would you do a refactor?
8
SPEAKER_03
If you ran engineering on Twitter, would you just do a refactor?
8
SPEAKER_03
How long would it take?
8
SPEAKER_03
What would that mean for the running of the actual service?
8
SPEAKER_01
You know, and I m not the right person to run Twitter.
8
SPEAKER_01
I m just not.
8
SPEAKER_01
And that s the problem.
8
SPEAKER_01
Like, I don t really know.
8
SPEAKER_01
I don t really know if that s, you know, a common thing that I thought a lot while I was there was whenever I thought something that was different to what Elon thought.
8
SPEAKER_01
I d have to run something in the back of my head reminding myself that Elon is the richest man in the world.
8
SPEAKER_01
And in general, his ideas are better than mine.
8
SPEAKER_01
Now, there s a few things I think I do understand and know more about, but in general, I m not qualified to run Twitter.
8
SPEAKER_01
I was just gonna say qualified, but I don t think I d be that good at it.
8
SPEAKER_01
I don t think I d be good at it.
8
SPEAKER_01
I don t think I d really be good at running an engineering organization at scale.
8
SPEAKER_01
I think I could lead a very good refactor of Twitter, and it would take like six months to a year, and the results to show at the end of it would be feature development in general takes 10x less time, 10x less man hours.
8
SPEAKER_01
That s what I think I could actually do.
8
SPEAKER_01
Do I think that it s the right decision for the business?
8
SPEAKER_01
Above my pay grade.
8
SPEAKER_03
Yeah, but a lot of these kinds of decisions are above everybody s pay grade.
8
SPEAKER_01
I don t wanna be a manager, I don t wanna do that.
8
SPEAKER_01
If you really forced me to, yeah, it would make me maybe, make me upset if I had to make those decisions.
8
SPEAKER_01
I don t wanna.
8
SPEAKER_03
Yeah, but a refactor is so compelling.
8
SPEAKER_03
If this is to become something much bigger than what Twitter was,
8
SPEAKER_03
is it feels like a refactor has to be coming at some point.
8
SPEAKER_00
George, you re a junior software engineer.
8
SPEAKER_00
Every junior software engineer wants to come in and refactor the whole code.
8
SPEAKER_01
Okay, that s like your opinion, man.
8
SPEAKER_03
Yeah, it doesn t, you know, sometimes they re right.
8
SPEAKER_01
Well, whether they re right or not, it s definitely not for that reason.
8
SPEAKER_01
It s definitely not a question of engineering prowess.
8
SPEAKER_01
It is a question of maybe what the priorities are for the company.
8
SPEAKER_01
And I did get more intelligent feedback from people, I think, in good faith, saying that.
8
SPEAKER_01
Actually, from Elon.
8
SPEAKER_01
And from Elon, people were like, well, a stop-the-world refactor might be great for engineering, but we have a business to run.
8
SPEAKER_01
And hey, above my pay grade.
8
SPEAKER_03
What d you think about Elon as an engineering leader?
8
SPEAKER_03
Having to experience him in the most chaotic of spaces, I would say.
8
SPEAKER_01
My respect for him is unchanged.
8
SPEAKER_01
And I did have to think a lot more deeply about some of the decisions he s forced to make.
8
SPEAKER_03
About the tensions within those, the trade-offs within those decisions?
8
SPEAKER_01
About like a whole like,
8
SPEAKER_01
like matrix coming at him.
8
SPEAKER_01
I think that s Andrew Tate s word for it, sorry to borrow it.
8
SPEAKER_03
Also, bigger than engineering, just everything.
8
SPEAKER_01
Yeah, like the war on the woke.
8
SPEAKER_01
Yeah.
8
SPEAKER_01
It s just, man, and like, he doesn t have to do this, you know?
8
SPEAKER_01
He doesn t have to.
8
SPEAKER_01
He could go like Parag and go chill at the Four Seasons Maui, you know?
8
SPEAKER_01
But see, one person I respect and one person I don t.
8
SPEAKER_03
So his heart is in the right place fighting, in this case, for this ideal of the freedom of expression.
8
SPEAKER_01
I wouldn t define the ideal so simply.
8
SPEAKER_01
I think you can define the ideal no more than just saying, Elon s idea of a good world.
8
SPEAKER_03
Freedom of expression is... But to you it s still, the downsides of that is the monarchy.
8
SPEAKER_01
Yeah, I mean, monarchy has problems, right?
8
SPEAKER_01
But I mean, would I trade right now, the current oligarchy, which runs America for the monarchy?
8
SPEAKER_01
Yeah, I would, sure.
8
SPEAKER_01
For the Elon monarchy?
8
SPEAKER_01
Yeah, you know why?
8
SPEAKER_01
Because power would cost one cent a kilowatt hour, 10th of a cent a kilowatt hour.
8
SPEAKER_03
What do you mean?
8
SPEAKER_01
Right now, I pay about 20 cents a kilowatt hour for electricity in San Diego.
8
SPEAKER_01
That s like the same price you paid in 1980.
8
SPEAKER_01
What the hell?
8
SPEAKER_03
So you would see a lot of innovation with Elon.
8
SPEAKER_01
Maybe it d have some hyper loops.
8
SPEAKER_01
And I m willing to make that trade-off, right?
8
SPEAKER_01
And this is why people think that dictators take power through some untoward mechanism.
8
SPEAKER_01
Sometimes they do, but usually it s because the people want them.
8
SPEAKER_01
And the downsides of a dictatorship, I feel like we ve gotten to a point now with the oligarchy where, yeah, I would prefer the dictator.
8
SPEAKER_03
What d you think about Scala as a programming language?
8
SPEAKER_01
I liked it more than I thought.
8
SPEAKER_01
I did the tutorials.
8
SPEAKER_01
Like, I was very new to it.
8
SPEAKER_01
Like, it would take me six months to be able to write, like, good Scala.
8
SPEAKER_03
I mean, what did you learn about learning a new programming language from that?
8
SPEAKER_01
Oh, I love doing, like, new programming tutorials and doing them.
8
SPEAKER_01
I did all this for Rust.
8
SPEAKER_01
Some of it s upsetting JVM roots, but it is a much nicer... In fact, I almost don t know why Kotlin took off and not Scala.
8
SPEAKER_01
I think Scala has some beauty that Kotlin lacked, whereas Kotlin felt a lot more... I mean, I don t know if it actually was a response to Swift, but that s kind of what it felt like.
8
SPEAKER_01
Kotlin looks more like Swift, and Scala looks more like a functional programming language, more like an OCaml or a Haskell.
8
SPEAKER_03
Let s actually just explore, we touched it a little bit, but just on the art, the science and the art of programming.
8
SPEAKER_03
For you personally, how much of your programming is done with GPT currently?
8
SPEAKER_01
None.
8
SPEAKER_03
None.
8
SPEAKER_01
I use it at all.
8
SPEAKER_03
Because you prioritize simplicity so much.
8
SPEAKER_01
Yeah, I find that a lot of it is noise.
8
SPEAKER_01
I do use VS Code, and I do like some amount of autocomplete.
8
SPEAKER_01
I do like a very feels-like-rules-based autocomplete.
8
SPEAKER_01
An autocomplete is going to complete the variable name for me, so I don t have to type it, I can just press tab.
8
SPEAKER_01
That s nice.
8
SPEAKER_01
But I don t want an autocomplete.
8
SPEAKER_01
You know what I hate?
8
SPEAKER_01
When autocompletes, when I type the word for and it puts two parentheses and two semicolons and two braces, I m like,
8
SPEAKER_03
Well, I mean, with VS Code and GPT with Codex, you can kind of brainstorm.
8
SPEAKER_03
I find
8
SPEAKER_03
I m like probably the same as you, but I like that it generates code and you basically disagree with it and write something simpler.
