So Matt, today we're reviewing the singularity as near when humans transcend biology by Ray Kurzweil. Tell the listeners, what on earth is this book about? Adam, you may have heard that the machine overlords are coming. Well, good news, you're going to become a machine overlord. The idea behind this book is that humans, machines, virtual reality, actual reality are all going to merge together as one. Yes, essentially technology will progress so quickly that we'll be subsumed with our technology and become one with it. Now, this can kind of sound like, you know, a sci-fi fantasy, something you might see in a pot of Star Trek, but Ray Kurzweil is really a respected author and AI theorist. Yeah, Kurzweil does seem to be writing about the Borg at times, but he's actually very respected. As you said, he's worked with Marvin Minsky in MIT. He's an entrepreneur that's founded a lot of different companies. And despite calling himself a singularitarian, he actually takes this very seriously.  And now, before we get further into our review of the singularity, it's time to remind listeners that this is random talkers, I am Adam, the other voice to hear is Matt. And this is a show where we prognosticate on how technology is going to shape our future for better and worse. You can hear us on YouTube, you can hear us on iTunes or SoundCloud if you prefer the podcast form. Make sure to subscribe, leave a review, leave a comment. We love to hear from you, especially if you have any book suggestions for us to add to our reading list. Now, to get back to the idea of the singularity, you know, humans merging with machines, you might wonder how on earth technology is going to become advanced enough, but we'll get to a point where we're basically cool with becoming one with it. Now, in Ray Kurzweil's mind, this is going to happen because technology grows it an exponential rate. It's not a linear growth of a slight improvement year after year. No, it's a steadily increasing rate of growth, which is kind of powering with technological advancements of the future. Yeah, he calls this exponential growth rate the law of accelerating returns, the idea that each advancement builds on the last and it just gets faster and faster as time goes on. Now, if you take the 2004 rate of progress when this book was written, you'll actually see that Ray says we'll get 20,000 years of technological progress this century. I'm pretty excited by that, Adam. Yeah, I'm very excited by two. And one thing you just mentioned then is that this book was in fact written in 2004, which means now in 2018, we have 14 years to look back on some of the predictions that Ray made and kind of assess whether or not they're coming true. But you know, we'll get more into that later. Yeah, you know, you may find yourself doubting that this exponential growth could be true. But I'll point out that there is another law that seems to hold pretty steady, which is Moore's law. And the idea behind Moore's law is that we'll double the number of transistors on an integrated circuit approximately every two years. And this has held steady for about 45 years now. Yes, the other constant with Moore's law has been every two years or so we get an article proclaiming is Moore's law dead. But for the most part, you know, it seems to be chunking along reasonably well even here in 2018. Now, one key point that Ray makes towards exponential growth is to say that over a short period of time, exponential growth can appear more like linear growth. So if we look back over the last year or two, say, we might think that, you know, not much has really changed, you know, our phones are basically the same, you know, there might be a few more emojis, but not much really changed between the last iPhone and this one. You know, Adam, I would say you're not noticing the change because you're using an Android device. Yeah, that's true. I basically noticed how my phone doesn't work every day. But I'm sure iPhones are maybe progressing faster than I might think. But Ray basically says that we shouldn't consider technological growth on such a short time frame of one to two years. Instead, we need to look back say a century. And let's say as a thought experiment, we took the technology of today back to someone who was alive 100 years ago, they would surely be absolutely stunned by just how much technological advancement has taken place over a bad period of time. I mean, even something that we take for granted today, something like Spotify, the ability to stream a few thousands, millions of songs from a single device would have absolutely full abacus to someone who was alive 100 years ago.  One way I like to think about this is my own family, my own relatives. I asked myself, what was the difference in generations between, let's say my great grandparents to my grandparents, to even my parents? And it's clear to me that the differences between those generations are increasing. My great grandparents were much more similar to my grandparents than even my parents are to me today. And because of this, I think there's a lot of evidence for this structure that Kurzweil is putting forward. Right. Kurzweil points out that new technologies are basically being adopted faster and faster. So if you look at like traditional landline phones versus the cell phone, the cell phone saturated the market a whole lot faster than the original phone did. Same thing with technologies like the internet. Kurzweil also says that we've had these kind of temporary blips in human history that you might expect to slow down a pace of technology, but they really haven't. So he's thinking of things here like depressions, recessions, world wars. But in fact, something like a world war might have actually sped up the pace of technology via the atomic bomb. Yeah, you know, Kurzweil really sees everything as exponential growth.  You know, the other thing he points out is that while it does look like exponential growth at the macro level, if you zoom in a bit, what you'll actually see is that technological change is a series of overlapping S curves. So the idea behind an S curve is there's a gradual steady state, a ramping up, if you will, then there's a really drastic step change to a new plateau. And then if you stack these S curves together, you'll actually get a very good representation of technological change. So to use an example here, let's think about computer design, computer paradigms.  All of these are a step change function that has led us to where we are today. Right, I think this exponential growth kind of theory works very well for computing, but maybe not so much so for other areas. There's one chart in the book, for example, where Ray shows educational spend as following an exponential growth pattern. Now this might be true that spend on education has grown very sharply, but I doubt anyone would say that the returns from education have really increased at an exponential rate. And for that reason, it's hard to kind of say that we've seen the same progress in other areas of technology that we have in just say pure computing. Yeah, it may be exponential, but it's certainly not headed in the upward direction. I would also say that, you know, there's lots of different examples in the book that get used, for example, VR, that I think people today would point out AR is perhaps even more prominent. So didn't exactly nail that one. The other thing is, you know, obviously blockchain technology had not been invented yet, so that doesn't show up. And this is not to say that, you know, this is, you know, necessarily a flaw of the book, it's just pointing out that, you know, when you design a book written in 2004 trying to predict the future, especially when you believe there's going to be exponential growth, it's really, really difficult to get right. Now another area that that's also somewhat, you know, testing in my opinion, difficult to describe is his belief that, you know, we'll be able to model the human brain. This idea is that instead of, you know, creating AI through computer algorithms, we'll simply reverse engineer the existing circuitry of the brain to be a functional model of an AI algorithm. Now, I kind of equivocate this to, you know, Leonardo da Vinci coming up with a flying machine, but later on, we needed the Wright brothers to explain to us that we actually need a fixed wing aircraft for this thing to work. Right. Looking back now in 2018, the book that was written in 2004, I would say, rate gets a lot right, but there are some things that kind of stand out as being omitted or, you know, perhaps misrepresented in terms of how they would affect the future. So if you're looking for a discussion of crypto kitties and, you know, how they're going to transform technology, that's not in here, unfortunately. And also there is a kind of very long winded discussion of the brain and reverse engineering the brain and all kinds of facts about the brain. But just don't see particularly relevant to modern AI research, where if you read sort of intro AI books, I'll kind of say, yes, it's a neural network, but we're not trying to reverse engineer the brain. That's not what this is about. And that's not really what is kind of generating the AI progressive today. Nevertheless, there are some interesting parts when Ray is talking about the brain that we will be remiss to not to mention. For example, there's a discussion on just how many computations the brain can make. So Ray talks about a CPS metric or computations per second metric throughout the book. And for humans, it's about 10 to the 14th power, which is really quite stupendous. And at the time that the book was written, it was basically equivalent to the top supercomputer in the world. Another thing Ray talks about is how the brain stores memories. He kind of compares them to being a hologram, whereby they're stored in a diffuse pattern throughout the brain, whereby as neurons pick up new information, some of the neurons that were being used to store the memory are basically repurposed. But the overall structure of the memory sort of remains, it's just kind of a hologram that is losing its resolution. And that's kind of how we see memories fade in our brains as these neurons are essentially being replaced for other purposes over time. Well, I for one, Adam found these holograms much more useful than the holographic Tupac that appeared at Coachella a couple of years ago. Yeah, legendary rapper, not so legendary performance, I would say. Yeah, yeah, it didn't didn't turn out great. You know, in addition to reverse engineering the brain, Kurzweil sees there being three main drivers of technological progress, genetics, nanotechnology and robotics. Now we're going to shorten these as G and R, but we'll go through each of them in order. So the first is genetics. Now this is one where I think most people will probably be the most familiar. You of course have new technologies like CRISPR, but then the general idea that you can change DNA and eradicate diseases or make ourselves smarter, stronger, faster, whatever it may be. I think Ray Kurzweil kind of looks as this is not necessarily the most important or the most compelling because he kind of sees the machine side of things taking over and really negating our need to do too much genetic fiddling. Now the next side though is nanotechnology and nanotechnology is where Ray really shines. He loves nano anything at all. Yes, Ray is a huge believer in the power of nanotechnology. He lists a number of examples of nanotechnology, so many examples that one might get a little bit bored reading all of them. But overall, I would say that the gist of it is that nanotechnology will be to say physical manufacturing what AI is to computing whereby using nanobots you'll be able to make everything so cheaply that the value of the item will be in the design, not the kind of raw materials and processing needed to create it. There are some interesting nanotechnology applications that are mentioned in the book.  