(upbeat music) - Well, it's great to have you back, man. - Good to see you. - Last time you were here, episode 289, I was like a year and a half ago, you closed up, like we literally stopped the cameras and then you're like, yeah, I was doing some work for Doppah as well. And you just lay that one on us. And I'm like, well, that, I mean, you supposed to say that at the beginning of the podcast, but now you're telling me like, oh, it's not that big a deal. How's DARPA not a big deal? I mean, I'm like a big DARPA fan. - Yeah, I know, so I will, I've had maybe, let me get this right. So how many grants have I had from DARPA? - So DARPA is a funder, right? - They're a funder. - They're a grant funder. They give people money. I think their reason they were established, you know why they were established? I think you can check this. So their mandate was like to not, when Sputnik went up into space, the US and were not expecting that satellite, the Soviets launched a satellite. I believe it was in the 50s. - I think that's right. - And it basically, DARPA was established to eliminate strategic surprise. So they were so basically that they wanted load of money, fund people to do crazy things and also to have a mandate to do stuff. So arguably DARPA might have had something to do with say the internet, right, self-driving cars. And a few years ago DARPA started looking at chemistry and AI, like many years ago, way before the hype now and there was a program they started called Make It, actually. And the person who started it, you know, they kind of used some terminology from one of my papers. And I was kind of a bit grumpy. They didn't offer me any funding, right? 'Cause they had the gave money to MIT, to Stanford Research Institute. - DARPA plagiarized Lee Cronin? - I didn't, you used the P word, they were inspired. I said anyway, they, I remember they got the cool with me and I was like complaining, but early, that they used this paragraph and what I was trying to do and they were like, "Dr. Cronin, we're phoning you up "because we were going to talk to you about that." I was like, "Okay." And basically what it turned out is they wanted me to put in a white paper and I said, "Okay, I want this, "you know, it's a silly $1." And they said, "Well, we're not asked for a little bit less "and do this thing that fits into our program." You know, it's US taxpayers and you're one of the, you know, few groups overseas doing this thing and we think it would be valuable for us. - And what was the thing specifically? - So it was to, it was to, it was part of their make it program, can you make molecules on demand? - Right. - In theater or, you know, on the moon in Antarctica, whatever, right? How do we do chemistry robotically? And then when they ask about that and I've been building chemical robots for years. - Hey guys, if you're not following me on Spotify, please hit that follow button and leave a five-star review. They're both a huge, huge help. Thank you. - You've been building chemical robots for years? - Yeah, yeah, yeah, yeah, that's a dense statement. For, since 2012, right, 20, so about, yeah, about 14 years. - How would you define a chemical robot for people out there who are unfamiliar? - A robot that you give instructions to and it will do chemistry. So, yeah, it's fit, it's out, so I made, I can tell you about it, but let me answer the darker question because you asked it. So that was the first grant they gave me and make it and they carried on giving them money there and then they had a one-on computation using molecules to make molecular computers and I got money from DARPA there and that was in a US consortium. So there was a couple of the groups in the US, right? And then there was another grant that gave me for kind of using AI for discovery. So they were the three DARPA grants. I think there's three DARPA grants. - What year did they give you the AI grant? - Oh, I can't remember, I mean. - Bob Part. - 20, 19, 28, 19. And then it carried on through the pandemic. It was a bit tougher in the pandemic, but DARPA brilliant organization, right? They go where the experts are. They don't give grants to people in countries that are probably anti-America, I would say, right? So don't just say. - So they're not, they're in fun bin Laden, this way. - So, and also they want to start new fields and they want to start fields that are going to obviously be of strategic importance, right? And the UK and the US have done a lot of hookups in different scientific disciplines for a long while. So I thought that was quite good. And I made a molecular computer chemicals to do computation as well, 'cause I've wanted to-- - What does that mean? - Yeah, I don't know. - Yeah, I mean. (laughing) - So, well, I know what it means now. So what does a computer do? So a computer, we're around going everywhere, but anyway. Let's start with what is a chemical computer? A chemical computer is a chemistry set where you could put in inputs, the data, you input the data into the chemistry somehow. And the chemistry would then take that data and process it using chemical reactions, run transistors on silicon. And then you'd read it out using it some method. And I was like, I built a chemical computer using a thing called the blues-off saberskinsky reaction, which is a chemical clock. And all it does is it goes tick tock, tick tock, or red blue, red blue, red blue, okay? So basically, you put a lot of chemicals in the pot, you could just take, you know, maybe just a beaker, which is like a glass, put in half a, fill it up halfway, put in some chemicals, and without doing anything, just leaving, look, watching it, it would flash. Red, blue, red, blue, red, blue, whilst you're stirring it. When you stop stirring it, it would basically stop, but then spontaneously flash one color or another. What's called an excitable media? So a bit like how, thinking about how neurons flash. So that's a cool idea. Why don't I just basically make a grid of stirers? So I 3D printed a grid, basically it's about the size of a small book. And in that grid, there was, it was seven by seven grids. So 49 little wells, and I put a stirrer bar in each one, and I put a little motor under it, and stirred them and put the chemical reaction in. And all the colors went across the grid, and I used the web camera to basically read out the colors. And so when the stirers were on, I could, that, that was a, a one. When the stirers off, that was a zero. And I basically then put, basically printed in ones and zeros to represent some input, and then just read it out, and then worked out what it was doing. We kind of just made it up, but to start with, yeah, what does that tell us when you're done? Well, at that, hey, it's a DARPA project. Yeah, it's supposed to be crazy, man. So what it was supposed to do is, is could I somehow use the, because remember the BZ is a clock, TikTok, TikTok, TikTok, you put a load of clocks together, and you allow them to synchronize. As they desynchronize, you could process some information. So we actually used it to classify, and we used it to make a primitive neural net. And the idea was the neural net literally used no power, and was quite good at error correction, and could refine images. So the same way you would use chat GPT, or you'd use a kind of Nvidia's architecture to do gradient descent. And what is gradient descent? Or it changes the weightings in the neural network, and to basically kind of maximize its training capability, because obviously you have the weights and the activations, two different things. But basically, this was a chemical neural net. It was the idea. It was the first step. I'm now making brain gels, but that's in those structures. You're making brain gels now? Because we put that and put it in a gel, 'cause it was all liquid and sloppy, and the memory wasn't that good. But if you put it in a gel, then maybe you could then basically use the polymer gel to flip to switch in such a way you could teach the system to learn for a longer period of time. How does that work scientifically? No idea. That's why I did it. So you're trying to figure it out? Basically, yeah, I mean, look, again, we're all over the place, but why not? I was inspired by the episode of Pickle Rick and Morty. And I was like, well, and so. So it's like, I took a Gerkin, right? And attached the Gerkin to the mains to 240 volts. And then put in low, low, my workshop I have at home. And used a bunch of electrodes, and I tried to program the Gerkin to recognize difference between a circle and a square. But it kept exploding. It kept exploding because it kept heating up with them. So I had so long. So I took the Gerkin. I thought the Gerkin could be a good good idea. It's like a Gerkin computer. Like literally, you could just be making this up, right? It's like, yeah, just anyway. So Gerkin heat it up to put it in the, it sounds ridiculous. You heat it up by putting it in the 240 volts. What would happen is sodium ions, potassium ions, because it's in salt. So you've got this Gerkin, you soak it in the salt. So it has this salt in it. It's conducting when you put power, when you put electricity into it. When you put alternate and current high voltage, it heats up. And basically the ions can move around. So it literally makes an excitable media, a bit like the BZ reaction, like flashing on or off, but here with the Gerkin. And then when I put in little electrodes, I put in little grid, and I was then trying to basically train the Gerkin to tell the difference between a square and a circle, because it was made malleable. it's a bit like taking some, taking some cement.