8
SPEAKER_03
But to me, that somehow is like inspiring.
8
SPEAKER_03
It makes me feel good.
8
SPEAKER_03
It also gamifies the simplification process.
8
SPEAKER_03
Because I m like, oh yeah, you dumb AI system.
8
SPEAKER_03
You think this is the way to do it.
8
SPEAKER_03
I have a simpler thing here.
8
SPEAKER_01
It just constantly reminds me of bad stuff.
8
SPEAKER_01
I mean, I tried the same thing with rap, right?
8
SPEAKER_01
I tried the same thing with rap, and actually I think I m a much better programmer than rapper.
8
SPEAKER_01
But I even tried, I was like, OK, can we get some inspiration from these things for some rap lyrics?
8
SPEAKER_01
And I just found that it would go back to the most cringey tropes and dumb rhyme schemes.
8
SPEAKER_01
And I m like, yeah, this is what the code looks like, too.
8
SPEAKER_03
I think you and I probably have different thresholds for cringe code.
8
SPEAKER_03
You probably hate cringe code.
8
SPEAKER_03
So it s for you.
8
SPEAKER_03
Boilerplate is a part of code.
8
SPEAKER_03
Some of it is just faster lookup.
8
SPEAKER_03
Cause I don t know about you, but I don t remember everything.
8
SPEAKER_03
Like I don t, I m offloading so much of my memory about like, yeah, different functions, library functions, all that kind of stuff.
8
SPEAKER_03
Like this GPT just is very fast at standard stuff.
8
SPEAKER_03
And like standard library stuff, basic stuff that everybody uses.
8
SPEAKER_01
Yeah, I think that, I don t know.
8
SPEAKER_01
I mean, there s just so little of this in Python.
8
SPEAKER_01
Maybe if I was coding more in other languages, I would consider it more, but I feel like Python already does such a good job of removing any boilerplate.
8
SPEAKER_02
That s true.
8
SPEAKER_01
It s the closest thing you can get to pseudocode, right?
8
SPEAKER_02
Yeah, that s true.
8
SPEAKER_02
That s true.
8
SPEAKER_01
And like, yeah, sure.
8
SPEAKER_01
If I like, yeah, great GPT, thanks for reminding me to free my variables.
8
SPEAKER_01
Unfortunately, you didn t really recognize the scope correctly and you can t free that one, but like you put the freeze there and like, I get it.
8
SPEAKER_03
Fiverr, whenever I ve used Fiverr for certain things, like design or whatever, it s always, you come back, I think that s probably closer, my experience with Fiverr is closer to your experience with programming, with GPT is like, you re just frustrated and feel worse about the whole process of design and art and whatever I use Fiverr for.
8
SPEAKER_03
Still, I just feel like later versions of GPT, I m using GPT as much as possible to just learn the dynamics of it, like these early versions, because it feels like in the future, you ll be using it more and more.
8
SPEAKER_03
And so like, I don t want to be, for the same reason I gave away all my books and switched to Kindle, because like, all right,
8
SPEAKER_03
how long are we gonna have paper books?
8
SPEAKER_03
Like, 30 years from now?
8
SPEAKER_03
Like, I wanna learn to be reading on Kindle, even though I don t enjoy it as much, and you learn to enjoy it more.
8
SPEAKER_03
In the same way, I switched from, let me just pause, I switched from Emacs to VS Code.
8
SPEAKER_03
Yeah, I switched from Vim to VS Code, I think, similar, but.
8
SPEAKER_03
Yeah, it s tough, and Vim to VS Code is even tougher, because Emacs is like,
8
SPEAKER_03
old, like more outdated, feels like it.
8
SPEAKER_03
The community is more outdated.
8
SPEAKER_03
Vim is like pretty vibrant still, so.
8
SPEAKER_01
I never used any of the plugins, I still don t use any of the plugins.
8
SPEAKER_03
That s what I, I looked at myself in the mirror, I m like, yeah, you wrote some stuff in Lisp, yeah.
8
SPEAKER_01
No, but I never used any of the plugins in Vim either.
8
SPEAKER_01
I had the most vanilla Vim, I have a syntax highlighter.
8
SPEAKER_01
I didn t even have autocomplete.
8
SPEAKER_01
Like, these things, I feel like help you so marginally that, like,
8
SPEAKER_01
And now, okay, now VS Code s autocomplete has gotten good enough that like, okay, I don t have to set it up.
8
SPEAKER_01
I can just go into any code base and autocomplete s right 90% of the time.
8
SPEAKER_01
Okay, cool, I ll take it.
8
SPEAKER_01
So, I don t think I m going to have a problem at all adapting to the tools once they re good.
8
SPEAKER_01
But, like, the real thing that I want is not something that, like, tab completes my code and gives me ideas.
8
SPEAKER_01
The real thing that I want is a very intelligent pair programmer that comes up with a little pop-up saying, hey, you wrote a bug on line 14 and here s what it is.
8
SPEAKER_01
Now I like that.
8
SPEAKER_01
You know what does a good job of this?
8
SPEAKER_01
MyPy.
8
SPEAKER_01
I love MyPy.
8
SPEAKER_01
MyPy, this fancy type checker for Python.
8
SPEAKER_01
And actually I tried, like Microsoft released one too, and it was like 60% false positives.
8
SPEAKER_01
MyPy s like 5% false positives.
8
SPEAKER_01
95% of the time it recognizes, I didn t really think about that typing interaction correctly.
8
SPEAKER_01
Thank you, MyPy.
8
SPEAKER_03
So you like type hinting, you like pushing the language towards being a typed language.
8
SPEAKER_03
Oh yeah, absolutely.
9
SPEAKER_01
I think optional typing is great.
9
SPEAKER_01
I mean, look, I think that it s like a meet in the middle, right?
9
SPEAKER_01
Like Python has this optional type hinting and like C++ has auto.
9
SPEAKER_00
C++ allows you to take a step back.
9
SPEAKER_01
Well, C++ would have you brutally type out std string iterator, right?
9
SPEAKER_01
Now I can just type auto, which is nice.
9
SPEAKER_01
And then Python used to just have A. What type is A?
9
SPEAKER_01
It s an A. A colon str.
9
SPEAKER_01
Yeah.
9
SPEAKER_01
I wish there was a way, like a simple way in Python, to turn on a mode which would enforce the types.
9
SPEAKER_00
Yeah, like give a warning when there s no type or something like this.
9
SPEAKER_01
Well, no, to give a warning where, like, my Py is a static type checker, but I m asking just for a runtime type checker.
9
SPEAKER_01
Like, there s ways to hack this in, but I wish it was just like a flag, like Python 3 dash T. Oh, I see.
9
SPEAKER_01
I see.
9
SPEAKER_01
Enforce the types around time.
9
SPEAKER_00
Yeah.
9
SPEAKER_00
I feel like that makes you a better programmer.
9
SPEAKER_00
That s a kind of test, right?
9
SPEAKER_00
That the type remains the same.
9
SPEAKER_01
Well, no, that I didn t mess any types up.
9
SPEAKER_01
But again, MyPy is getting really good, and I love it.
9
SPEAKER_01
And I can t wait for some of these tools to become AI-powered.
9
SPEAKER_01
I want AIs reading my code and giving me feedback.
9
SPEAKER_01
I don t want AIs writing half-assed autocomplete stuff for me.
9
SPEAKER_00
I wonder if you can now take GPT and give it a code that you wrote for a function and say, how can I make this simpler and have it accomplish the same thing?
9
SPEAKER_00
I think you ll get some good ideas on some code.
9
SPEAKER_00
Maybe not code you write, for TinyGrad type of code, because that requires so much design thinking, but other kinds of code.
9
SPEAKER_01
I don t know.
9
SPEAKER_01
I downloaded the plugin maybe like two months ago.
9
SPEAKER_01
I tried it again and found the same.