There is one slight concern here which is the nanobots would need to be internet connected in Ray's vision to receive updates and instructions which could be a little bit terrifying if you've heard anything about computer viruses, but in Ray's mind we've done a reasonably good job of controlling viruses when it comes to computers and he feels like we could do the same thing with nanobots and his view is that the overwhelming kind of positive consequences of nanobots will sort of overtake any negative side effects of them. Yeah I'm sure the dystopians out there will be very alarmed by these interconnected bots, but you know the real thing that you should have called on Adam is that he talks about a series of nanobots that will allow me to eat anything I want. That is the real value add. You just have the bots just chomp off all those excess calories and you know I'm having a good time. Yeah Ray has this interesting example where he basically says that you know we can have sex now about making a baby so we should be able to eat without gaining weight. You know you should be able to eat that burger for lunch, maybe have a second burger and the nanobots will just take care of it so you don't actually gain any weight. Yeah I think another interesting application of this is that perhaps we won't necessarily need the bots to eat up the excess calories. We'll just simply insert the bots into our brain and make us perceive a different reality.  Now obviously this starts to feel a bit like a Philip K Dick novel where you start to ask yourself if you have bots that are in the brain that can manipulate neurons in such a way. Can we know anything is real at all? How will we be able to perceive reality? What can we trust? Right and as part of kind of the singularity of emerging of humans and machines Ray basically envisions the physical and virtual world emerging too and I think one of kind of the differences in the way that Ray looks at the world to how most people look at it is that Ray I don't think really sees the virtual world as being inferior in any way to the physical world. You know he'd be absolutely fine with living in a virtual world you know if it was a fantastic utopia versus slogging things out in the real world. And for nanobots you know Ray really goes a step further when it comes to virtual reality you know today we think of virtual reality as putting on a clunky headset you have to wear all the time Ray actually basically says no we could have nanobots inside our brains but a program to basically show us this virtual world and that's his idea of a immersive virtual reality rather than kind of the headset version we have right now. But I would say you know the predictions that have been made in 2004 in terms of the the power of nanotechnology have not necessarily yet come to pass. One of the advancements that Ray talks about is nanotech being used for fuel efficient gains in terms of renewable energy. Basically you could create these amazing nanotechnology solar panels that would be much more fuel efficient than the ones we have right now but this hasn't really come to pass. There was a startup called Nanosolar that attracted about $400 million in VC money and it went completely bankrupt it didn't really go anywhere. And so some of these like advancements in nanotechnology you kind of have to put the brakes on and say you know is this really going to happen anytime soon. Yeah maybe we haven't seen the progress we expected in nanotech but one area we have seen progress in is robotics. So robotics is the R in G and R and it's the final area that Ray Kurzweil kind of sees as driving the future.  They follow a set of instructions but they can't really think or make decisions on their own. However Ray says that pretty soon we'll get into you know robotics which has a strong AI. Now a strong AI is an AI which is defined as being smarter than humans. So if you've read Nick Bostrom's Super Intelligence he goes into this topic at depth. We actually have a review out there of this book if you're interested but to describe this we'll say that at some point in the future AI is going to be smarter than humans and at that point they're really going to sort of be the next evolution if you will of humanity will be these super smart AIs and you know from Kurzweil's perspective he's not really bothered by this. He sort of sees the merger of man and machine as the natural evolutionary process and welcomes it with open arms. Right Ray doesn't see it as a takeover as some people might have AI he sees it as a merger where we'll basically gain from this AI we've created rather than being you know subservient to it. And in Ray's kind of vision of the world you know we are one with the machines we basically live in this world where the physical and virtual have merged basically ready to play one in real life kind of. One thing that Ray kind of takes away from this potential future is a lot of the issues and the problems that we have today will sort of go away. We'll have nanotechnology that can basically be used to say cure any diseases you know we'll be able to say upload our minds and save them forever and for that reason you know death won't really be a thing. And he's really against kind of us hanging on to what he sees as human imperfections and sort of romanticizing them or making them seem noble in any fashion. I mean one great line he has in the book is that he sees no reason to celebrate our limitations. You know he doesn't see the fact that we die as a necessary or a noble or a great thing but is you know somehow necessary for humanity. And instead he actually has quite an incisive critique of religion I would say in this book in which he basically says that religion has been created to justify why we have to die. But in Kurzweil's mind death isn't necessary at all.  Maybe if you look back in human history and you see you know perhaps infant mortality rates 100 or 200 years ago and you looked at you know that today it would be absolutely appalling. He kind of sees death as the same way in like 200 or 300 years we're going to look back at today and just be absolutely appalled that people died. Yes and so Ray for one is not accepting death anytime soon. He's actually written a book about living forever and he's quite serious about living long enough to get to a point where his say mind and intelligence could be uploaded and saved you know even if his physical body is no longer around. And he basically talks about this as being a bridge to a bridge to a bridge whereby you just have to make it to the next kind of technological innovation that's going to keep you alive and eventually you'll get to a point where death isn't really a thing. Yeah just waiting on that next S-curve. Yes but Ray points out that you know for this to happen we are going to be dependent on technology. You know evolution happens but it's incredibly slow. One interesting fact he has in the book is that he talks about how we evolve about one cubic inch of brain matter every 100,000 years. We get smarter but it takes a long time and if we instead depend on say a strong AI to help us we can get a lot further a lot faster. So these new technologies really bring up an important philosophical question for us which is what is the nature of who you are if you're backing up your mind to the internet if your body parts are being replaced by nanotech what is the nature of you? So one question that comes up in philosophy is this example of the ship of Theseus. So for those of you who may not know in Theseus' paradox the idea is that there's a ship it's traveling all around the world and it's on a journey let's say for 10 years and as it's traveling each of the pieces of the ship are being replaced so a board here a sail here and when the ship leaves it has all of its original parts but as it travels around every single one of those parts is replaced and we ask ourselves is the ship that returns to port at the end the exact ship or the same ship that started would you still call that the ship of Theseus and most people would say yes even though the pieces have been replaced that is the same ship but then you have this new interesting twist on the story which is if you took that same ship that Theseus had and you place it in museum and night by night you had someone sneak in and replace it part by part would that still be the original ship and I would say most people would disagree and say no it's actually the pieces that were stolen out that were the original ship so there's some element of Theseus owning the ship or having the ship that implies who the parts belong to and I think it then asks this interesting question if there are multiple copies of you if your brain is being influenced by different nanobots what is the nature of you what is your true reality so Ray kind of says you know for example if he was cloned and there was a ray two out there most people would agree that that ray two is not him it's not his identity but then he kind of talks like you said the ship of Theseus about gradual replacement whereby if our bodies were gradually over time replaced with nanomaterials you know would we still consider that to be us and some people even here are kind of saying well maybe not you know if I'm just nanobots is that really me but the counter to that that Ray has is that he says our bodies are replacing ourselves from themselves right now you know he says that every month essentially if you look at your biological material you know your cells are rebuilding what was you a month ago is not you now so he would argue that this gradual replacement is happening today and if it's happening with nanomaterials well that's all the more the better you know is going to be a better you a longer lasting you and you should sort of embrace that as still being your identity rather than worrying about yourself being you know taken over by nanobots so this question of what makes you you I would say has really infiltrated the culture as a kid saying if you watch netflix for example right now there's a show called altered carbon that is on and in this show human bodies are basically known as sleeves they're eminently replaceable what is us is essentially a metal desk that is plugged into the vertebrae of this sleeve and then basically turns on to become our body for that point in time and humans over the course of history can basically switch sleeves switch bodies and carry on just fine now there is some slight drama to this in the altered carbon universe which is that if your body or your sleeve is killed well you're okay because the desk