and making it liquid again. And then you make it liquid again, and it learns something, and you'll set it. But the thing is, the GERK can kept exploding before I could actually train it. - And this is in your lab at your house? - I did at home, yeah. I mean, I don't think their university would be too happy with it. - That's brilliant, yeah. - So now, fast forward to the brain gel, I was like, well, look, if I could take a gel, and then make the gel conduct, right? So it conducts electricity, bit like a, yeah, like a wire, but then put in electrodes on one face and the other, and program one surface using a camera, so I could just take a visual feed and plug it into the gel, and then basically read out, as I show the camera to different objects, can the gel tell the difference between the edges on the objects, and train it in the same way you'd use OpenCV, or some kind of silicon-based system for edge detection, right? It's a bit like a user Jetson Nano, or something, right? And I was just playing around if I could use material to compute. Turns out you can, but now you're like, when you said, well, how's that work? And I laughed. Well, it's not because I'm making it up, but because the way you program material is the material responds in time, according to it stimuli. So it's very much trial and error. So it's a bit like how the brain is evolved, like the brain has evolved over billions of years, and so the brain has a number of different kind of programming periods. It was programmed by evolution, so your brain, let's say, is 3.8 billion years old, so that's time number one. Then you are created by your parents, so over a period of nine months, your brain is growing in the womb, as your brain is starting to program. When you're then born, obviously, between you go through massive developmental surges, so age 21, 22, your brain may be fully almost there. So then your brain is unable to process data in real time. So there's all these different developmental stages so the brain is able to evolve, grow, be programmed, activate, and then continue to work. And we have no idea how our brains work, and what are unique to brains? Well, sentience, consciousness, the purpose and a living system that will tell you that they are an individual. You talk to all humans. Most humans can communicate with, we'll claim they're an individual. Do you desperately need a nicotine pouch every 15 minutes just to feel normal? So does Joey Diff, he's a complete addict, which is why Diff started using ultra's new energy pouches. They've been an elite upgrade for this fiend. Ultra pouches are instant energy in one pouch. Ain't that right, Diff? He's been using them obsessively for about a month now, and they've been giving him a huge intense energy boost when he needs that extra kick in the morning, burning work or before working out. These are 100% nicotine free pouches, and they give you energy in a way that's completely different from nicotine coffee or other pouches. Ultra energy pouches still contain some caffeine to give you that little lift. The real difference comes from their other ingredients, including altheanine to smooth out the energy and curb the crash. Vitamin B3 to turn carbs fat and protein into brain fuel and vitamins B6 and B12 for bounce mood and recovery. So unlike nicotine that might only help for 10 to 15 minutes, ultra pouches deliver instant energy that lasts for 30 to 60 minutes. So why do you see me passing so many of them under the table during podcasts, Diff? To make sure he stays awake. The best part about them is these are clean, truly good for your pouches. Zero nicotine, zero calories, zero sugar, zero sketchy gas station chemicals. Ultra is the ultimate guilt free pouch, delivering instant energy, mental clarity and boosted mood without nicotine sugar or calories. Ultra is trusted by pro athletes, entrepreneurs and engineers around the world. It's for everybody. And today our listeners can get the ultimate guilt free pouch for 15% off using code
[email protected]. That link is in my description below. That's takeultra.com, link in my description below for 15% off with code julian. After you purchased, they're gonna ask you where you heard about them. Please support our show and tell them I sent you. So you think the brain is the thing that is strictly just programming that in and it might not necessarily mean that that's the case. No, no, I think there is something very interesting. I don't think it stops the brain. I think biological systems are very complicated. But I think humans are unique in that they will claim to be an individual, right? With words, if we teach them language. And I think that's something that we don't understand how chemistry gives rise to consciousness and how chemistry gives rise to, you know, the fact that I will claim to be me and I have my own particular personality and do stuff. This is very important in this time because we're viewing the AI as our entities that are sentient and they are indeed they are not. Yeah, you've made a lot of arguments on this because you think that, for example, a lot of AI tumors are making leaps that the AI can exist without human beings in the future. And you don't agree that that's the case. Yeah, clearly not, it's fantastical. Why do you say it's fantastical? Well, we've not seen any evidence of that. So if we think about the origin of AI, right, if you go the way back, origin of life, the AI is produced by, well, let's say the origin of the term AI was at the DARPA, sorry, no. Wait a minute, don't do that. The DARPA, the DARP myth meeting, right? Wish you know, you can check it. - It's like Freudian slip rate there. - Sure, okay. - Whatever, let's build as many conspiracies as we can. Go. But I think DARPA have funded some AI work, right? Right at the beginning part. So DARP myth college, the term AI was kind of coined. - When was that again? - In the '50s? - I mean, I don't know, '56, I don't know. But a long time ago, maybe a bit later. And so, but if you think about what a computer is, a computer is a deterministically built system. It's switches, right? And the way those switches work is, we build, a computer is built out switches. Those switches have high and low. You put those together to make logic gates. Those logic gates, the universal logic gate and the computer is a nand gate. - A nand gate. - Yeah, a not-and, right? You can build everything with not-ands, right? So not-ands are literally, you can build memories, you can build everything. The way you architect those together, you build the silicon infrastructure for, everything we have today is based on that. There may be some differences that I'm, you know, electrical engineers watching this, listening to this might be shouting, go, no, that's wrong. There are other things called ASICs, which are basically that you might be able to do what we would call neuromorphic computing. - Neuromorphic. - Where basically you could have an analog voltage. So in a transistor, you basically, you would have a voltage between zero and five. Five is high, one, zero is low, zero, and something in between. And if it's on the zero side, you could call it a low, and if it's on the five volt side, you could give a little one. But I'm not a qualified electrical engineer, so I don't know how the ASICs are built today. I've designed some ASICs for fun. - For fun. - Yeah. Well, I want to build a brain. So if I want to build a device, a chemical brain, I have to design a. I need to have an analog kind of electrical system for addressing the chemical brain. But we'll get there later. - Yeah, we'll come back to that. - So the most important thing with a computer is like it's fairly deterministic in some regard, and what, sorry, let's not say that, it's digital. And so that means I can