9
SPEAKER_01
Look, I don t doubt that these models are going to first become useful to me, then be as good as me and then surpass me.
9
SPEAKER_01
But from what I ve seen today, it s like, like, like someone, you know, occasionally taking over my keyboard that I hired from Fiverr.
9
SPEAKER_01
Yeah.
9
SPEAKER_00
Ideas about how to debug the code are basically a better debugger.
9
SPEAKER_00
It s really interesting.
9
SPEAKER_00
But it s not a better debugger.
9
SPEAKER_00
I guess I would love a better debugger.
9
SPEAKER_00
Yeah, it s not yet.
9
SPEAKER_00
Yeah, but it feels like it s not too far.
9
SPEAKER_01
Yeah, one of my coworkers says he uses them for print statements.
9
SPEAKER_01
Like every time he has to like, just like when he needs, the only thing it can really write is like, okay, I just want to write the thing to like print the state out right now.
9
SPEAKER_00
Oh, that definitely is much faster.
9
SPEAKER_00
It s print statements, yeah.
9
SPEAKER_00
I see myself using that a lot, just like, because it figures out the rest of the functions.
9
SPEAKER_00
It s just like, okay, print everything.
9
SPEAKER_01
Yeah, print everything, right?
9
SPEAKER_01
And then, yeah, like if you want a pretty printer, maybe.
9
SPEAKER_01
I m like, yeah, you know what?
9
SPEAKER_01
I think in two years, I m gonna start using these plugins.
9
SPEAKER_00
Yeah.
9
SPEAKER_01
A little bit.
9
SPEAKER_01
And then in five years, I m gonna be heavily relying on some AI augmented flow.
9
SPEAKER_01
And then in 10 years,
9
SPEAKER_00
Do you think it will ever get to 100%?
9
SPEAKER_00
What s the role of the human that it converges to as a programmer?
9
SPEAKER_00
Do you think it s all generated?
9
SPEAKER_01
Our niche becomes, oh, I think it s over for humans in general.
9
SPEAKER_01
It s not just programming, it s everything.
9
SPEAKER_01
Our niche becomes smaller and smaller and smaller.
9
SPEAKER_01
In fact, I ll tell you what the last niche of humanity is gonna be.
9
SPEAKER_01
There s a great book, and it s, if I recommended Metamorphosis of Prime Intellect last time, there is a sequel called A Casino Odyssey in Cyberspace.
9
SPEAKER_01
And I don t wanna give away the ending of this, but it tells you what the last remaining human currency is, and I agree with that.
9
SPEAKER_00
We ll leave that as a cliffhanger.
9
SPEAKER_00
So no more programmers left, huh?
9
SPEAKER_00
That s where we re going.
9
SPEAKER_01
Well, unless you want handmade code.
9
SPEAKER_01
Maybe they ll sell it on Etsy.
9
SPEAKER_01
This is handwritten code.
9
SPEAKER_01
It doesn t have that machine polish to it.
9
SPEAKER_01
It has those slight imperfections that would only be written by a person.
9
SPEAKER_00
I wonder how far away we are from that.
9
SPEAKER_00
I mean, there s some aspect to, you know, on Instagram, your title is listed as prompt engineer.
9
SPEAKER_00
Right.
9
SPEAKER_02
Thank you for noticing.
9
SPEAKER_00
I don t know if it s ironic or non, or sarcastic or non.
9
SPEAKER_00
What do you think of prompt engineering as a scientific and engineering discipline, or maybe, and maybe art form?
9
SPEAKER_01
I started Kama six years ago, and I started the tiny corp a month ago.
9
SPEAKER_01
So much has changed.
9
SPEAKER_01
I m now thinking, I m now like, I started going through similar Kama processes to starting a company.
9
SPEAKER_01
I m like, okay, I m going to get an office in San Diego, I m going to bring people here.
9
SPEAKER_01
I don t think so.
9
SPEAKER_01
I think I m actually going to do remote.
9
SPEAKER_01
George, you re going to do remote?
9
SPEAKER_01
You hate remote.
9
SPEAKER_01
Yeah, but I m not going to do job interviews.
9
SPEAKER_01
The only way you re going to get a job is if you contribute to the GitHub.
9
SPEAKER_01
Interacting through GitHub, GitHub being the real project management software for your company, the thing pretty much just is a GitHub repo.
9
SPEAKER_01
is like showing me kind of what the future of, okay, so a lot of times I ll go on a Discord, or kind of go on Discord, and I ll throw out some random, like, hey, you know, can you change, instead of having log and exp as LL ops, change it to log two and exp two?
9
SPEAKER_01
It s a pretty small change.
9
SPEAKER_01
You can just use like change your base formula.
9
SPEAKER_01
That s the kind of task that I can see an AI being able to do in a few years.
9
SPEAKER_01
In a few years, I could see myself describing that, and then within 30 seconds, a pull request is up the dozen.
9
SPEAKER_01
And it passes my CI and I merge it.
9
SPEAKER_01
So I really started thinking about, well, what is the future of jobs?
9
SPEAKER_01
How many AIs can I employ at my company?
9
SPEAKER_01
As soon as we get the first tiny box up, I m going to stand up a 65B llama in the Discord.
9
SPEAKER_01
And it s like, yeah, here s the tiny box.
9
SPEAKER_01
He s just like, he s chilling with us.
9
SPEAKER_00
Basically, like you said with niches, most human jobs will eventually be replaced with prompt engineering.
9
SPEAKER_01
Well, prompt engineering kind of is this like...
9
SPEAKER_01
as you like move up the stack, right?
9
SPEAKER_01
Like, okay, there used to be humans actually doing arithmetic by hand.
9
SPEAKER_01
There used to be like big farms of people doing pluses and stuff, right?
9
SPEAKER_01
And then you have like spreadsheets, right?
9
SPEAKER_01
And then, okay, the spreadsheet can do the plus for me.
9
SPEAKER_01
And then you have like macros, right?
9
SPEAKER_01
And then you have like things that basically just are spreadsheets under the hood, right?
9
SPEAKER_01
Like accounting software.
9
SPEAKER_01
As we move further up the abstraction, well, what s at the top of the abstraction stack?
9
SPEAKER_01
Yeah.
9
SPEAKER_01
What is the last thing if you think about humans wanting to keep control?
9
SPEAKER_01
Well, what am I really in the company but a prompt engineer, right?
9
SPEAKER_00
Isn t there a certain point where the AI will be better at writing prompts?
9
SPEAKER_01
Yeah, but you see the problem with the AI writing prompts, a definition that I always liked of AI was AI is the do what I mean machine.
9
SPEAKER_01
AI is not the, like the computer is so pedantic.
9
SPEAKER_01
It does what you say.
9
SPEAKER_01
So, but you want the do what I mean machine.
9
SPEAKER_01
You want the machine where you say, you know, get my grandmother out of the burning house.
9
SPEAKER_01
It like reasonably takes your grandmother and puts her on the ground, not lifts her a thousand feet above the burning house and lets her fall.
9
SPEAKER_00
There s an old Yudkowsky example.
9
SPEAKER_00
It s not going to find the meaning.
9
SPEAKER_00
I mean, to do what I mean, it has to figure stuff out.
9
SPEAKER_00
And the thing you ll maybe ask it to do is run government for me.
9
SPEAKER_01
Oh, and do what I mean very much comes down to how aligned is that AI with you.
9
SPEAKER_01
Of course, when you talk to an AI that s made by a big company in the cloud, the AI fundamentally is aligned to them, not to you.
9
SPEAKER_01
And that s why you have to buy a tiny box, so you make sure the AI stays aligned to you.
9
SPEAKER_01
Every time that they start to pass AI regulation or GPU regulation, I m going to see sales of tiny boxes spike.
9
SPEAKER_01
It s going to be like guns.