can come out of the vertebrae and be plugged into another sleeve but if that disc itself is destroyed the vertebrae is destroyed well now you're done and your life is well and truly over and this of course adds a lot of drama to the show but you might wonder you know in a universe where the technology is available to do this why wouldn't they have made a backup of you that seems like it'd be useful to have you know I have to agree Adam in reality we would always want a backup but it does make a little bit of sense because I could see a government or other regulatory agency demanding that only one copy may exist and there's some good reasons for this you can imagine a world where you know Adolf Hitler has cloned himself a million times on some sort of you know outer rim planet and they're headed to do something evil so it's not something that you know I could see being that far off of reality the good news is is that Ray Kurzweil is the perennial tech optimist he really thinks in the long run the positive outcomes will always win out yes so Ray is really aggressive about how quickly he sees tech progressing for example by the end of the 2030s he predicts that we will be able to upload our digital cells basically keep our minds our memories our intelligence in the cloud and essentially live forever really and Ray is very serious about this concept of not dying he takes for example over 250 supplements per day that's about 250 more than I take Adam yet likewise he also receives about a half a dozen intravenous therapy drips and he is incredibly serious about keeping his body going and basically living long enough to reach this technological innovation whereby our minds can be saved forever now I think you can say that Ray was potentially a little over-infusiastic with some of the predictions that were made in the two finals and four edition of this book for example he talks about a drug to fight heart disease which was a torso trap it now this drug went into medical trials and unfortunately killed a lot of people who took it and therefore is never going to come to market and so I think this is just one of the dangers you obviously there's no way Ray at the time of writing this book have known that the drug wouldn't work out too well but this is one of the dangers of trying to kind of forecast drug advances medical advances that kind of thing you know it's very difficult to know what is actually going to take place yeah Adam one thing you're pointing out here is that Ray basically ignores all of the societal changes of his technological predictions he sort of thinks that you know everything will just work itself out we don't really need to worry about the detail so much just the direction we're going so for example one thing I think he gets right in the book it's his prediction that we will be cloning animals or creating some sort of synthetic meat in the near future but what he doesn't talk about at all is what that might do for farmers how are they going to find a job if they're out of work and they are used to raising cattle so that's completely ignored the environmental effect that this could create is also sort of glossed over because you could say that okay now we're actually going to have quite a bit of excess energy or less greenhouse gas because of that and that's that's maybe a good thing and you know in in the end he doesn't talk about it at all and I think the the glaring one and the one we talked about last time was UBI so universal basic income is something that we kind of said may be required to pay people or to provide sustenance in a world where people don't have jobs well again Ray sort of says eh don't worry too much about that yeah and Ray does credit does talk about kind of needing to convince the public about the benefits of technology and I would say that in the 14 years since this book was written that campaign has not been going terribly well I think there's been a lot of backlash against sort of tech companies as being sort of greedy and not necessarily kind of working towards the greater good and of course we have to work in a Trump reference there are you know impending trade wars with certain industries that may have not been foreseen yes and I think when we go back to the concept of G&R genetics nanotechnology robotics we see a lot of ways that these can go wrong but as sort of acknowledged by Ray but not necessarily delved into in a whole lot of detail so for nanotechnology you have the prospect of unstoppable nanobots self-replication for instance whereby to create trillions of nanobots we would essentially need them to be able to self-replicate but if this process were to grow out of control you could see a situation where nanobots take over the earth in about three and a half hours so yeah potentially look forward to that one when it comes to robotics and strong AI there's this idea that it's going to be very very difficult to control intelligence that is smarter than you everyone including Ray sort of acknowledges this but the general kind of you know compromise here or the general kind of acknowledgement is that you have to get the limitations of strong AI right the first time around you have to set the rules of the game before strong AI arrives and they have to be good enough to contain it once it does get here but I think we could all say that we're somewhat skeptical this is actually going to happen as people like Nick Boston pointed out now going back to kind of the lowly field of genetics in this book there are kind of terrifying implications here of you know altered DNA and the potential to create diseases that could kill people very effectively now Ray talks a lot in this book about SARS and the SARS outbreak and Ray kind of holds this up as being a successful example about how we were able to take a potentially very dangerous outbreak and basically contain it you know across nations and do a really good job of working together to make sure SARS wasn't too powerful one thing I will call out here is that SARS only had a mortality rate of about 15 to 20 percent and it didn't necessarily sprout as quickly as some of the diseases you could potentially see created in the future as genetics advances and especially if you had kind of a terrorist element that was able to introduce a disease into many world cities all at once it could be something where you have this terrifying threat with very little you can do before it had infected millions and millions of people so in that regard I mean I think all of the aspects of GNR genetics nanotechnology robotics all have areas where they could potentially grow out of control and be extremely dangerous yeah so for anyone who's played pandemic you should know that I will be hiding out in Madagascar if any of this goes down but I think we should switch gears a bit and talk a little bit about a concept that Ray thinks about a lot which is asymmetric risk tolerance the idea here is basically that there are a lot of dangers to the existing system and we just simply don't acknowledge them and we get freaked out a bit by potential changes so for example Ray talks a lot about how the drug approval process is too slow we drag our feet throughout the entire thing just to ensure that a drug doesn't harm people but we completely ignore the idea that the disease that the drug could potentially treat is killing people today so by doing that we're giving up lots of opportunity to save lives because we're scared that it might create incremental harm in some drug doubt yes while Ray is very much a tech futurist he does a good job I think in this book of focusing on the here and now and the millions of deaths from disease and famine that really should be preventable so famine in particular is something that Ray talks about extensively in the book he rails against environmentalists specifically of those who are trying to block the adoption of genetically modified crops because while Ray acknowledges there could be some you know obscure unforeseen danger of these crops for the most part they have been proven absolutely safe and they have the potential to save millions of lives in impoverished countries you know countries suffering from famine and environmentalists would think of those preventable deaths rather than worrying about some niche worry about you know GMO crops you know Adam intellectually Ray and I are on the same page but I'm going to have to leave eating the golden rice to you I did not realize you were such a lada when it came to to rice technology but let's move on and talk about something else yeah so another place asymmetric risk comes up all the time is when you think about self-driving technology now there was actually a very recent example of this where a uber self-driving car hit a pedestrian in Tempe, Arizona and killed them and this person was walking in the middle of the street it was at night they appeared to be pushing a bicycle but we would have expected the LiDAR technology on the car to have detected the person now there's been a media firestorm where the media is asked like why this happened and how could we have prevented this but Ray Kurzweil would probably point out that we've completely ignored all of the countless deaths that are caused by human drivers who are not paying attention and hit a pedestrian and so because of this I would say you know this is a really good example where we're not thinking about this asymmetric risk correctly right so I don't want to really let uber off the hook here uber does not have the greatest reputation of any tech company I think there are valid questions about why was the human driver kind of supervising the car not looking at the road at the time why did the LiDAR not detect this person at all why did the car not slow down at all and I think because of that you know it's very reasonable there's going to be an extensive investigation into this to determine exactly what went wrong now having said that I do agree that the adoption of self-driving cars should generally dramatically reduce the amount of traffic deaths we see in the United States or anyway really but when I think you think about traffic deaths you can kind of separate them into three distinct categories right so there are those deaths that would have been say prevented by a self-driving car but not by a human driver who wouldn't have been able to respond in time so those are kind of great you know if you introduce self-driving cars you should be able to eliminate those deaths there are going to be some deaths that could not be prevented by either a human or a self-driving car you know maybe if there's some kind of like natural disaster a force of nature just nothing that a computer or human could possibly deal with and then the third category of the deaths that could be prevented by a human but not by a self-driving car because its algorithm for whatever reason could not prevent the death from occurring and I think people are somewhat concerned that this uber case could kind of fall into that third category whereby a human you know at night would have actually been able to at least slow the car down maybe get it down to a speed where the crash wasn't fatal whereas the self-driving car just did absolutely nothing you know kept going a 40 miles an hour or whatever speed was and struck