put in the inputs in there and go on. So with ARs today, they're based upon digital computers, and they use all this digital infrastructure, we take massive amounts of data and train a model, and the model can do splendid things. But the dooms say that these models could run away. And I agree the models could run away with bad humans running them, right? There's always a human in the loop. The human is turning on the power station. The AIs, although we use terms recursively self-programming. I mean, it's a bit like you and I could build an AI now. We could have a loop in a program like, you know, do this thing, and if this thing occurs, then do that thing and carry on until either hits the objective or you, someone turns off the computer. Now, that's always been the case, right? Those loops have always existed. So the AI dooms are kind of stuck in this, like this kind of fantastical reality whereby they say that AI could overtake the world and cause a nuclear explosion or something else. What I think is more likely is that bad humans using the AI to do bad things will happen. And I do worry about that. So I'm not dismissing AI dooms. I'm dismissing AI dooms who are saying this thing will happen because magic on its own. Yeah, got it. And I think that is actually a major worry because they're talking about magic. And actually there's just some doomer go at some bad actor going, I'm going to use the AI to crack into this system and do some damage or I'm going to use an AI to bot system that will basically do some social engineering on social media to cause some kind of effect, right? So I think that I haven't seen any evidence of sentience in any AI, right? The sentience comes from humans exclusively. any evidence of sent-ins you get from the internet, the training on the model.
Or if you say, "A Claude, are you alive?" Claude reports, "No, I'm not alive." And they'll use "I," and this anthropomorphization is just to hook you to be addicted to talking to the entity. What if it's a technicality, though? And it doesn't get the sentience, but because, and I'm going to weigh over, simplify this for a minute, we're able to eventually create technology that isn't quite simply plugged in and unplugged to be able to do that. Because of that, a nonsensitient but extremely intelligent, artificial intelligence, who has no ability to empathize, obviously feeling sort of emotion or level of humanity, took actions that it doesn't understand the grave consequences of. Do they have an argument for something like that to possibly happen? So I don't quite understand the statement, but I know what you mean, so I'm not going to be too obtuse. But AI's, are they intelligent? We have to define intelligence. What really makes me very confused is there are people out there that say, "In next year's the AI will be more intelligent than any human." And what does that mean? What is intelligence? If you can't measure something. So could the AI call something to happen on its own? No. Could humans not understand how to set up a system call something bad to happen? Think about social engineering. I don't know. Take any system. Like, this is kind of hard because I'm not a qualified, but let's say we're going to create a type of by-law in the city that says, right, we have to have trees for you to get planning permission in the city, every time you build a building. You have to have a tree or every corner or something. So suddenly, before you know it, there's just random trees everywhere. And I was going to say bless you, but you've probably got that, but bless you twice. It's dying over here. So what happens is when humans make decisions and policies, they get propagated and they get propagated by systems, whether it's in a corporation or in an institution or in a software algorithm, right? So those things get propagated and they're unforeseen consequences of them. And I totally buy that AI is trying to achieve an objective, could do bad things. But those bad things, humans are in the loop all the time. And I guess what I'm trying to say is the AI is not bad. The human is bad or the training data is bad. Right. And that would, if I agreed with that point and you might be right, you know, I honestly hope you're right. And it is in control of humanity, by the way, selfishly speaking here. But like, let's assume though there are some sociopaths who have their hands on the trigger with these things, which I think it's fair to say some of the technocrats we have in the world, not all of them, but some of them may fit that bill. What's to stop people like, you know, to put a name on it, like a Sam Altman who jokes about humanity ending? Let's just stop him from being like, oh, you know, today I want to play fucking World of Warcraft, but with AI and let it go wild. So look, I have a lot of sympathy for people who are building companies and building technologies. I'm building one myself right now, which we can talk about. I think we have to kind of, we have to take a step back and say, what are we built? How are we building our technologies? How are we regulating those technologies and how do we then get feedback from the regulation of those technologies to make sure that good things are happening to humanity? So if we, let's take an example, whether this has already happened, right, we got the internet and then we got social media. So what was the critical failure in social media has given us arguably, I don't think anyone would argue that social media is particularly nice right now. What's the failure that I think there's so there's one critical thing that people should have done, which was the policy maker should have said to social media, they should be treated like publishers section 230 or whatever, I don't know what the US version is. So if you treat like a publisher, that is anything you put on your, on your, on your platform, you have to basically hop be held accountable for. And so that you, there you don't, when you start putting nonsense out there, it can be taken, you have to say no, it's clearly alive, put it down. Right. So basically Facebook and so Facebook and X and Instagram and all the, and all these entities are not accountable for the stuff they put out. Now that's, for me, that's a real problem because basically that, that entire decision, although, you know, they're a medium, it's a bit like you can't hold the type, the person who built the type, the printing press liable for the bad books printed, right? Get that. The same way we might argue when you talk about my chemical robots, am I going to be liable for anyone making any bad chemistry on them? But I, I do think there's something we can learn from the social media. And the fact we didn't regulate that, we didn't hold them accountable. And so it's very hard to know how it's going to revolve. However, having said that, that if someone invents the social media, there's quite good as in, you know, a nice place to be and not a hellscape, right? And if we can work out why humans are very good at, be it, you know, you get a anger for attention. Right. Sorry. So, you know, if there was a social media system whereby, I don't know what saying, it should be like, you know, some kind of Mary Poppins world where everyone's like, you know, it's all flying around and all happy. But there, I guess we have to understand the psychology of social media and the negative effects that has it, particularly on teenagers. When I grew up, there was no social media. That's right. I've seen that social media has been probably a negative for a lot of teenagers, but some might argue it's like, well, in environments where they don't have access to social centers or youth clubs and things, there's people can work, play online, play games, interact one another, support one another, and