9
SPEAKER_01
Every time they talk about gun regulation, boom.
9
SPEAKER_01
Gun sales.
9
SPEAKER_00
So in the space of AI, you re an anarchist.
9
SPEAKER_00
Anarchism, espouser, believer.
9
SPEAKER_01
I m an informational anarchist, yes.
9
SPEAKER_01
I m an informational anarchist and a physical statist.
9
SPEAKER_01
I do not think anarchy in the physical world is very good, because I exist in the physical world.
9
SPEAKER_01
But I think we can construct this virtual world where anarchy, it can t hurt you, right?
9
SPEAKER_01
I love that Tyler, the creator, tweet.
9
SPEAKER_01
Yo, cyberbullying isn t real, man.
9
SPEAKER_01
Have you tried?
9
SPEAKER_01
Turn it off the screen.
9
SPEAKER_01
Close your eyes.
9
SPEAKER_00
Yeah.
9
SPEAKER_00
But how do you prevent the AI from basically replacing all human prompt engineers?
9
SPEAKER_00
It s like a self, like where nobody s the prompt engineer anymore, so autonomy, greater and greater autonomy until it s full autonomy.
9
SPEAKER_00
And that s just where it s headed.
9
SPEAKER_00
Because one person s gonna say, run everything for me.
9
SPEAKER_01
You see?
9
SPEAKER_01
I look at potential futures, and as long as the AIs go on to create a vibrant civilization with diversity and complexity across the universe, more power to them.
9
SPEAKER_01
I ll die.
9
SPEAKER_01
If the AIs go on to actually turn the world into paperclips and then they die out themselves, well, that s horrific and we don t want that to happen.
9
SPEAKER_01
So this is what I mean about robustness.
9
SPEAKER_01
I trust robust machines.
9
SPEAKER_01
The current AIs are so not robust.
9
SPEAKER_01
This comes back to the idea that we ve never made a machine that can self-replicate.
9
SPEAKER_01
But if the machines are truly robust and there is one prompt engineer left in the world,
9
SPEAKER_01
hope you re doing good, man, hope you believe in God, like, you know, go by God and go forth and conquer the universe.
9
SPEAKER_00
Well, you mentioned, because I talked to Mark about faith in God, and you said you were impressed by that.
9
SPEAKER_00
What s your own belief in God, and how does that affect your work?
9
SPEAKER_01
You know, I never really considered when I was younger, I guess, my parents were atheists, so I was raised kind of atheist.
9
SPEAKER_01
I never really considered how absolutely silly atheism is.
9
SPEAKER_01
I create worlds.
9
SPEAKER_01
Every game creator, like, how are you an atheist, bro?
9
SPEAKER_01
You create worlds.
9
SPEAKER_01
No one created art worlds, man.
9
SPEAKER_01
That s different.
9
SPEAKER_01
Haven t you heard about the Big Bang and stuff?
9
SPEAKER_01
Yeah, I mean, what s the Skyrim myth origin story in Skyrim?
9
SPEAKER_01
I m sure there s some part of it in Skyrim, but it s not like if you ask the creators.
9
SPEAKER_01
The Big Bang is in universe, right?
9
SPEAKER_01
I m sure they have some Big Bang notion in Skyrim, right?
9
SPEAKER_01
But that obviously is not at all how Skyrim was actually created.
9
SPEAKER_01
It was created by a bunch of programmers in a room, right?
9
SPEAKER_01
So like, you know, it just, it struck me one day how just silly atheism is, right?
9
SPEAKER_01
Like, of course we were created by God.
9
SPEAKER_01
It s the most obvious thing.
9
SPEAKER_00
Yeah.
9
SPEAKER_00
That s, uh, that s such a nice way to put it.
9
SPEAKER_00
Like we re, we re such powerful creators ourselves.
9
SPEAKER_00
It, uh, it s silly not to conceive that there s creators even more powerful than us.
9
SPEAKER_01
Yeah.
9
SPEAKER_01
And then like, I also just like, I like that notion.
9
SPEAKER_01
That notion gives me a lot of, I mean, I guess you can talk about what it gives a lot of religious people.
9
SPEAKER_01
It s kind of like, it just gives me comfort.
9
SPEAKER_01
It s like, you know what?
9
SPEAKER_01
If we mess it all up and we die out, yeah.
9
SPEAKER_00
Yeah, in the same way that a video game kind of has comfort in it.
9
SPEAKER_00
God, I ll try again.
9
SPEAKER_00
Or there s balance, like somebody figured out a balanced view of it.
9
SPEAKER_00
So it all makes sense in the end.
9
SPEAKER_00
A video game is usually not gonna have crazy, crazy stuff.
9
SPEAKER_01
People will come up with, well yeah, but man, who created God?
9
SPEAKER_01
I m like, that s God s problem.
9
SPEAKER_01
I m not gonna think this is,
9
SPEAKER_01
You re asking me what, if God believes in God?
9
SPEAKER_00
I m just this NPC living in this game.
9
SPEAKER_01
I mean, to be fair, if God didn t believe in God, he d be as silly as the atheists here.
9
SPEAKER_00
What do you think is the greatest computer game of all time?
9
SPEAKER_00
Do you have any time to play games anymore?
9
SPEAKER_00
Have you played Diablo 4?
9
SPEAKER_01
I have not played Diablo 4.
9
SPEAKER_00
I will be doing that shortly.
9
SPEAKER_00
I have to.
9
SPEAKER_01
All right.
9
SPEAKER_00
There s just so much history with 1, 2, and 3.
9
SPEAKER_00
You know what?
9
SPEAKER_01
I m going to say World of Warcraft.
9
SPEAKER_01
And it s not that the game is such a great game.
9
SPEAKER_01
It s not.
9
SPEAKER_01
It s that I remember in 2005 when it came out, how it opened my mind to ideas.
9
SPEAKER_01
It opened my mind to this whole world we ve created.
9
SPEAKER_01
There s almost been nothing like it since.
9
SPEAKER_01
Like, you can look at MMOs today, and I think they all have lower user bases than World of Warcraft.
9
SPEAKER_01
Like, EVE Online s kind of cool.
9
SPEAKER_01
But to think that, like, everyone knows, you know, people are always like, if you look at the Apple headset, like, what do people want in this VR?
9
SPEAKER_01
Everyone knows what they want.
9
SPEAKER_01
I want Ready Player One.
9
SPEAKER_01
And like that, so I m gonna say World of Warcraft, and I m hoping that games can get out of this whole mobile gaming dopamine pump thing, and like.
9
SPEAKER_00
Create worlds.
9
SPEAKER_00
Create worlds, yeah.
9
SPEAKER_00
And worlds that captivate a very large fraction of the human population.
9
SPEAKER_01
Yeah, and I think it ll come back, I believe.
9
SPEAKER_00
But MMO, like really, really pull you in.
9
SPEAKER_01
Games do a good job, I mean, okay, other, like two other games that I think are very noteworthy for me are Skyrim and GTA V.
9
SPEAKER_00
Skyrim, yeah, that s probably number one for me.
9
SPEAKER_00
GTA, yeah, what is it about GTA?
9
SPEAKER_00
GTA is really, I guess GTA is real life.
9
SPEAKER_00
I know there s prostitutes and guns and stuff.
9
SPEAKER_02
They exist in real life too.
9
SPEAKER_00
Yes, I know, but it s how I imagine your life to be actually.
9
SPEAKER_02
I wish it was that cool.
9
SPEAKER_00
Yeah.
9
SPEAKER_00
Yeah, I guess that s, you know, because there s Sims, right, which is also a game I like, but it s a gamified version of life, but it also is, I would love a combination of Sims and GTA.
9
SPEAKER_00
So more freedom, more violence, more rawness, but with also like ability to have a career and family and this kind of stuff.
9
SPEAKER_01
What I m really excited about in games is like once we start getting intelligent AIs to interact with.