this person and for that reason I think that's what people are upset about now I do think you can make the case as Ray probably would that people focus way too much on the third category of deaths whereby any death that you know a human possibly could have prevented the self-driving car didn't it's going to be looked on you know truly as a tragedy which it is but people aren't going to focus on kind of the first category of deaths which are the deaths that could be prevented by rolling out self-driving cars and I think a lot of people in kind of a self-driving community or just the tech community in general are going to be worried that this uber case is going to lead to a massive rollback in you know self-driving car progress which although preventing the third category of deaths is going to allow the first category of you know human kind of cause deaths to keep going which even though they could have been say solved by rolling out self-driving cars yeah I think all of these issues around self-driving cars and medical research calls into place for government regulation but I think Ray is pretty upfront that he doesn't think the government can be very effective in this space at all with maybe the exception if they are very totalitarian they can get away with some of these things but you know as a whole I think he really looks at things like open-source software development is being the way forward whereby you know if you can see the code that's written and everyone's familiar with it it actually will decrease things like computer viruses that's one example we talked about earlier and the other one is he believes a lot that industries can self-regulate so that you know there can be different principles and different you know guiding thoughts that industries can use and follow pretty closely and that's generally good enough to prevent really apparent behavior within a given industry the other thing though I think we should switch gears on a bit is just talk about the book in general this book covers a ton of topics Adam what did you like the most so yeah Ray can have you talking about the the Fermi paradox one moment switch to you know privacy and music the next he kind of goes around all over the place I actually thought this discussion of the Fermi paradox which is essentially why haven't we met any aliens yet it was pretty interesting and Ray's kind of solution to the paradox is that we are the civilization of all the civilizations that might be out there but as the furthest along in terms of technology this might be somewhat hard for us to believe but I think Ray makes a reasonably convincing case about why that may be so the stuff in here that considering the book was written in 2004 I would say has actually really been seen as kind of ahead of its time there's a discussion for example of government surveillance and NSA surveillance but really only came to kind of the general public's attention with Snowden and those revelations but here in 2004 you know Ray is on it you know he's talking about it right then overall you know this can be a pretty dense book it can be kind of dry in terms of the amount of technology that is discussed you know it's a pretty difficult read at certain points but overall I think Ray Kurzweil kind of comes at it with a sense of humor that sort of lifts the material up but it really keeps you engaged the whole way through in particular he has these dialogue sections kind of at the end of key points at the end of chapters whereby we have these dialogues where Ray might be talking to somebody from say the year 2100 or he has like historical figures jump in like Freud and Charles Darwin make appearances for instance and these kinds of mock conversations really help you sort of understand the concepts in your mind yeah you know I did not like the conversations the dialogue as much as you did Adam but the one thing I give Ray a lot of credit for is he comes out he makes his predictions but they're not exactly correct but he acknowledges that like he acknowledges that the future is ever changing and this is just a general framework for thinking about you know what might come to pass and I will say he gets a lot more right than he gets wrong so in general I don't hold him you know sort of speak accountable for for all of the misses because his hits are pretty high up there and you know I think he's just a really authentic person I think one of the interesting things about Ray Kurzweil as a person is he believes everything he says in this book I mean he is taking these you know 250 some odd supplements he is you know believe he does believe this with his whole being and so from that I give him a lot of credit he's not simply writing some you know book to put a theory out there and sell a bunch of books he's just telling you you know his philosophy on life if you will right and he's kind of put his money where his mouth points in his career in terms of a kind of technological investments he's made and he's really a kind of solid futurist in my mind and that he does make these very distinct predictions where he says you know by this particular point in time I think technology will have advanced to this state and I think you know if you went back and talked to sort of 2004 Ray now in 2018 you might find that he was perhaps you know a little bit disappointed about how far technology has come I mean we've certainly made strides in some areas you know like we've talked about self-driving cars appearing and for the most part they work but overall I think things like nanotechnology and kind of increases in computing power have not perhaps developed to the extent that Ray might have expected when he wrote the book yeah when I think back to 2004 a lot of the development in technology was hardware based was about you know rapidly increasing our capabilities in lots of different areas unfortunately I think shortly after that period of time you saw a bit of a change in the landscape whereby people who would go and you know let's say work at companies like Microsoft and Cisco are now working you know at companies that build apps and that's not necessarily a good or bad thing but I think it's changed the rate of some of these hardware predictions that someone like Kurzweil would be making you also saw this I think early on when people were talking in the early 2000s about oh you know it used to be that the best and the brightest were becoming doctors and scientists and now they're becoming Wall Street traders well unfortunately those Wall Street traders have now turned into app developers yes I mean I think the innovations he talks about you know essentially emerging man with machine you know creating these nanobots inside you that are going to fix up your immune system these kind of medical advances have not really come to pass at least not yet and so I think for Ray's vision of the singularity it could be a while before we get there you know I personally would be skeptical that we would reach a singularity vision within the next century although Ray certainly in this book and perhaps right now kind of believes it will come a lot sooner yeah one thing that is really hard to grasp is how quickly these changes will come and what do these changes mean so you know when Kurzweil says something like we'll have a trillion trillion trillion times more computational power what does that mean for us and what does it mean to say we have a universe saturated with intelligence all these are almost just too big in scale for us to really fathom and so trying to say where we're going almost as hard to get your head around is probably one of the more sort of difficult parts of the books and I think the other side we should go to is just asking ourselves will we be happier post-singularity yes it's very hard to kind of grasp just the scope of the changes that would occur instead of a true singularity vision I think one useful analogy that Ray kind of makes is he basically compares bacteria today to humans as being akin to humans today to post-singularity your human machines that would arise and so if you kind of think to yourself you know is a bacterium that much you know happier or unhappy of an human today that's kind of a situation you arise in with humans there are some obvious benefits of course of the singularity you know this idea that disease will essentially be eradicated you'll be able to live in the virtual world of your choosing and and from that you can kind of say well maybe things will be much more pleasurable um but there's also kind of a dystopian futures to you know AI takeovers government takeovers to where you might say that this would actually feel more like a prison than you know a bold new world you'd really want to in fact live in but overall I think after reading this book Matt and I would both consider ourselves singularitarians we have kind of grasped the scope and the potential power of the singularity Ray's book it is dense it is difficult to get through in parts but overall it is an engaging humorous read that I think we would both highly recommend um I hope you've enjoyed listening to our review this has been random talkers make sure to subscribe on youtube and we'll see you next time


Live from downtown San Francisco, it's theCUBE. Covering IBM Chief Data Officer Strategy Summit 2018, brought to you by IBM. We're back in San Francisco, everybody. This is theCUBE, the leader in live tech coverage. And we're here covering exclusive coverage of IBM's Chief Data Officer Strategy Summit. This is a summit, as I said, they bookend at each coast San Francisco and Boston, intimate, a lot of senior practitioners, chief data officers, data folks, people who love data. Caitlin Halferty is back. She's the client engagement executive and the chief data officer office at IBM. And Alan Crane, assistant vice president at USAA. Thank you, welcome. Good to see you, thanks for coming on. Thanks for having us. You're welcome. Well, good day today. As I said, a very intimate crowd. You're here as a sort of de facto CDO, learning, sharing, connecting with peers. Set up your role, Alan, tell us about that. Well, at USAA, we've got a distributed data and analytics organization where we have centralized functions in our hub and then each of the lines of business have their own data offices. And I happen to have responsibility for all the different ways that our members interact with us. So, about 100 million phone calls a year, about a couple billion internet and digital sessions a year. Most of that is on mobile. And always looking at the ways that we can give back time to our membership as well as our customer service reps, who we call our member service reps, so that they can serve our members better. The faster and more predictive we can be with being able to understand our members better and prompt our MSRs with the right information to serve them, then the more they can get on to the actual value of that conversation. A lot of data. So one of the things that Inderpal talked about, very first time I met him in Boston, he said, he talked about the five pillars. And the first one was, you have to understand as a CDO how your organization gets value out of data. He said that could be direct monetization or I guess increase revenue, cut costs, right? That's value. So