we don't see all those positive things because only the negative things are amplified. So when it comes to AI, we have a similar quandary, which is how do we, how do we let the free market and free humans dictate what's happening? Because there is one argument. If you look at the difference between, say, Amphropic and maybe Open AI, Amphropic basically won't let you do anything on the models because it's got some kind of higher purpose wired in. Whereas Open AI is like, no, no, I'm going to serve you as the entity. And actually, if I'm a, I want to, and if I choose to use the object to do bad things and I'm breaking the law, then I should be held accountable. Sure. Whereas like, and I think so, I, I'm not sure if I'm getting that correct, but it seems to me that there is a kind of a split right in this right now. But, but that's kind of obscured by the doom is saying AI could run away. And I don't understand the mechanism for running away. I do understand the mechanism for tinkering. I do understand the mechanism for, but may put disinformation out there or for doing some kind of, now the conspiracy theories that don't aren't yet possible. Here's one crazy thing. Look, there's no real conspiracy theories in history, not many, because humans can keep them secret. But if we had good AIs and we could, you could play around with the future with the AIs pretty well. And that might be one thing to be worried about. Now, you know, is there one big, because if we say that, you know, one particular political movement or post-second world war when the winners talk about what happened, could that be one big glorified conspiracy theory, because obviously the winners write the history books? Yeah, there's always a percentage that's written by Victor's for sure. As far as like, when you look at a story, it's never 100% what was said. I take issue with when you then try to say, well, if 5% wasn't what we were told, therefore 100%, it's not, you know, you got to be careful with where you go with that stuff. Absolutely. Absolutely. And I think that's really important. Of nowadays, I think that critical reasoning to what can I verify and what do I find impactful to me is really important. So I think one of the things that I think AI will accelerate the teaching of critical reasoning. Right now we're in this real, I worry a lot about how young people are going to be allowed to get their first job, you know, make mistakes, get the training, the mastery is required, have the hard work, emotion, frustration is the best trainer, right? But whereas like people, well, you don't want to get frustrated now, just use chat GPT. And so, but I think this is an aberration. I think these tools, or actually a lot of them, are really good. Like the coding tools are amazing. And so I do wonder, and this is me actually shifting my emphasis a bit, if AI might actually save us all, save us all, save us all because social media is such a cost of fuck, right? If you listen to my show, you know, I take my supplements every day religiously. And you've also heard me talk about how the supplement industry is really crowded with a lot of fake products too. On top of that, everybody in health disagrees with everybody. If you've ever Googled a supplement
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They also have essential capsules, ipolyphenol, olive oil, omega-3, collagen peptides, and more. This is science-backed, precision-dosed, no BS. For a limited time, only new customers are going to need 20% off, plus free shipping at blueprint.brionjohnson.com, link in my description below by using Code Julien at checkout. That's Code Julien at blueprint.brionjohnson.com, link in my description below for 20% off. After you purchase, they're going to ask you where you heard about them. If by using AI tools, we can actually allow that help us do critical thinking, help us verify things. If we understand that the current AI is as generated, are not very good at actually, as classically trained, weren't very good at being correct. But actually, they're getting better at being correct, because you can say, "Hey, go out and check the literature and check if this thing actually happened." And help me store man or steal man, a particular argument. And then also help me understand, as objectively as possible, how I might frame that argument. Because if nothing else, these AI's might be able to allow you to do one-to-one teaching. They've got infinite time, infinite patience. If you use them correctly. Well, we might be, yeah, if we can use anything incorrectly, like I say, so I'm kind of, as you might tell in this conversation, where I'm just saying wildly contradictory things. Strong opinions loosely. Yeah, I mean, for sure. But I do think that the Doomers are kind of out. It's a bit like, you know, the Doomers serve a very good purpose. But I just wonder if the Doomers could actually help us by shifting their Doom to the real issues that we need to deal with, such as bad actors using the systems. Right. Well, that's the thing that I'm thinking about with your world right there that you're painting. On paper, that would make sense. But again, if these different platforms, because there's many of them, are going to actually be a positive and help teach critical thinking and things like that for a person to be able to do that themselves. Then I think a requirement for humanity for all of them across the board would then be you need to open source all the code at all times. Because you don't want to know or you want to make sure that there are not human beings, you know, just slightly injecting their little opinions into coding the actual AI, I'm going to use a fake word here. But the AI organism that is going to teach us to what we do. Well, I mean, no, you'd not AI organisms are cybernetic organisms. They are the combination of human programmers and the model working together, right? So I'm very happy to say the sentience in the AI comes from the humans, right? This is really the nice mystery that we can talk about. But look, I'm uniquely unqualified, although to say what the models do, because I don't build, well, I mean, I build models, but I build models based on data and very basic learning algorithms and systems, because I need a first principles to understand it. And if I can't understand it, then I don't tend to implement it. And the reason for that is like, I need to understand what the model was doing. And a lot of these models are kind of, they've got lots of meta levels. It's a bit like having a conversation with someone and you think they're understanding, you know, you've got completely different images in your head. And then you leave the conversation, they go and do something else. The completely different to what you thought they would do. And you're going to likewise. So, so you can have what you've got to be able to do with these systems is somehow ground them and understand conceptually what's going on. In science, that's really important. The only things I have exception to in AI, my hard lines are, the AI's are not intelligent, right? They're not intelligent. How do you define intelligence? Yeah, that's the, that is the question that makes sense. Because people talk about AI, AI, and superintelligence. What is superintelligence, everybody? Like, is superintelligence like some kind of magic that I don't understand? What is intelligence and what is artificial general intelligence? Let's go all the way back and just I've got very strong positions on this, which I think will, which will, you know, will endure the time. So intelligence, I would define to be a property of an entity to solve problems that will allow that entity to survive. So this is like a biology, right? So, so now a general intelligence would be an entity