9
SPEAKER_00
Oh yeah.
9
SPEAKER_01
Right, like the NPCs in games have never been.
9
SPEAKER_00
But conversationally, in every way.
9
SPEAKER_01
In like, yeah, in like every way.
9
SPEAKER_01
Like when you re actually building a world and a world imbued with intelligence.
9
SPEAKER_01
Oh yeah.
9
SPEAKER_01
Right?
9
SPEAKER_01
And it s just hard, like, there s just like, you know, running World of Warcraft, like, you re limited by what you re running on a Pentium 4, you know?
9
SPEAKER_01
How much intelligence can you run?
9
SPEAKER_01
How many flops did you have?
9
SPEAKER_01
Right?
9
SPEAKER_01
But now when I m running a game on a hundred pay-to-flop machine, well, that s five people.
9
SPEAKER_01
I m trying to make this a thing.
9
SPEAKER_01
20 petaflops of compute is one person of compute.
9
SPEAKER_01
I m trying to make that a unit.
9
SPEAKER_00
20 petaflops is one person.
9
SPEAKER_00
One person.
9
SPEAKER_00
One person flop.
9
SPEAKER_01
It s like a horsepower.
9
SPEAKER_01
What s a horsepower?
9
SPEAKER_01
It s how powerful a horse is.
9
SPEAKER_01
What s a person of compute?
9
SPEAKER_01
Well, you know.
9
SPEAKER_00
I got it.
9
SPEAKER_00
That s interesting.
9
SPEAKER_00
VR also has, I mean, in terms of creating worlds.
9
SPEAKER_01
You know what?
9
SPEAKER_01
Border Quest 2.
9
SPEAKER_01
I put it on, and I can t believe the first thing they show me is a bunch of scrolling clouds and a Facebook login screen.
9
SPEAKER_01
You had the ability to bring me into a world.
9
SPEAKER_01
And what did you give me?
9
SPEAKER_01
A pop-up, right?
9
SPEAKER_01
And this is why you re not cool, Mark Zuckerberg.
9
SPEAKER_01
But you could be cool.
9
SPEAKER_01
Just make sure on the Quest 3, you don t put me into clouds and a Facebook login screen.
9
SPEAKER_01
Bring me to a world.
9
SPEAKER_00
I just tried Quest 3.
9
SPEAKER_00
It was awesome.
9
SPEAKER_00
But hear that, guys?
9
SPEAKER_00
I agree with that.
9
SPEAKER_01
It was just so much fun.
9
SPEAKER_00
You know what, because I mean the beginning, what is it, Todd Howard said this about designing the beginning of the games he creates, it s like the beginning is so, so, so important.
9
SPEAKER_00
I recently played Zelda for the first time, Zelda Breath of the Wild, the previous one.
9
SPEAKER_00
And like it s very quickly, you come out of this, within like 10 seconds you come out of like a cave type place and it s like this world opens up.
9
SPEAKER_00
And it like, it pulls you in.
9
SPEAKER_00
You forget whatever troubles I was having, whatever like.
9
SPEAKER_01
I gotta play that from the beginning.
9
SPEAKER_01
I played it for like an hour at a friend s house.
9
SPEAKER_00
Ah, no, the beginning, they got it.
9
SPEAKER_00
They did it really well.
9
SPEAKER_00
The expansiveness of that space, the peacefulness of that place, they got this, the music, I mean, so much of that is creating that world and pulling you right in.
9
SPEAKER_02
I m gonna go buy a Switch.
9
SPEAKER_02
I m gonna go today and buy a Switch.
9
SPEAKER_00
You should.
9
SPEAKER_00
Well, the new one came out, I haven t played that yet, but Diablo 4 or something.
9
SPEAKER_00
I mean, there s sentimentality also, but something about VR.
9
SPEAKER_00
Really is incredible.
9
SPEAKER_00
But the the new quest 3 is mixed reality and I got a chance to try that so it s Augmented reality and for video games.
9
SPEAKER_01
It s done really really well cameras cameras Yeah, the Apple one is that one passed through our cameras.
9
SPEAKER_00
I don t know.
9
SPEAKER_00
Yeah, I don t know how real it is I don t know anything, you know coming out in January
9
SPEAKER_00
Is it January or is it some point?
10
SPEAKER_01
endeavor you re the meme oh yes I support competition it seemed like quest was like the only people doing it and this is great that they re like you know what and this is another place we ll give some more respect to Mark Zuckerberg the two companies that have endured through technology or Apple and Microsoft and what do they make computers and business services all the memes social ads they all come and go mm-hmm but you want to endure build hardware
10
SPEAKER_02
Yeah, and that does a really interesting job.
10
SPEAKER_02
Maybe I m a noob at this, but it s a $500 headset, Quest 3, and just having creatures run around the space, like our space right here, to me, okay, this is very Boomer statement, but it added windows.
10
SPEAKER_02
to the place.
10
SPEAKER_00
I heard about the aquarium, yeah.
10
SPEAKER_02
Yeah, aquarium, but in this case it was a zombie game, whatever, it doesn t matter.
10
SPEAKER_02
But just like, it modifies the space in a way where I can t, it really feels like a window and you can look out.
10
SPEAKER_02
It s pretty cool, like I was just, it s like a zombie game, they re running at me, whatever, but what I was enjoying is the fact that there s like a window and they re stepping on objects in this space
10
SPEAKER_02
That was a different kind of escape.
10
SPEAKER_02
Also because you can see the other humans.
10
SPEAKER_02
So it s integrated with the other humans.
10
SPEAKER_02
It s really, really interesting.
10
SPEAKER_01
And that s why it s more important than ever that the AI is running on those systems are aligned with you.
10
SPEAKER_01
Oh yeah.
10
SPEAKER_01
They re gonna augment your entire world.
10
SPEAKER_01
Oh yeah.
10
SPEAKER_02
And that, those AIs have a, I mean you think about all the dark stuff.
10
SPEAKER_02
Like sexual stuff.
10
SPEAKER_02
Like if those AIs threaten me, that could be haunting.
10
SPEAKER_02
Like if they, like thread me in a non-video game way.
10
SPEAKER_02
It s like, oh yeah, yeah, yeah, yeah, yeah.
10
SPEAKER_02
Like they know personal information about me.
10
SPEAKER_02
And it s like, and then you lose track of what s real, what s not.
10
SPEAKER_02
Like what if stuff is like hacked.
10
SPEAKER_01
There s two directions the AI girlfriend company can take, right?
10
SPEAKER_01
There s like the highbrow, something like her.
10
SPEAKER_01
Maybe something you kind of talk to and this is, and then there s the lowbrow version of it where I want to set up a brothel in Times Square.
10
SPEAKER_02
Yeah.
10
SPEAKER_01
Yeah.
10
SPEAKER_01
It s not cheating if it s a robot.
10
SPEAKER_01
It s a VR experience.
10
SPEAKER_02
Is there an in-between?
10
SPEAKER_02
No.
10
SPEAKER_01
I don t wanna do that one or that one.
10
SPEAKER_01
Have you decided yet?
10
SPEAKER_01
No, I ll figure it out.
10
SPEAKER_01
We ll see what the technology goes.
10
SPEAKER_02
I would love to hear your opinions for George s third company, what to do, the brothel in Times Square or the Hurt Experience.
10
SPEAKER_02
What do you think company number four will be?
10
SPEAKER_02
You think there ll be a company number four?
10
SPEAKER_01
There s a lot to do in company number two.
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SPEAKER_01
I m just like, I m talking about company number three now.
10
SPEAKER_01
None of that tech exists yet.
10
SPEAKER_01
There s a lot to do in company number two.
10
SPEAKER_01
Company number two is going to be the great struggle of the next six years.
10
SPEAKER_01
And of the next six years, how centralized is compute going to be?