that's a starting point. And so, how did you start? Well, actually it was the internal monetization. So first off, I want to say USA never sells any of our member data. So we don't think of monetization in that framework. But we do think about it in terms of how do we give something that's even more precious than money back to our company and to our members and the MSRs? And that is really that gift of time by removing friction from the system. We've been able to reduce calls per member through digitization activities and reduce transfers and reduced misdirects by over 10% every year. We're doing work with AI and machine learning to be able to better anticipate what the member is calling about so that we can get them to the right place at the right time to the right set of member service representatives. And so all these things have resulted in not just time savings, but obviously that translates directly to bottom line savings. But at the end of the day, it's about increasing that member service level, increasing your responsiveness, increasing the speed that you're answering the phone and ultimately increasing that member satisfaction. Yeah, customer satisfaction, lower churn rates. That's a form of monetization. It's hard dollars to the CFO, right? Let's talk about the role of the CDO. This is something we touched on earlier. Yes. We're bringing it home here at the last segment. Where are we at with the role of the CDO? It was sort of isolated for years in regulated industries, permeated to mainstream organizations. Correct. Many of those mainstream organizations can move faster because they're not regulated, but so if we sort of reach parity between the regulated and the unregulated, and what do you discern there in terms of patterns and states of innovation? Sure, I think when we kicked off these summits in 2014, many of our CDOs came from CIO type organization, defensive posture, king of the data warehouse that we joke about. And now we've, you know, analyst reports at that time were saying, you know, maybe 20% of large organizations were investing in a CDO or similar individual responsible for enterprise data.  At the, in my opening remarks this morning, I pulled the room to say, you know, who's here for the first time? It was interesting, you know, 69, 70% of attendees are joining us for the first time. I went back, okay, who's been here last year, a year before? And I said, who is here from the beginning? 2014 with us. And Alan is one of the individuals who's been with us. And as much as topics have changed and the role has grown and the purview and scope of responsibilities, some topics have remained our attendees tell us they're still important top of mind and data monetization is one of those. So we always have a panel on data monetization and we've had some good discussions recently that the idea of it's just the external resell or something to do with, you know, selling data externally is one view but really driving that internal value and the ways you drive out those efficiencies is another perspective on it. So, fortunate to have Alan here. We've been able to, for that very reason, we've been able to grow our team from about six or seven people five years ago to well over 100 people that's focused on how we take inefficiency out of the system. And those, you know, that mere 10% when you recall call per member reduction, when you were taking 30 million calls in the bank, you know, that's real dollars, right? Three million calls out of the system that you can monetize like that. So it's real value that the company sees in us and I think that in a sense is really how you want to be growing as a data organization because people see value in you, willing to give you more and then you start getting into those interesting conversations.  Let's talk about digital transformation and how it relates to all this. So you've got, presumably you've got a top-down initiative. The CEO says, he or she says, okay, this is important. We got to do it. Boom, there's the North Star. Let's go. What's the right regime that you're seeing? Obviously you got to have the executive buy-in. You got the chief data officer, you have the chief digital officer, the chief operating officer, CFO is always going to be there making sure things are on track. But how are you seeing that whole thing shake out at least in your organization? I think one thing that we've been seeing is that digital digitization, you know, really is not about where the digital transformation is not about just going only digital. It's how does all this work together?  But it's got to be something that that experience online has got to do something that's transformative in your organization. So we really look at the member all the way through that whole ecosystem and not just through the digital lens. And that's really where teams like ours have really been able to stitch together the member experience across all their channels that they're interacting with us, whether that's the marketing channels or the digital channels or the call channel so that we can better understand that experience. But it's certainly a complimentary one and not, it can't just be an additive one. I wonder if we could talk about complacency in terms of digital transformation. I talk to a lot of companies and I just don't, there's discussion about digital you talk to a lot of people who say, well, we're doing fine. Really, you know, maybe not in our industry. Insurance is one that hasn't been highly disrupted. Financial services, things like aerospace. I'll be retired by the time this all happens. I mean, that's true, right? And so, and it's probably accurate. So are you seeing a sense of complacency or you're seeing a sense of urgency or sort of mix or both? What are you seeing, Caitlin? Well, it's interesting and people may not be aware, but I'm constantly pulling our attendees to ask what are top of mind topics? What are you struggling with? Where are you seeing successes? And digital was one that came up for this particular session, which is why tomorrow's keynote, we have our chief digital officer giving the morning keynote to show how our data office and digital office are partnering to drive transformation internally. So at least from our perspective and internal side of it, we have a priority initiative, Cognitive Sales Advisor, and it's essentially intended to bring in disparate parts of customer data obtained through many different channels, all the ways that they engage with us, our mind and other, and then deliver it through Sales Advisor app that empowers our digital sellers to better meet their revenue targets and impact and develop more of a quality client relationship and improve that customer experience. So internally, at least it's been interesting to see one of our strongest partnerships in terms of business unit has been our data and digital office. They say, look, the quality of the data is at the core. You then enable our digital sellers and our clients benefit for a better client experience. Well, about a year ago, we actually changed the organization to align the data office with the digital office. And so that reports to our executive council level. So they're peers that report into the same organization to ensure that those strategies are connected. Yeah, so as Caitlin was saying, the chief data officer kind of emerged from a defensive posture, compliance, governance, data quality, the chief digital office kind of knew. Oftentimes associated with marketing, more of an external, perhaps facing role, not always. But so do you see, and then the CIO, we say, well, wait a minute, data, it's the CIO's job. But of course, the CIO, she's too busy, you know, trying to keep the lights on and make everything work. So where does the technology organization fit? Well, all that's together. So when we brought all those things together at the organizational level, digital data and technology are all together in even design, actually. You guys are all peers reporting into the executive committee, essentially, is that right? Yes, our data, technology and design and digital office are all peers reporting into the same executive level later. And then one of the other pillars that Interpol talks about is the relationship with the line of business. So how is that connective tissue created? Well, being on the side that is responsible for how all of our members interact, my organization touches every product, every line of business, every channel that our members are interacting with. And so our data is actually shared across the organization. So right now, really my focus is to make sure that that data is as accessible as it can be across our enterprise partners. It's as democratized as it can be. It's as high as quality. And then things that we're doing around machine learning and AI can be enabled and plugged in from all those different lines of business. What does success look like in your organization? How do you know you're doing well? I'm obviously dropping money to the bottom line, but how are you guys measuring yourselves and setting objectives and what's your North Star? I think success for me is when you're doing a good job to the point that people say that question, could you do more if I gave you more? That to me is the ultimate validation. It's how we grew as an organization. It's how we don't have to play that justification game when people are already coming to the table saying you're doing great work. How can you do more great work? So what's next for these summits? Are you guys doing Boston again in the fall? Is that right? You're planning on doing that? We are, we are. And you know, fall of last year, we released the blueprint and the intent was to say, hey, here's the reflection of our 18 months internal journey as well as all of our client interactions and their feedback. And we said we're coming back in the spring and we're showing you the detail of how we've really built out these internal platforms. So we released our hybrid on-prem cloud showcase today, which was great. And to the level of specificity that shows the product solutions, what we're using, the flash storage, some of the AI components of that machine learning model, exactly. And then our vision to your question to the fall is coming back with the public cloud showcases. So we're already internally doing work on our public cloud in particular with respect to our backup, some of our client, very sensitive client data as well as some initial deep learning models. So those are the three pieces we're doing on public cloud internally. And just as we made the commitment to come back and unveil and show those detail, we want to come back in the fall and show a variety of public cloud showcases where we're doing this work. And then hopefully as we'll continue to partner and say, hey, here's how we're doing it. We'd love to see how you're doing it. Let's share some best practices, accelerate, you know, build these capabilities. And I'll say to your business benefit question, what we found is once we've built that platform, we call it internally a one IBM architecture out our platform. We can then drive critical initiatives for the enterprise. So for us GDPR, we own delivery of GDPR readiness across the IBM corporation, working with senior executives in all of our lines of business to make sure we get there. But now we've got the responsibility to drive out initiatives like that, cross business unit to your question on partnerships. And the evolution of this event seems to be this kind of a lot of evangelism early on and now it's really practical sort of sharing, like you say, the blueprint and how to apply it. You know, a lot of people asking questions, how do I, you know, there's different levels of maturity.  