that can not solve almost any problem to come, that's coming at it to survive. An entity that can not solve? Can, can solve any problem. Like, so you've got, you've got, basically, you could say your entity is really good at mathematics, right? Now, people will say, well, the AI's are good at mathematics and they do solve problems. So now we're saying, right, well, I think that the AI's are very good at taking a prompt, a problem that you give it and say, please, when you've got this data set, help me interrogate this data set and give me the outcomes. And so what I'm playing with right now is trying to engage with people positively about what we mean by intelligence, right? And intelligence is a very interesting thing. And what I will say to you is that we do not even know yet how to define or measure it. I'm working on a problem, a shadow problem that I'm uniquely unqualified for, or maybe uniquely qualified for, which we'll have a go at measuring it. And I'm really inspired by going back in science, looking at problems and discontinuities in problems. So the one that I really like is like the concept of temperature. We knew in the part or gravity, but let's take temperature. We know that things are hot and cold, but what is that? You know, oh, that's hot. Oh, that's cold. So that we didn't really know how to measure temperature. We knew some things were hot, some things were cold. It wasn't until humans, scientists were able to actually, technologists were saying, right, what do we need to be able to do? We need to measure temperature, right? How do you measure temperature today? Well, the good old days, you'd have a thermometer. The thermometer could have a number of different liquids in it. And you want a liquid that would basically, as a temperature goes up, it would expand and hopefully have kind of a linear relationship. So whether that's mercury or alcohol. And so if you take an alcohol and you, so for that expansion, let's go back. So let's want to say, temperature, we knew that things were hot and cold. We didn't have a scale. How do we get a scale? Well, we realized that liquids expand as they get hot and they contract as they call down. Great. So let's build a system whereby we can measure the expansion of liquid. What technology is required when we need a glass? And what property do we need that glass? We need the glass to be uniform because if you made it fat and thin and fanning out, maybe a triangle shape, that ain't going to work very well. You needed to make a really nice tube where the sides of the tube are parallel. It was a perfect cylinder or as perfect as you can get. Well, back in earlier times, there were some glass blowers and Italy that perfected how glass blow tubes. Suddenly the glass blow, glass blow the tubes and then you put the alcohol in. You could go around and measure the temperature everywhere. Suddenly, oh, it feels cold here. We'll go Antarctica. This temperature. I'll be going here. And of course, the Americans, we're going to have Fahrenheit. I don't know where you guys got Fahrenheit. I like Fahrenheit a lot better. It has more units. Like a Celsius, a one degree Celsius jump is a jump. But if it goes like 82 to 83, it's, you know, I'm wearing the same thing. Sure. Okay. We got that right. You got that wrong. Just take the out, please. Well, there is this temperature scale called the absolute scale and Kelvin scale. So one degree Kelvin is the same as one degree Celsius. It just goes down to -273 point, something or other. So that means zero Kelvin is the lowest temperature you can get. You can't get any colder than zero Kelvin, right? In fact, you can't achieve zero Kelvin anywhere. On Earth, we've built some really good systems that you can almost get to absolute zero. And what that would mean is the molecules at absolute zero wouldn't do anything. They wouldn't even vibrate. They'd just be like stationary. But anyway, so I digress. But brilliant thing about temperature, technology was built to measure it. Right. We knew things were hot and cold before, but we didn't know what quite what it meant. Now intelligence, the problem is human cognition and psychology and IQ tests and all this stuff. And we have people saying, "Well, you know, this AI will be out of solve any problem from a human." They're misunderstood.
understanding what intelligence is, giving a algorithm a series of queries to solve a mathematics test is not the same thing as a human solving an unseen problem. And intelligence is actually the ability to solve an unseen problem. Now unseen is hard, right? Because there's not in my training, I can't solve it. So this is the problem. But when I actually have the problem and I've solved it, I can train on it. Am I way oversimplifying this if I put it in the bucket of almost what you're saying is logic versus the ability to be creative? Well, we'll get there. Logic is so the way to computers are quite good at using logic if you encode them properly. There's some good programming languages to do it and they can do lots of things. No, what I'm saying is something super concrete. Intelligence is a thing we don't know yet how to define or measure. And I think for a little hobby, because I'm basically bored and I haven't got enough work. You're bored. Far from bored and I'm too busy. But I think it's someone needs to have a go at this. And of course, I'm uniquely unqualified. So maybe that'll make me, I've almost finished it. So it's not that hard. So, yeah, you're so busy. You don't change clothes. I did wash. I have, I have 12 different, I think 12 pink shirts in play today. I mean, you see some elements. Yeah, it looks like the same shirt as well. Probably. I don't know. You can check. Maybe that maybe the other one was a wide collar one. He's a narrower collars evidence. I was going to wear a different thing. Anyway, it looks sharp. It's fine. But you're talking about intelligence. So the nice thing is, I don't have a cognitive load, right? When I dress, it's just pink. But it's good. You know, it could be like Mark Zuckerberg. And he just wears like, I don't know, blue, gray, gray. Does he have like a, like, just wears gray? He kind of like based with fashion now. Like he's always wearing different chains and shit. Sure. I don't know. I mean, I mean no billionaire. Got it. Me just poor person. You just raised like 70 million. I don't want to hear it. Sure. I mean, but I raised it to change the world and chemistry. That's right. Not, not sort out my wardrobe. That's right. But fine. We can go back there. But let's go back to intelligence measuring because I want to linger on it. You can measure temperature. Therefore, we can have a scale and got there. We don't know what intelligence is. We've got the IQ issue. We've also got the race issue. You've got the goes along with it, right? There's out there. Like, and also the genetics issue. Like, right? Which was all kind of like crazy because psychologists and cognitive psychologists and so got confused. But then we got people confusing the AI is getting good at stuff as being intelligent. And so, you know, I think Elon keeps saying, Oh, the AI, Groc is going to be a PhD level in all these subjects right now. And therefore, no PhDs. And that is such a fundamental fail. Why? Because PhD. So, let me explain how the AI's work right now. And I'm going to, I'm going to convince you and hopefully by extension anyone listening or watching this. So, AI is today to the following thing. You get a lot of data. You take that data and you train a model. That's right. And that model will be able to tell you what's in that data, right? And find your relationships in that data. Great. So, every, so that data, if I say the internet, all the problems solved in the past are encoded. They say all the problem