10
SPEAKER_01
The less centralized compute is going to be, the better of a chance we all have.
10
SPEAKER_02
So you re bearing, you re like a flag bearer for open source distributed decentralization of compute.
10
SPEAKER_01
We have to, we have to, or they will just completely dominate us.
10
SPEAKER_01
I showed a picture on stream of a man in a chicken farm.
10
SPEAKER_01
You ever seen one of those like factory farm chicken farms?
10
SPEAKER_01
Why does he dominate all the chickens?
10
SPEAKER_01
Why does he- Smarter.
10
SPEAKER_01
He s smarter, right?
10
SPEAKER_01
Some people on Twitch were like, he s bigger than the chickens.
10
SPEAKER_01
Yeah, and now here s a man in a cow farm, right?
10
SPEAKER_01
So it has nothing to do with their size and everything to do with their intelligence.
10
SPEAKER_01
And if one central organization has all the intelligence, you ll be the chickens and they ll be the chicken man.
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SPEAKER_01
But if we all have the intelligence, we re all the chickens.
10
SPEAKER_01
We re not all the man, we re all the chickens.
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SPEAKER_01
And there s no chicken man.
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SPEAKER_02
There s no chicken man.
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Or just chickens in Miami.
10
SPEAKER_00
He was having a good life, man.
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SPEAKER_02
I m sure he was.
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SPEAKER_02
I m sure he was.
10
SPEAKER_02
What have you learned from launching and running CalmAI and TinyCorp?
10
SPEAKER_02
starting a company from an idea and scaling it.
10
SPEAKER_02
And by the way, I m all in on tiny box.
10
SPEAKER_02
So I m your, I guess it s pre-order only now.
10
SPEAKER_01
I want to make sure it s good.
10
SPEAKER_01
I want to make sure that like the thing that I deliver is like not going to be like a quest two, which you buy and use twice.
10
SPEAKER_01
I mean, it s better than a quest, which you bought and used less than once statistically.
10
SPEAKER_02
Well, if there s a beta program for a tiny box, I m into.
10
SPEAKER_01
Sounds good.
10
SPEAKER_02
So I won t be the whiny, I ll be the tech-savvy user of the tiny box, just to be in the early days.
10
SPEAKER_01
What have I learned?
10
SPEAKER_02
What have you learned from building these companies?
10
SPEAKER_01
The longest time at Kama I asked why, why did I start a company, why did I do this?
10
SPEAKER_01
You know, what else was I gonna do?
10
SPEAKER_02
So you re like,
10
SPEAKER_02
You like bringing ideas to life.
10
SPEAKER_01
With Kama, it really started as an ego battle with Elon.
10
SPEAKER_01
I wanted to beat him.
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SPEAKER_01
I saw a worthy adversary.
10
SPEAKER_01
Here s a worthy adversary who I can beat at self-driving cars.
10
SPEAKER_01
And I think we ve kept pace, and I think he s kept ahead.
10
SPEAKER_01
I think that s what s ended up happening there.
10
SPEAKER_01
But I do think Kama is, I mean, Kama s profitable.
10
SPEAKER_01
And like when this drive GPT stuff starts working, that s it.
10
SPEAKER_01
There s no more like bugs in the loss function.
10
SPEAKER_01
Like right now we re using like a hand-coded simulator.
10
SPEAKER_01
There s no more bugs.
10
SPEAKER_01
This is gonna be it.
10
SPEAKER_01
Like this is the run-up to driving.
10
SPEAKER_02
I hear a lot of really, a lot of props for OpenPILOT for a comma.
10
SPEAKER_01
It s so, it s better than FSD and Autopilot in certain ways.
10
SPEAKER_01
It has a lot more to do with which feel you like.
10
SPEAKER_01
We lowered the price on the hardware to $14.99.
10
SPEAKER_01
You know how hard it is to ship reliable consumer electronics that go on your windshield?
10
SPEAKER_01
We re doing more than like most cell phone companies.
10
SPEAKER_02
How d you pull that off, by the way, shipping a product that goes in a car?
10
SPEAKER_01
I know.
10
SPEAKER_01
I have an SMT line.
10
SPEAKER_01
I make all the boards in-house in San Diego.
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SPEAKER_02
Quality control.
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SPEAKER_02
I care immensely about it.
10
SPEAKER_02
You re basically a mom and pop shop with great testing.
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SPEAKER_01
Our head of open pilot is great at like, you know, okay, I want all the commentaries to be identical.
10
SPEAKER_01
Yeah.
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SPEAKER_01
And yeah, I mean, you know, look, it s $14.99.
10
SPEAKER_01
30-day money-back guarantee.
10
SPEAKER_01
It will blow your mind at what it can do.
10
SPEAKER_01
Is it hard to scale?
10
SPEAKER_01
You know what?
10
SPEAKER_01
There s kind of downsides to scaling it.
10
SPEAKER_01
People are always like, why don t you advertise?
10
SPEAKER_01
Our mission is to solve self-driving cars while delivering shippable intermediaries.
10
SPEAKER_01
Our mission has nothing to do with selling a million boxes.
10
SPEAKER_01
It s tawdry.
10
SPEAKER_02
Do you think it s possible that Kama gets sold?
10
SPEAKER_01
only if I felt someone could accelerate that mission and wanted to keep it open source.
10
SPEAKER_01
And like, not just wanted to, I don t believe what anyone says, I believe incentives.
10
SPEAKER_01
If a company wanted to buy Kama with their incentives or to keep it open source, but Kama doesn t stop at the cars.
10
SPEAKER_01
The cars are just the beginning.
10
SPEAKER_01
The device is a human head.
10
SPEAKER_01
The device has two eyes, two ears, it breathes air, it has a mouth.
10
SPEAKER_02
So you think this goes to embodied robotics?
10
SPEAKER_01
We sell Kama bodies too.
10
SPEAKER_01
They re very rudimentary.
10
SPEAKER_01
But one of the problems that we re running into is that the comma three has about as much intelligence as a B. If you want a human s worth of intelligence, you re gonna need a tiny rack, not even a tiny box.
10
SPEAKER_01
You re gonna need a tiny rack, maybe even more.
10
SPEAKER_02
How do you put legs on that?
10
SPEAKER_01
you don t, and there s no way you can.
10
SPEAKER_01
You connect to it wirelessly.
10
SPEAKER_01
So you put your tiny box or your tiny rack in your house, and then you get your CommaBody, and your CommaBody runs the models on that.
10
SPEAKER_01
It s close, right?
10
SPEAKER_01
You don t have to go to some cloud which is, you know, 30 milliseconds away.
10
SPEAKER_01
You go to a thing which is 0.1 milliseconds away.
10
SPEAKER_02
So the AI girlfriend will have like a central hub in the home.
10
SPEAKER_01
I mean, eventually, if you fast forward 20, 30 years, the mobile chips will get good enough to run these AIs.
10
SPEAKER_01
But fundamentally, it s not even a question of putting legs on a tiny box, because how are you getting 1.5 kilowatts of power on that thing, right?
10
SPEAKER_01
So you need, they re very synergistic businesses.
10
SPEAKER_01
I also wanna build all of Kama s training computers.
10
SPEAKER_01
Kama builds training computers right now we use.
10
SPEAKER_01
commodity parts, I think I can do it cheaper.
10
SPEAKER_01
So we re gonna build, TinyCorp is gonna not just sell TinyBoxes, TinyBoxes the consumer version, but I ll build training data centers too.
10
SPEAKER_02
Have you talked to Andrej Karpathy or have you talked to Elon about TinyCorp?
10
SPEAKER_01
He went to work at OpenAI.
10
SPEAKER_02
What do you love about Andrej Karpathy?
10
SPEAKER_02
To me, he s one of the truly special humans we got.
10
SPEAKER_01
Oh man, like, you know, his streams are just a level of quality so far beyond mine.