We are doing a panel on data monetization tomorrow. Okay, and then you got Bob Lord and Inderpal talking about that's a perfect juxtaposition and teamwork of those two major roles. And this is the first time we've really showcased the data digital partnership and connection. So I'm excited, you know, want to appeal to the developer viewpoint of this. So I think it'll be a great conversation about, you know, data at the core, driving digital transformation. And then as you said, you know, our data monetization panel, both, you know, external efforts as well as a lot of the internal value that we're all, that we're all driving. So I think that'll be a great session tomorrow. Well, and it's important, it was a lot of confusing and still is a lot of confusion about those roles. And you made your point early today is, look, there's a big organizational issue you have to deal with particularly around data silos. My data, I presume you guys have, are attacking that challenge. Yes, yeah, absolutely. Still, it's still attacking. It's an ongoing thing, but they were getting a lot better at it, I think they, but it's, you know, but you've got to lean in because if it's not internal, it's some of the external challenges around, now we're picking cloud vendors and so forth. So it was, you know, 10 years ago we were, we had our own silos and our own warehouses if we had a warehouse. And then we were kind of moving into our own silos in our own databases. And then as we democratize that, that we solved one problem, but now we're, our data's so big and our compute needs are so large that we have no choice but to get more external into a cloud. So you have to lean in because everything is changing. It's such a rapid rate. And it requires leadership, right? I mean, the whole digital data really requires, excellent leadership, vision, IBM's catalyzing a lot of that conversation. So congratulations on getting this going. Last thoughts. Oh, I would just say, you know, we were joking, the 2014, the first couple of summits, small group, maybe 2030 participants figuring out how to best organize from a structural perspective, you know, set up the office, what sort of outcomes metrics are we going to measure against? And those things I think will continue to be, you know, topics of discussion, but now we see we've got about, you know, 500 data leaders that are tracking our journey and that are involved and engaged with us. We've done a lot in North America. We're starting to do more outside the geographies as well, which is great to see. So I just have to say, I think it's interesting to see the topics that continue to be of interest, the governance, the data monetization, and then the new areas around, you know, AI and machine learning, data science, empowering developers, the DevOps delivery, how are we going to, you know, deliver that type of training? So it's been really exciting to see the community grow and all the best practices leveraged and look forward to continuing to do that and more of that this year as well. Alan, you obviously get a lot of value out of these events. You're here at the first one, you're here today. It was in 2018, you know, your thoughts. I think the first one, we were all trying to figure out, you know, who we are, what's our role, and it varied from, I'm an individual contributor, data evangelist in the organization to, you know, I'm king of the warehouse for this thing. Right, right. And largely from that defensive standpoint. I think today you see a lot more people that are leaning in, leading data science teams, leading the future of where the organizations are going to be going. And people, this is really where the center of a lot of organizations are starting to pivot and look and see, you know, where is the future and how does data become the leading edge of where the organization is going? So it's pretty cool to be a part of a community like this that's evolving that way, but then also being able to have that at a local level within your own organization. Well, another big takeaway for me is the USAA, the USAA example shows that this can pay for itself.  So it makes it easier to justify when you can demonstrate a business case. So guys, thanks very much for helping me wrap here. Absolutely. I really appreciate you having us here. It's been a great event. Always a pleasure. Hopefully we'll see you in the fall. Sounds good. Thank you so much. All right, thanks everybody for watching. We're out. This is theCUBE from IBM CDO Summit. Check out thecube.net for all the videos, siliconangle.com for all the news summaries of this event and wikibon.com for all the research. We'll see you next time.


Well, yeah, it's great to be back for PhosAsia. Last time I talked was at 2018. I was talking about the old crypto space. And my company, biggestlab.io, we are crypto stuff. And so my last talk, if you YouTube search it, PhosAsia Proteus or PhosAsia Sherry, you'll see my talk and that's 45 minutes long. So we got to do some back and forth. So I really like back and forth. So if I say anything that you find objectiveful or you have a question in the middle of it, raise your hand. I like the debate aspect. That's the open part of Phos. So I'm hoping next year we're gonna have a little bit longer talks so that we can get into that. But this talk is something completely different. This is actually about a space that I kinda swore that I would never get into. And yet, here I am. So yeah, it was good to see I'm not the only one doing edu-tech stuff. Traumae here gave a great talk in the adventure room earlier on. With COVID, right? We've all been impacted. Education's getting changed. Education changes are generational, right? You almost for changes to happen, you have to kinda wait for the old school administrators and teachers to retire for the new ones to come on. And in fact, I was born in the very late 60s. I went through the 70s in America. And I remember I had some incredibly good public school teachers, Mrs. Fletcher in second grade. She would open up the class by reading a verse from the Bible. In America now, she would be put in jail. My best teacher ever would not be allowed to teach in America, that's this generational change. And it happened during the Carter administration when they created the federal education, federal department of education before then there was not such. And Thomas Sowell, great economist, has shown the inverse proportional relationship between SAT scores and federal government spending in education. So spending is not the problem, right? So what's going on? I've been a mentor for lots of tech startups. I was one of the first mentors for the JFDI incubator here in Singapore. And I've worked with a lot of startups and I've helped advise some edutect companies and I've just watched edutect on the sides. And for about 20 years and a lot of well-meaning people that are really trying to have a positive impact. But they have almost universally failed, right? And so the three things that we see commonly is that they believe that education, automation, I'm sorry, not education, automation can replace teachers and books. They have this, hey, our curriculum or our system is so cool that everyone will see it and adopt it, right? If you build it, they will come in mentality for getting market share. And they think that creating the curriculum is something that they can do with less than $20 million, right? These are all, you know, if you see a edutect company or anyone who's thinking that this is any of these, you'll see this commonality, right? So, right, public education is, you know, it's been focused on teaching. Teachers teaching, you know, we're going to show you what to do and what to learn, right? Teachers are the source of knowledge. You know, it's rote memorization. Students are measured by how well they can repeat back what the teacher has told them, right? That's what your classic education does. My focus, and I think what needs to just change is that we need to make sure that we're just focused on learning, we're not focused on teaching, right? And what is education? So, learning or education requires understanding the knowledge and demonstrating the ability to apply it, right? See, apply it usefully, recognizing these common recurring patterns in the real world. So, it requires the adoption, the enabling of critical thinking skills, ultimately, is what must be there. I also believe that the proper role of teachers is not to be the source of all knowledge, right? Because often, you know, in lots of school and places, the teachers aren't even smarter than the students, right? Or they have different exposure for things, right? They can't be the guides of everything, right? But teachers should be coaches that enable learning, right? And so, edu-tech, technology is not the thing, right?  There's even a phrase for it in the tech world, like worse is better, right? Well, they're talking about that, right? Technology is not the thing. Technology is a multiplier of the thing, right? You got a $15 million SAP accounting system and you have no accounting skills, anything times zero equals zero. Let that be lesson number one. But if you're a really great accountant, right? Technology, like this SAP accounting system, can make it where instead of you needing to be, have a staff of 20 people to manage this one company, you by yourself could almost manage 20 other companies for their accounting, right? So that's scalability, that's what's critical. That's what tech is at the tactical level. Now tech also introduces some other things at the strategic level, but if you haven't accomplished the tactical level first, forget about it, right? So I believe that as a good coach should be measured by educational outcome, that good technology should be measured by how much you enable, how effective you can help make that coach. So we're not trying to abandon teachers here, right? So my metaphor for education or for learning is like working out, right? If you've ever started to try to work out and try to get your body in shape, if you've gone to the gym and you've had a good personal trainer, like I was fortunate to in Atlanta, I haven't lived in Atlanta a long time as you can tell, I have no personal trainer. But I mean, I can just tell my workouts were three to five times more effective because I had this guy. Even when he would tell me what to do and do it by myself, it wasn't as good as when I was with him. That's what a teaching coach should do for education, right? That's what it should be. So it's trying to get your mind in shape, right? Regular school is like going to a gym, but everyone's got the same equipment, everyone's looking the same weights, and everyone's gonna do the same lesson, right? So if you look at the, on a standard distributed curve, that's great for the majority of the class. There's some people, they're never gonna be able to lift it, they're gonna be left behind. And there's some people that's gonna be like, okay, this is not a challenge, right? So there's like two to 5% on this one side, right? Who would succeed no matter what? So they're not getting anything out of it, but on average, right? You're better off having attended, they're not having done it, right? You're gonna be in better shape if you do any kind of workout, even if the regimen is very standard. Then if you did no workout at all, and also you've got your peers around you to cheer you on, which is a big thing, right? People kind of discount that. I happen to homeschool, I've got three boys, I happen to homeschool them, and you know, everyone, when you say homeschool, you know how to make friends and all that kind of stuff. Well, you gotta do other things about it, but it is an important thing, but it's the first thing everyone jumps at, right? But they don't think about this when they talk about edu-tech. So edu-tech is like, okay, you don't need a teacher or whatever.  