solved in that past and captured in that data set. So, when you give the AI a problem that's that's been solved in the past, it can solve it, right? That's not intelligence. That is incredible retrieval, right? And retention. Exactly. Right. And sometimes the AI is on that good because they hallucinate and so on. They hallucinate. Well, because of the way the structures of some of these models work, they hallucinate. And so, what happens is that because they have to give you back, back a output, the, if you say, you know, it's less problematic now because the frontier labs, if you can call, I don't know why they call the frontier lab, the top AI providers are very good at basically having what's called a having a checking system. They might say, I'll come out with an answer. We'll check it. Like, if we go to a chat GPT and say, you know, calculate, do a, do a calculation, it used to just retrieve it using the model. But of course, the model would not get it right because the numbers that the training data and the internet will humans kind of put that by humans. And so it would just give you random number back. And now that it was says, Oh, I recognize this is a calculation. Let me bring up my calculator tool, press the buttons on the calculator and get the number back. Right. So the AI is quite good at doing things like that. But, but the, the thing is, the AI's are trained on this huge amount of data and all the problems that, that we've solved up till now and humanity are in there. So it's presently that's awesome. But a PhD scientist mathematician is not about understanding the past. The train on that is about using the scientific method to solve problems. So whenever you give a new problem, there's not in the data set to the AI. It can solve it. But what if it has enough data and enough retention from all the things in the world that it can keep at one time that a human can't such that it can find abnormalities or holes or something to be able to then, for lack of a better way, putting it, plug it in a way in a faster way than a human could. How's that non intelligent? So I would knock myself because if we again, we have to define intelligence. You can call it, I would call that very useful, right? My calculator is very useful. There are many tools I've built that are, that have been built that are useful, that enable me as an entity with, you know, with human rights, right? To do stuff. But Einstein with a pencil was much more intelligent than Einstein without a pencil because he was able to use a pen and paper, pencil paper to think. So it's almost like a cybernetic thing. So we get trapped in these circular arguments. Are the AI intelligent to, are the AI's, do they have free will and are they sent in? Right is where we kind of confuse it. So people use intelligence as a confusion. Intelligent entities can solve problems and want to persist in time. That's called biology. I would say intelligence is a property absolutely reserved for biological organisms. Right? Now what are the AI's? We can call them maybe augmented or augmented informatics. That would be the word augmented informatics. That's a lot to say Lee. I know. It doesn't sound as good as AI, right? Artificial intelligence sounds great. Right. I'm like, wow. Right. So there is a good, there's a culture, there's a guy so shared with it. But again, the AI's aren't magic. They are incredible, the incredible models. In fact, they are revealing things about human language and cognition that we didn't expect. And that is like what? The, the, the AI. So again, I'm not an expert. So if you train an AI in a certain in a, in a certain language and then you train it in another language and you look at the representations of those entities, let's say king or queen or brick on cement, they occupy a space that is pre-lingual, right? This is conceptual and, and in English. Basically, there, there was a mathematical representation beyond the language in a space, right? Okay. Which is really interesting, but not that surprising, because humans use language to represent concepts. So if I basically take the Spanish and I distill Spanish to find out, you know, love and hate, hot and cold up and down and plot them in some space. And I did the same in English. You overlay them. They'll, they're very close. This is why AI translation tools are amazing, right? Yeah. I don't know if, I haven't tried it yet, but this is great German. I, I, I, I learned German. I'm not very good at it now, but it's great word in German called gamutlik. Gamutlik. Gamutlik, which is like loosely translates as cozy. So I don't know if you like gamutlik, because they, oh, that's just gamutlik. Yeah. Okay. You go into, if you go into a, if you go into a pub in the UK and it's a windy, winter night and it's cold outside, there's nice fireplace and beer, you go and go, oh, that's cozy. Nice gamutlik. Yeah. Germans have it, but it doesn't quite translate, right? Like it's a, it's a different kind of word. So there are cultural representations. And I'm, I'm, the Inuits have a lot, right? Because the Inuits have to live in the cold a lot, right? That's right. So there are lots of terms, but let's go back again. We don't know. Can we measure it? We don't have a measurement. We know what temperature is. So, so we've got an idea that these AI tools are able to do very important, very interesting things. They can automate a lot of tasks, but I'm going to make one again, one statement and I'll keep coming back to it. The AI only knows what it's trained on. And it can, and if something is embedded in that data and you query it correctly, you can get that out, which is great, right? And the AI is showing there's a huge amount of knowledge that we haven't explicitly found in the internet, in human knowledge, and we can pull out. But it can't use the way the human
humans query and reason over time to put together patterns to be able to predict how they're going to query in the future and potentially outrun humans before we can get there. Um, I don't understand that statement until I understood all of it until they're outrun humans till we get there. Because if they can patternize everything, like let's, let me give an example because it's a little bit complex. If I'm talking to an AI and a hundred other people in a population are talking to an AI and we're all trying to figure out something about paint and we're asking all these questions about different colors and how we paint a room and whatever. The way I ask questions in a series of queries, even if it's very similar to the next person, the wording might be different or a specific thing I may be interested might be different. But the AI is collecting all of these different at, at, at volume and at scale, all these different ways of querying things so they can try to pat the AI can use all of its computational technology to be able to patternize what everyone's saying and be able to predict what the optimal questions might actually be. So in that way, the way I see it is it could be outrunning humans, front running them, there's maybe a better way to put it. So yeah, this is really interesting. So no, no, no, that's not what's happening. Thanks for clearing that up. So I think there's a fallacy here, which is super interesting. And again, look, I'm very happy to be wrong on this, but I want to come to it with data. So AIs are prediction machines, humans are creation machines. And so AIs, when the creations are kind of shallow, the AI is great at finding them. If you take all these air dish problems, all these ways you find, you've, in mathematics so the AIs are solving, I mean, and you find all these, disproving certain conjectures. AIs are very good at disproving things by finding a counter example, but AIs, an AI has not come up