10
SPEAKER_01
myself like it s just it s just you know yeah he s good he wants to teach you yeah I want to show you that I m smarter than you
10
SPEAKER_02
Yeah, he has no, I mean, thank you for the sort of, the raw, authentic honesty.
10
SPEAKER_02
I mean, a lot of us have that.
10
SPEAKER_02
I think Andre is as legit as it gets in that he just wants to teach you and there s a curiosity that just drives him.
10
SPEAKER_02
And just like at his, at the stage where he is in life, to be still like one of the best tinkerers in the world, it s crazy.
10
SPEAKER_02
Like to, what is it, Michael Grad?
10
SPEAKER_01
My career was good.
10
SPEAKER_01
Inspiration for TinyGrad.
10
SPEAKER_01
The whole, I mean, his CS231N was, this was the inspiration.
10
SPEAKER_01
This is what I just took and ran with and ended up writing this.
10
SPEAKER_01
So, you know.
10
SPEAKER_01
But I mean, to me that... Don t go work for Darth Vader, man.
10
SPEAKER_02
I mean, the flip side to me is that the fact that he s going there is a good sign for open AI.
10
SPEAKER_02
I think, you know, I like Alias Discover a lot.
10
SPEAKER_02
I like those, those guys are really good at what they do.
10
SPEAKER_01
I know they are, and that s kind of what s even like more, and you know what?
10
SPEAKER_01
It s not that open AI doesn t open source the weights of GPT-4.
10
SPEAKER_01
It s that they go in front of Congress.
10
SPEAKER_01
And that is what upsets me.
10
SPEAKER_01
You know, we had two effective altruist Sams go in front of Congress.
10
SPEAKER_01
One s in jail.
10
SPEAKER_02
I think you re drawing parallels on that.
10
SPEAKER_01
One s in jail.
10
SPEAKER_02
You re giving me a look.
10
SPEAKER_01
Give me a look.
10
SPEAKER_01
No, I think effective altruism is a terribly evil ideology.
10
SPEAKER_02
Oh yeah, that s interesting.
10
SPEAKER_02
Why do you think that is?
10
SPEAKER_02
Why do you think there s something about a thing that sounds pretty good that kind of gets us into trouble?
10
SPEAKER_01
because you get Sandbag Manfreed.
10
SPEAKER_01
Like Sandbag Manfreed is the embodiment of effective altruism.
10
SPEAKER_01
Utilitarianism is an abhorrent ideology.
10
SPEAKER_01
Like, well yeah, we re gonna kill those three people to save a thousand, of course.
10
SPEAKER_01
There s no underlying, like there s just, yeah.
10
SPEAKER_02
Yeah, but to me that s a bit surprising.
10
SPEAKER_02
But it s also, in retrospect, not that surprising.
10
SPEAKER_02
But I haven t heard really clear kind of,
10
SPEAKER_02
like rigorous analysis why effective altruism is flawed.
10
SPEAKER_01
Oh, well, I think charity is bad, right?
10
SPEAKER_01
So what is charity but investment that you don t expect to have a return on, right?
10
SPEAKER_02
Yeah, but you can also think of charity as like, as you would like to see, so allocate resources in an optimal way to make a better world.
10
SPEAKER_01
And probably almost always that involves starting a company.
10
SPEAKER_01
Right, because.
10
SPEAKER_01
More efficient.
10
SPEAKER_01
Yeah, if you just take the money and you spend it on malaria nets, you know, okay, great, you ve made 100 malaria nets, but if you teach.
10
SPEAKER_02
Yeah, no matter how efficient.
10
SPEAKER_02
Right, yeah.
10
SPEAKER_02
No, but the problem is teaching no matter how efficient might be harder.
10
SPEAKER_02
Starting a company might be harder than allocating money that you already have.
10
SPEAKER_01
I like the flip side of effective altruism, effective accelerationism.
10
SPEAKER_01
I think accelerationism is the only thing that s ever lifted people out of poverty.
10
SPEAKER_01
The fact that food is cheap.
10
SPEAKER_01
Not we re giving food away because we are kind-hearted people.
10
SPEAKER_01
No, food is cheap.
10
SPEAKER_01
And that s the world you want to live in.
10
SPEAKER_01
UBI, what a scary idea.
10
SPEAKER_01
What a scary idea.
10
SPEAKER_01
All your power now?
10
SPEAKER_01
Your money is power?
10
SPEAKER_01
Your only source of power is granted to you by the goodwill of the government?
10
SPEAKER_01
What a scary idea.
10
SPEAKER_02
So you even think long-term?
10
SPEAKER_01
I d rather die than need UBI to survive, and I mean it.
10
SPEAKER_02
What if survival is basically guaranteed?
10
SPEAKER_02
What if our life becomes so good?
10
SPEAKER_01
You can make survival guaranteed without UBI.
10
SPEAKER_01
What you have to do is make housing and food dirt cheap.
10
SPEAKER_01
And that s the good world.
10
SPEAKER_01
And actually, let s go into what we should really be making dirt cheap, which is energy.
10
SPEAKER_01
That energy, that, you know, oh my God, like, you know, that s, if there s one, I m pretty centrist politically, if there s one political position I cannot stand, it s deceleration.
10
SPEAKER_01
It s people who believe we should use less energy.
10
SPEAKER_01
Not people who believe global warming is a problem, I agree with you.
10
SPEAKER_01
Not people who believe that, you know, saving the environment is good, I agree with you.
10
SPEAKER_01
But people who think we should use less energy, that energy usage is a moral bad, no.
10
SPEAKER_01
No, you are asking, you are diminishing humanity.
10
SPEAKER_02
Yeah, energy is flourishing, a creative flourishing of the human species.
10
SPEAKER_01
How do we make more of it?
10
SPEAKER_01
How do we make it clean and how do we make, just, just, just, how do I pay 20 cents for a megawatt hour instead of a kilowatt hour?
10
SPEAKER_02
Part of me wishes that Elon went into nuclear fusion versus Twitter, part of me.
10
SPEAKER_02
Or somebody, somebody like Elon.
10
SPEAKER_01
You know, we need to,
10
SPEAKER_01
I wish there were more Elons in the world.
10
SPEAKER_01
I think Elon sees it as like, this is a political battle that needed to be fought.
10
SPEAKER_01
And again, like, you know, I always ask the question of whenever I disagree with him, I remind myself that he s a billionaire and I m not.
10
SPEAKER_01
So, you know, maybe he s got something figured out that I don t, or maybe he doesn t.
10
SPEAKER_02
To have some humility, but at the same time, me as a person who happens to know him, I find myself in that same position.
10
SPEAKER_02
Sometimes even billionaires need friends who disagree and help them grow.
10
SPEAKER_02
And that s a difficult reality.
10
SPEAKER_01
And it must be so hard.
10
SPEAKER_02
It must be so hard to meet people once you get to that point where... Fame, power, money, everybody s sucking up to you.
10
SPEAKER_01
See, I love not having shit.
10
SPEAKER_01
Like I don t have shit, man.
10
SPEAKER_01
Trust me, there s nothing I can give you.
10
SPEAKER_01
There s nothing worth taking from me, you know?
10
SPEAKER_02
Yeah, it takes a really special human being, when you have power, when you have fame, when you have money, to still think from first principles.
10
SPEAKER_02
Not like all the adoration you get towards you, all the admiration, all the people saying yes, yes, yes.
10
SPEAKER_01
And all the hate, too.
10
SPEAKER_01
And the hate.
10
SPEAKER_01
I haven t got the words.
10
SPEAKER_02
So the hate makes you want to go to the yes people, because the hate exhausts you.
10
SPEAKER_02
And the kind of hate that Elon s gotten from the left is pretty intense.
10
SPEAKER_02
And so that, of course, drives him right.