Almost everybody is gonna be your news clothes hanger, right, because you are not self-motivated to educate, right? Now that two to 5% of people who are good at just naturally good learners, they might use this. So, you know, talk about the build it and they will come mentality and how do you get market share as an edu-tech company? Well, what you've really done by going with this model is you've eliminated all but 95% of the learning audience because they're not gonna do your thing, right? So our focus, again, is on, we're not, there's a group called the Acton Academy in Austin, Texas that's starting to get really big and they're doing a lot of Socratic Methods style of teaching, right? It requires that you have exceptional teachers who are really dedicated and it's a fantastic method that's not gonna solve this generation's worth of educational challenges, right? We don't wanna leave this generation behind. So what are we trying to do here? So a little bit more about my background. My parents were both educators. I was born in the Navajo Indian Reservation in Winter Rock, Arizona, because my parents had to leave Arkansas to get a good paying job in education. We don't pay good in the government, the federal government does. And my dad was a principal of the school there, my mom was a teacher and when we were about six years old, they wanted to move back home. So I grew up in Arkansas. My dad was the assistant superintendent of the Fort Smith Public School System. My mom was a seventh grade geography teacher. My dad started his PhD program when my sister entered kindergarten. And he got his PhD when she graduated high school. It's the longest PhD program in the University of Arkansas history. His PhD thesis was trying to attempt to measure the impact of educational outcomes by how good the administrator, the principals were, right? Dad's an administrator, you know? He's thinking, we're gonna prove this once and for all. The man taught himself statistics. I remember him going through all this stuff. And I mean, and you'll collect the data over time. Did this thing end of his dissertation? No measurable impact whatsoever, right? I think it was probably a disappointing outcome for him. But it made no difference. There was no way of seeing there was any correlation between good administrators. Of course, there's good correlations between teachers. And I asked, you know, this made me interested in other things that were going on. And so I read about other things. And really the thing, the impact of educational outcomes more than anything, by far, like nothing even came close, was parental participation. And it didn't mean that your parent was teaching. It means that your parents showed up for your football games or whatever. Your parents just showed by, you know, showing you that it was an important thing and making education a priority. They didn't have to teach you, right? And so one of the things that we wanted, you know, a lot of edu-tech that's inside the classical teaching system right now is focused solely on the teachers. And what we wanna do is we wanna focus on learning. If we wanna focus on learning, it means when you also need that we, absolutely, we gotta help the teachers, right? We gotta help them be good coaches. We're gonna enable them. But we gotta give resources to the students and we've gotta bring the parental participation. And we gotta give them an opportunity. Because what is the typical experience of a parent and their child's education system if they're in the classic school network? It is Sunday night, little Amy comes up and goes, daddy, daddy, daddy. I've got this assignment to do my own. And, you know, you may not have seen this subject in 20 years or maybe it's math and they teach math differently and so daddy, that's not how they showed it in class, right? It's not a positive experience. And so we can, we hope, with automation and stuff, build tools and things to let this parent know what the kid's been exposed to, even give the parent, hear some questions and stuff that you can do to, you know, be involved in your kid's education, right? Just help the parents out. Because lots of times parents don't have much of an education, right? It's the first time. So, right? Educate companies think that they've got the one true way. You see all these programming language education systems like, this is the way to learn Python. It's ultimate, it's great. No, people are different types of learners. Some people learn visually. Some people learn audio. Some people learn by just knowing the first principles. Some people wanna know mathematical formulas, right? Which means you need to make at least three types of curriculum if you wanna have the ultimate system. Curriculum is extremely expensive, right? And also, if you're only going after... If you really only market as these people who are good self-educators, well, in the classic VC perspective, you're either a vitamin or a cure is the way they measure you if you're a good investment.  You're not a good investment.  You've got the potential to be a unicorn, right? Almost all edutec companies, their ultimate top-level possibility is only as a vitamin company, right? So what we wanna do is we wanna help teachers be better coaches. And so the most effective way to learn is with a professional coach or a teacher who is focused on your learning goals, right? And the most effective edutec is the one that makes that teacher more capable. So one of the things that we have that has been a big thing for me, I make a lot of domain-specific languages. We deal with ontologies and taxonomies. And also, so my client, by the way, is a company called Axorn in Thailand. They are the largest Thai publisher of educational curriculum. They have 40% of the commercial market, eight out of 10 Thai students who are in a Thai curriculum, whether it's public or private school, are using some of their books. Now they see an existential issue that books ain't gonna be the way to teach another 10 years from now. And so they have bought me on, I have signed on as a consultant as their CIO, to build an entirely new division, a digital division for Axorn in Thailand. And of course we're going to adopt and use a lot of open technologies, open-source technologies, and we hope to also participate and create some protocols to enable edutec to work together with this focus on learning. So this is my call out here for people who are interested anywhere around the world. Our immediate content inside Thailand must be in Thai, which is by the way a challenge for doing a neuro-language programming, or natural language processing, because we don't put spaces between our words in Thailand. It's a computational challenge just to separate the words. But we're working on that. So we have here the concept, we're introducing like an ontology of knowledge. Now an ontology is not specific to any language, right? It's not a cultural thing. So let's just pretend that our learning goal is to learn how to do division, right? So we have the orange box division, right? It depends on being able to know multiplication, which is an ontological concept, which depends on knowing addition, which depends on knowing what natural numbers are. Division also requires subtraction, so you can do the remainder. So we have these concepts and how they're related together. And what we do is we can take Axorn, it's a family-owned company, the Kungtawan, the current CEO, very, very much a guy who wants to have an impact on education. He is constrained by limits of having to work within the Ministry of Education's requirements, right? But he's still had a fantastic impact. He's behind making this happen. We've got 30 years worth of content. We're going through all this content and we're going to ontologically tag it. So imagine that we have the grade one map primes system, right? So we tag numbers and counting. And then also there's some other content. We've got a Sesame Street video. We've got a counting song for pre-readers. We've got a role-playing game over here. So we tag a lot of different content. And now, as students are introduced to stuff, our system will know what content that the students have been exposed to and also the type of content, right? Now, so we want to establish learning goals. Now the MOE in Thailand and almost all countries have specific learning outcomes for certain subjects, for certain students of certain grade levels. MOE has that. Those map very closely to ontological models as it turns out. So the MOE has some learning outcomes that are required by the government, but also the schools, the parents, teachers, students can set learning goals, right? You want to learn about the Renaissance and the Roman Empire. Okay, well, we're gonna generate a custom curriculum for you based off of the curriculum that we already know. That's gonna start with, okay, Christianity, Constantine getting in the Roman Empire and then the schisms and all that. And it was map. Here's a custom curriculum that is focused on your learning goals. So you can imagine if you've no doubt been in a situation where you're trying to learn something and you need to learn the prerequisites and the prerequisites are a couple of semesters worth of material, right? Well, what if you only need, this is one of those 20 chapters, you only need chapters one, four and seven to go to the next step of your learning goal, right? If everything is ontologically tagged, our system will discover that and only expose that to you so you can go through at your own pace, right? And so what is your pace, right? So you have to measure learning outcomes, all right? And what is the one thing that teachers hate? Can anybody guess what is the number one thing that teachers hate more than anything else in the world about being a teacher? And this is at all levels. Sorry? Fair to complain, well, maybe, I don't know, but it's grading tests. Oh my God, because you gotta give a quiz because you wanna know if they're absorbing your material or not, right? But then that means that that night you're gonna be upgrading tests at home rather than doing something enjoyable. It is, you know, bad. And also there's this latency, there's a delay between taking