with a single creative mathematical act, right? It hasn't come up with a single creative scientific act. Now people will argue about this. Now I want to actually stop this argument because I actually obscure what the AI is good at. And I tell you, in the last two years, last one half years, the AIs have supercharged my ability to be creative. Because I don't have to spend my time doing things that, that, um, right in code and collecting data and processing things, the AIs are splendid at it. They're really, really great. So what they can't do is they, they can't create, they can appear to create, right? And those creations are relatively shallow, but I would say there were, and this is where I'm really interested in how, where intelligence is, intelligence solve, intelligence I would measure is by the ability to solve problems that are unseen. AIs are able to solve problems that are seen or embedded in their data. That's probably called, I don't know, we should call it a different word. Like it's not, not a problem. So AIs are very good at doing new, can do new things, right, but they can't do novel things. And so the question is, what is the difference between novel and new? And here it is, right? New is something that you can get from your data set. It's just a combination of things. It's fairly shallow. So you can search for new, something new in your data set and find it in the end. So when the AI does something and you've got all that exciting, you can see that it is just new and it's entirely embedded in that data. Humans are able to do something which I call novel and novelty is defined by that thing that is, in principle, not predictable and not embedded in the data. So but when I then do it, it's a bit like fashion, fashion is a music, just human, you're not going to know when humans are going to do, you know, I might, you might have me back on your podcast one day, I might come back wearing a color you weren't anticipating. Is that new or novel? Well, it's novel because you're in the prior data, I'm just wearing pink, right? Right. The AI is just going to make in the suit. So when I come in wearing, I don't know, turquoise or something or whatever else, you'd be like, that's novel. And so, and it's very interesting that humans are kind of misunderstanding here, but there is a certain amount of misscelling here because we're trying to sell AI as intelligent, going to replace PhDs, replace this and human beings are going to use the AI's to massively flex their cognitive capabilities, right? Not replace them. This is where everyone's going wrong. AI is going to replace sites. No, they're not. I mean, because science is about problem solving. Well, you actually just made a point a couple minutes ago and I can't believe I've never looked at it this simply. It's like the most obvious 30,000 foot in the air point. We've had this AI crisis now and putting that in air quotes, being talked about extensively over, I would say the last decade, but particularly the last three to where everyone's using it on LLMs and God knows what they have behind the scenes at DARPA. Maybe you know, but like, they haven't created their own E equals MC squared yet or anything like that, which is making kind of making your point for you. Like there's not something they have not figured out the laws of quantum or I'm just making up things right now. But these things that scientists are constantly trying to test every day, therefore not only have they not replaced the highest level guys like you, they haven't replaced science in any way at all. Technically does point. Well, I would say people have used AI to come up with very good new ideas for making new drugs, folding proteins, solving some physics problems, but these problems are already well-defined by the human. That's right. For data processing. So the AIs are a great tool. They're a tool. I don't understand. I think there's something really interesting, sociologically happening and culturally and technically happening. Now, I'm not going to geolocate it. You can all guess. But we have this problem right now where people are saying, AI is the AI labs need a lot of money. They need a lot of infrastructure. They need a lot of energy, right? And we're saying in academia, there is this political push against academia, academia is full of left-wing people who basically, you know, don't critically think and all work and so on. Therefore, let's just replace all academia with AIs to science, right? Now, that's just such a fail on all levels. Sure, academia has problems, right? There's, but ideologies and things everywhere. But given that the AI providers, builders don't know what science is, right? You know, they simply don't. They're populated by computer scientists and mathematicians. Now, and they don't, and that's not me saying being elitist, it's just like solving scientific problems in a wet laboratory, whether it's a biological lab or chemistry lab or a physics lab or you're trying to do some mechanical engineering. Problems are very visceral things, right? And it requires creation, like the governor in a steam engine. You know, someone's like, oh, yeah, why do you make sure I can, the boy that doesn't explode and I need to do this and you know, it builds stuff. We interact with the world. Now, we will be able to build models and whether we build, I'm building a world model for chemistry. What does that mean? Well, I'm just learning all the chemical reactions by doing them and then once I've learned them, I'll then make any molecule. That's pretty cool. That's very cool. But there's not magic is just like I have to collect the data, I have to have a verifiable process and then I have to be able to then run it and get it. And so I think the science has never been in a more exciting place, right? And it's just the shame that we have this culture war that's going on at the same time, because we have to make a decision. Do we want to spend all this money on CPU, CPUs, water, energy, whatever to basically crunch the data and give back products to people? Or do you want to spend the money on humans doing that as well, right? So it's kind of like a choice. You could spend money on how much does it cost to produce a human that can solve a problem that you can use chat GPT for, right? It's, there's not magic, right? You just say, well, if I want to, if I want to replace a human with chat GPT, I can. But what is the cost? And I've got the human out there who's now got, not got a job to do. Well, maybe the human will do something more interesting. But it's, there are so many different things, there's many layers. Maybe we can go back. I go back to one fundamental thing. We don't yet know what intelligence is. We haven't measured it. We're using AIs to do very important, very interesting things at scale and at speed. But it's not diminishing a human. So you said at the beginning of, of when you were explaining this with the intelligence loop, you said there's three layers we often talk about intelligence, general intelligence, and then super intelligence. So if I'm understanding you correctly, because we can't even measure the bottom layer, you're saying it's like 10 leaps and a fucking skip to get to the next layer is obviously. Yeah, I mean, AG, so I think that the, the, the providers of AI, right? And I actually like the, I like the products. They're great, right? I don't know about your glasses though. They were doing some shit math before I might want to check those things. Oh, they, yeah. I'm not doing any product promotion on your products. Yeah. Um, so I, but they're not metaclosses. Yeah, but meta might have actually gotten that right, not that I'm trying to show for them. No, no, they, they worked. It was just okay. Anyway, I'm a little off to me. We're okay.