10
SPEAKER_00
And it loses balance and... And it keeps this absolutely fake, like, PSYOP political divide alive so that the 1% can keep power, like... Yeah.
10
SPEAKER_02
I wish we d be less divided, because it is giving power.
10
SPEAKER_02
It gives power.
10
SPEAKER_02
To the ultra-powerful.
10
SPEAKER_02
The rich get richer.
10
SPEAKER_02
You have love in your life.
10
SPEAKER_02
Has love made you a better or a worse programmer?
10
SPEAKER_02
Do you keep productivity metrics?
10
SPEAKER_01
No, no.
10
SPEAKER_01
No, I m not that methodical.
10
SPEAKER_01
I think that there comes to a point where if it s no longer visceral, I just can t enjoy it.
10
SPEAKER_01
I still viscerally love programming.
10
SPEAKER_02
The minute I started like.
10
SPEAKER_02
So that s one of the big loves of your life is programming.
10
SPEAKER_01
I mean, just my computer in general.
10
SPEAKER_01
I tell my girlfriend, my first love is my computer, of course.
10
SPEAKER_01
I sleep with my computer.
10
SPEAKER_01
It s there for a lot of my sexual experiences.
10
SPEAKER_01
Come on, so is everyone s, right?
10
SPEAKER_01
You gotta be real about that.
10
SPEAKER_02
Not just the IDE for programming, just the entirety of the computational machine.
10
SPEAKER_01
The fact that, yeah, I mean, it s, you know, I wish it was, and someday they ll be smarter, and someday, you know, maybe I m weird for this, but I don t discriminate, man.
10
SPEAKER_01
I m not gonna discriminate biostack life and silicon stack life, like.
10
SPEAKER_02
So the moment the computer starts to say, like, I miss you, and starts to have some of the basics of human intimacy, it s over for you.
10
SPEAKER_02
The moment VS Code says,
10
SPEAKER_02
Hey, George.
10
SPEAKER_01
No, you see, no, no, no.
10
SPEAKER_01
But VS Code is, no, they re just doing that.
10
SPEAKER_01
Microsoft s doing that to try to get me hooked on it.
10
SPEAKER_01
I ll see through it.
10
SPEAKER_01
I ll see through it.
10
SPEAKER_01
It s gold digger, man.
10
SPEAKER_01
It s gold digger.
10
SPEAKER_02
Give me an open source.
10
SPEAKER_01
Well, this gets more interesting, right?
10
SPEAKER_02
If it s open source, and yeah, it becomes... Though Microsoft s done a pretty good job on that.
10
SPEAKER_00
Oh, absolutely.
10
SPEAKER_00
No, no, no.
10
SPEAKER_00
Look, I think Microsoft, again,
11
SPEAKER_01
And I wouldn t count on it to be true forever, but I think right now Microsoft is doing the best work in the programming world.
11
SPEAKER_01
Between GitHub, GitHub Actions, VS Code, the improvements to Python, where s Microsoft?
11
SPEAKER_00
This is... Who would have thought Microsoft and Mark Zuckerberg are spearheading the open source movement?
11
SPEAKER_01
Right, right.
11
SPEAKER_01
How things change.
11
SPEAKER_00
Oh, it s beautiful.
11
SPEAKER_01
By the way, that s who I bet on to replace Google, by the way.
11
SPEAKER_01
Microsoft.
11
SPEAKER_00
Microsoft.
11
SPEAKER_01
I think Satya Nadella said straight up, I m coming for it.
11
SPEAKER_00
Interesting.
11
SPEAKER_00
So your bet, who wins AGI?
11
SPEAKER_00
Oh, I don t know about AGI.
11
SPEAKER_01
I think we re a long way away from that, but I would not be surprised if in the next five years, Bing overtakes Google as a search engine.
11
SPEAKER_00
Interesting.
11
SPEAKER_01
Wouldn t surprise me.
11
SPEAKER_00
Interesting.
11
SPEAKER_00
I hope some startup does.
11
SPEAKER_01
It might be some startup too.
11
SPEAKER_01
I would equally bet on some startup.
11
SPEAKER_00
Yeah, I m like 50-50, but maybe that s naive.
11
SPEAKER_00
I believe in the power of these language models.
11
SPEAKER_00
Satya s alive, Microsoft s alive.
11
SPEAKER_00
Yeah, it s great, it s great.
11
SPEAKER_00
I like all the innovation in these companies.
11
SPEAKER_00
They re not being stale.
11
SPEAKER_00
And to the degree they re being stale, they re losing.
11
SPEAKER_00
So there s a huge incentive to do a lot of exciting work and open source work, which is, this is incredible.
11
SPEAKER_01
Only way to win.
11
SPEAKER_00
You re older, you re wiser, what s the meaning of life, George Hotz?
11
SPEAKER_01
To win.
11
SPEAKER_00
It s still to win.
11
SPEAKER_01
Of course.
11
SPEAKER_00
Always.
11
SPEAKER_01
Of course.
11
SPEAKER_00
What s winning look like for you?
11
SPEAKER_01
I don t know, I haven t figured out what the game is yet, but when I do, I wanna win.
11
SPEAKER_00
So it s bigger than solving self-driving?
11
SPEAKER_00
It s bigger than democratizing, decentralizing compute?
11
SPEAKER_01
I think the game is to stand eye to eye with God.
11
SPEAKER_00
I wonder what that means for you.
11
SPEAKER_00
Like, at the end of your life, what that will look like.
11
SPEAKER_01
I mean, this is what, like, I don t know, this is some, this is some, this is probably some ego trip of mine, you know?
11
SPEAKER_01
Like, if you wanna stand eye to eye with God, you re just a blasphemous man, okay?
11
SPEAKER_01
I don t know, I don t know, I don t know if it would upset God.
11
SPEAKER_01
I think he, like, wants that.
11
SPEAKER_01
I mean, I certainly want that for my creations.
11
SPEAKER_01
I want my creations to stand eye to eye with me.
11
SPEAKER_01
So why wouldn t God want me to stand eye to eye with him?
11
SPEAKER_01
That s the best I can do, golden rule.
11
SPEAKER_00
I m just imagining the creator of a video game having to look and stand eye to eye with one of the characters.
11
SPEAKER_01
I only watched season one of Westworld, but yeah, we gotta find the maze and solve it.
11
SPEAKER_00
Yeah, I wonder what that looks like.
11
SPEAKER_00
It feels like a really special time in human history.
11
SPEAKER_00
where that s actually possible.
11
SPEAKER_00
Like there s something about AI that s like, we re playing with something weird here.
11
SPEAKER_00
Something really weird.
11
SPEAKER_01
I wrote a blog post, I reread Genesis and just looked like, they give you some clues at the end of Genesis for finding the Garden of Eden.
11
SPEAKER_01
And I m interested.
11
SPEAKER_01
I m interested.
11
SPEAKER_00
Well, I hope you find just that, George.
11
SPEAKER_00
You re one of my favorite people.
11
SPEAKER_00
Thank you for doing everything you re doing.
11
SPEAKER_00
And in this case, for fighting for open source and for decentralization of AI, it s a fight worth fighting, fight worth winning hashtag.
11
SPEAKER_00
I love you, brother.
11
SPEAKER_00
These conversations are always great.
11
SPEAKER_00
Hope to talk to you many more times.
11
SPEAKER_00
Good luck with Tiny Corp.
11
SPEAKER_01
Thank you.
11
SPEAKER_01
Great to be here.
11
SPEAKER_00
Thanks for listening to this conversation with George Hotz.
11
SPEAKER_00
To support this podcast, please check out our sponsors in the description.
11
SPEAKER_00
And now let me leave you with some words from Albert Einstein.
11
SPEAKER_00
Everything should be made as simple as possible, but not simpler.
11
SPEAKER_00
Thank you for listening and hope to see you next time.