the test and then getting the answer back, right? It may be tomorrow, or if it's a more comprehensive test, it may be next week. And so your mind determining did I really know this material or not and how can I do better at it is got this big time separation where you're not really in the mode. So we want to do gamification over testing. So this is a system called Kahoot that I think a lot of people have encountered and it lets you make little gamified things. So the teacher will have this up on the board and the students will have on devices and they can in real time do their own questions. It's a game, it's competitive, five minutes, thank you. And they can immediately see the feedback as to whether they got it right or wrong and the teacher doesn't have to do the grading. Matter of fact, at each end of each question, this is, so I'm very much into agile and we're doing planning poker. If you've ever done planning poker, everyone estimates at the same time, people who estimate at the very low end or the high end need to explain their estimates so everyone gets a consensus why. Well, so people who vote for the things that are wrong can explain why they voted that answer, why they thought and so the teacher will understand what aspects of it they didn't understand and the teacher will be able to provide more content and by the way our system, because the ontological stuff, will know what these measurements were and will say okay, for this class or even for the student for their homework tonight, this student needs more of this content because they didn't do so well on this but they don't need any more of this because they've already mastered it, right? So we're constantly reorganizing and re-optimizing and oh by the way, it knows what type of content the student has seen. So it starts learning what type of learner each student is as an individual. Now a teacher can't do that for all 30-something kids in their class, right? Our system will start to let the teacher know that and will start to let the parents know that, right? That's what we're trying to build. So this is our continual adaptive curriculum, right? So in agile, we like to discover things rather than prescribe things, right? How effective is this? Get rapid feedback and the things that work we double down on, things that don't work we toss out. Well, we're gonna create curriculums out of existing curriculum that do this and it's gonna do this automatically. So students will be routed to more supporting content for concepts with poor understanding and will skip over additional content for concepts already mastered. We're not wasting time consuming content not relative to our learning goal. And talking about different learning styles I need to get through this quick. We need more time next year. All right, and remember we have this curve, right? Average students, students that are poor, students that are great. And we wanna involve the students, right? Anyone know what is the best way to master a subject?  If you can teach the subject, like the first time you teach it you think you're good at it and then you try to teach it to somebody who doesn't have the core concepts, oh my God. Once you can do that, now you've mastered it. Well, guess what? We've got these brilliant kids, two to five percent. We've got these kids that are being held back. And the brilliant kids are not being challenged, right? There was, my son is one of those kids, the teacher always used to play and he always looks the other way. So is he getting any grades? Well, yeah, he's the first to finish his test. Well, he's bored. I learned to hate school as a kid because I got bored because I was stuck in the standard curriculum. Sammy fortunately needs, you know, we're homeschooled.  I can't even comprehend that myself personally. So what we want is we wanna give these same tools like the cahoots and whatever, and we wanna let those kids build content to help teach their fellow students, right? This will make the top smartest kids, it will push them and will make them better and it will take the kids who are being left behind and we won't lose another generation of people because we have a poor education program. So these are the types of experiments and we're doing dozens of experiments. I've signed up to do this for about two years. So the first year is just a lot of experiments, a lot of things that I met the only, Fosse is so awesome. I met the only office guys yesterday and like a whole lot of their clients in Europe are educators and it totally makes sense. We're gonna evaluate them. We might make that an offering to the schools in there. There's a lot of other challenges I can't get into but if any of this inspires you, please, please, please contact me. I want to be involved with what you're doing. We wanna evolve more open protocols. Like the challenge for CalHOOTS, for example, right? You'll find the good teachers will incorporate CalHOOTS into their program but they have to make the tests and all that stuff, right? A lot of the teachers, especially in these rural areas, they don't have the time to do that, they don't necessarily have the skills to do that. So we wanna make a lot of content for them and it needs to be integrated together because whatever the score was that somebody had on CalHOOTS, no system is gonna know what that kid's score was because CalHOOTS doesn't integrate with anything else. We need that to be part of the larger learning system and learning management systems are really, generally, horrifically awful. They're built for teachers and administrators who are also technical, which just eliminated about 95% of all the teachers. The teachers hate them, frankly. The administrators like them but that's, as we know, the person who's gonna have the least impact on our learning outcomes. So we need to help our teachers be better coaches. We need to help our students learn better. We need to get the parents involved and that is my mission, thank you very much and any questions or comments, I would really appreciate it. Yes, sir. We need to get it. I initially dropped out of a college but now I'm running an academy with a lot of students full degree, one month and I mean, one semester and two weeks University of Arkansas, well that's my educational background. Go at it. So the presentation was amazing. So I just have this thought. We are all talking about education technologies but I believe people are less focused on learning technologies. Amen, brother. So as much as we are focusing on education technologies and how you said you could map these curriculums and tag these curriculums that will help, how do you see that, like we are all good with technologies and how do you see that we can make more technologies that could not just help teachers to, I mean, not just help students to watch the contents through some videos or through some contents but help them experience the contents. So that is what I consider a difference between an education technology versus a learning technology. Learning technology should deliver them experiences instead of just watching the content. So what is your opinion on learning technologies versus a learning technology? You're, we're completely in line and that is the thing, right? And like the gamification is the huge, huge thing and the kids really do love it. I've talked to kids who have used CalHOOTS in their classes and they all enjoy it. They would like to make their own. We're going to enable that, right? It's, you know, you got to make them feel good about themselves on the outcome. And that's the challenge. And let me say it's one of the things that like when I was talking to them, I started talking to them in December and we just started doing this as of February. This is brand new. And I was thinking, okay, I know how to do this for STEM. How do you do this for humanities? How do you do this with kids who do not yet know how to read? That's hard, right? That's a hard because, right, technology is the multiplier, right? You got to find out what is the strengths here that our technology can multiply?  That technology can take off their hands. And so now the teachers will want to use it. They won't see it as a burden. So if we make the teachers want to use it, we make the kids want to participate in it, that's how we have to do this. And how to do that, I've got opinions. I'm always full of opinions. And we're going to start measuring learning outcomes and try to figure it out. Thank you. Yes, sir. Right here in the front. Let's take a couple more questions. Hey, thank you so much for the talk, Benjamin. Really involved in education myself. So my name is Aditya. And just want to ask you, so Kahoot is great at doing assessments. And I would, I have the opinion that it's one dimensional. Correct. And 21st century learning is not just about getting the answers right, right? It's repetitive. And there's something called Kahoot fatigue. So what would be your comment on making assessment more dynamic? Well, so it's, so it's not just, so I didn't look at Kahoot strictly for assessment, although that's like one of the good important things. But we also looked at it as a way like, you know, kids, I think it's very important that like for my boys, for example, I like them to do projects. So they're bringing in multiple disciplines at the same time. So it's not, this isn't just a math project. This isn't just, you know, English project, right? My kid, remember Tony when he was two years old burnt some toast in the thing and it turned black and he's going, I wonder what that is. I said, well, that's carbon. I said, well, why don't you do something about what the carbon cycle is and learn about that. So from his burnt toast to, you know, plants and the sun and all that kind of stuff, do a project. So we want to provide tools and Kahoot is kind of an inspiration for that with that kind of a model where the kids can create their own content, right? So they can do their own offering system very easy and then do gamified challenges is what I call them for the assessment, intermediate to that. So the kids can see if their own efforts to their classmates is effective in their classmates learning or not. Acton Institute also has this great program where kids, like you're going to do a book report. Kids vote to see if you should get a badge that you accomplish this. So we're gonna do, we're using AI art, which my CEO demonstrated yesterday for our IDs and you can have badges that show you did a good book report. The second time you do it, is it better than the last one? The third time you've done it. Okay, now are you mastering this? So, and it's gonna be voted on by the other kids, but then it gets audited.  Programs like this that get introduced by the Acton Institute's kids helping teach the kids and the parents or both parents and the teachers are now like agile coaches, right? They're not doing the work. They're not telling them how to do it. They're just enabling and make sure that they put them in a position where they can succeed. And thank you very much. I think Benjamin will have to come back next year to tell us how it's going. I'll see how it's going. Hopefully publish all of this into the open source, right, for all of us to use. So thanks a lot of applause for Benjamin. Thank you so much.