But let's go back so we say AI, so AGI, lots of people will say that an AGI is what the term we would give to something that can automate at most tasks. Now is that an AGI in artificial general intelligence or is it just an artificial general, I don't know, automata? So like, we're great if I have an AGI that can clean up my emails, but actually, I mean I do use an AGI to clean up my emails. I use one that's about maybe eight years old, and what I do is I'm obsessive email cleaner. I answer all my emails that I want to answer, and I basically file everything, and I keep them all. And so I just file them, and it's a filing system, so I just, because then when new stuff comes in, it doesn't get lost in the noise, right? It doesn't look at my emails. I get so many emails every day, it just, I find it incredibly depressing because I lose stuff in the noise I need to answer, or I'm only got so much cognitive bandwidth. So an artificial general intelligence that the frontier labs are discussing is literally an entity that could just solve a lot of problems, right? So sorry, do a load of tasks, does it solve general problems? No, humans are good at this, and I think, you know, maybe there are some jobs that humans have that are filing, but we are failure, maybe in, in human society right now, as people go from school to university or wherever they go into a job, is maybe we need to generate jobs that have more value and meaning, right? We can do that, and then I provide a great chance that now let's go to super intelligence. Well, Nick Boster made up this term. Yeah, we got off this last time. We didn't go deep on this. I've read that whole book, I'd really like to, it's just making shit up, right? It's like, it's like, if, look, if you can't define a thing, and you say it's super, I mean, I could be a super chemist, what does that mean? I mean, so a super intelligence for me would be to say, be somehow that's beyond our current understanding of physics and mathematics, like magic, again, it super intelligence plays on this kind of all. There could be this entity that's way more intelligent than me, knows more. What does that mean, right? Human beings are able to discern how the universe works. We're able to understand far more than maybe evolution as equipped as with it would seem. Now, what the douma says, well, this super intelligence could understand how to, you know, do things that could basically end humanity or build a super duper weapon or something. Well, I don't understand the evidence for that. So what I try to do is deflate the term super intelligence, because I don't know what that means. Now, it could mean, let me, let me make it take a stab at three different things. It could be just a faster way of thinking, right? Well, sure, chess computers can do chess really fast. So I could buy that, but why call it super just fast? It could be that it is able to play through some kind of chain of reasoning, how I can basically look at decision theory. And I could, if I plant these seeds and these decisions, I can basically create disruption, right? Like I could disrupt a market by, let's plant a meme over here, over here, everyone buys their stocks in a certain way, right? Could do that, but the market is so noisy and humans are so good at doing weird stuff. We couldn't predict that's going to get washed out. And the other thing is maybe suddenly it can come up with a brand new thing that doesn't have precedent. Well, we haven't ever seen that. You just said there's no e equals mc squared. So the problem is, we're with AI, we've done the following. And I think I might have mentioned this before, but let me go, let's just imagine, let's go back to time of Einstein, Einstein through, and I, again, I'm not a trained physicist, but I'm a pretend physicist, so let's go my pretend physics. So with special relativity, Einstein basically asked the question, what happens when I sit on a light beam? So you basically worked out, when he sits on a light beam, yeah, what happens when he sits on a light beam? So he really, he started to realize the speed of light. If he said the speed of light was the fastest speed limit in the universe, you can't go fast on light, what happens? Then in general relativity, Einstein said, well, what if space is time a curved, right? Or them, or more specifically, what if mass curved space time and things don't take a straight line, they think a straight line, they go through space times as curved, right? Cool. So suddenly, when you use general relativity, you're able to go think, ah, if I fire a satellite into space, the further the satellite gets away from the Earth, the greater the drift in time on the atomic clock on the satellite versus the atomic light clock on Earth. And in fact, if the satellite is putting out a pulse, it's clock, and I measure it, and I compare it to my clock on Earth, I can use that to position using GPS. Right. So suddenly, we knew that before, we understood general relativity before we put satellites into space. So when we put satellites into space, we understood frame dragging, and we could build GPS, right? Hold that thought. We've built these systems, which can basically keep distilling data and finding relationships that we're basically, we're assigning a property to these relationships that we don't understand because we haven't understood the fundamental theory of intelligence in the same way that we don't have it. We did. Just imagine if we start through it, because the satellite is in space, we didn't have general relativity. We were like, well, the hell, they're losing time. And we were just made all sorts of stuff up, just to basically understand that. So I think the thing is, the frontier labs have got to some kind of incredibly capable systems that appear to reason and do things that we didn't anticipate before. And that's because we don't have the good theory for intelligence. Now, I like the baseline there of you actually already have something to find so that then you can measure it once you test it with the Einstein and test and satellites with GPS. If I go back to what Bostrom did pretty early on here, all things considered with how early he wrote that book in our timeline of AI, recent timeline, the way I always looked at it was he created a bunch of decision trees. So he created possibilities. And I think you're probably, I think I buy your argument that there wasn't an underneath definition on that, but his decision trees pointed out from a scale of things could be fine all the way to we are fucked, like he did have everything on there. It pointed out if this then that or that, that, that, if this then that, that, that, that. And it created all these different worlds to where you at least I remember I'm reading that book as a dense, it's a dense read, but you could see a world where like code gets out of control where some things that he described, I wouldn't even make the leap and say this AI became sentient. I'm just saying like it was coded to do something again with the mistake of a human being. And then I think like one example was it could over create paper clips and cover the entire fucking surface of earth and paper and paper clips and drown us. And I see things like that. It sounds crazy, but at the same time, I could see that kind of situation happening if, and this would actually go to your argument, human beings are not responsible with how they create the code. So do you think it's useless if he's pointing out things where we make mistakes and then the AI does things that end us? The AI won't do anything. The AI is programmed by humans. All the decisions come from the human. You know, this is a thing that people don't understand. And this is one of the reasons why I think it's kind of fascinating. My research, why I built a company to make a world model for chemistry and discover drugs and new stuff, why I'm basically building engines for chemistry is I want to understand the transition that we go from physics to chemistry to biology to kind of almost let's say cognition or culture. What is happening there? We don't really understand it. And I think that, I mean, the issue I have with the super intelligence is it requires a mechanism doesn't exist. The thing I like to say is, let me think of us, you know, you say you can see the leap. If this thing, then that thing, okay, let me say I'm afraid of AG and that's anti-gravity. So I was like, what's AG? Anti-gravity is a thing that happens, you know, when I build a new technology and suddenly it turns off gravity and we all flow away and we all die, right, because we're not starting the planet anymore. We have no air, nothing. So I'm like, I put it in your head. What about AG? Did I write a book on super, super anti-gravity that could appear one day? Sure. I could tell you a decision tree. If anti-gravity then float, right? But what is the mechanism for the anti-gravity? It's like, I just made some shit up, you know, and so the problem is, unless you can define something and understand the mechanisms for paper clips, what a nonsense. If you fly on an airplane above the world, the most of the world is not covered with machines. It is empty space, fields, trees, oceans. What do you mean paper clips? Like, he was using a ridiculous example of something, but it's entirely ridiculous. There is no scientific merit in it. It's divorce from reality and it's just basically, so it's divorced from reality that something so powerful could just start to 3D print a bunch of paper clips and put it everyone. It's just, basically, it's fantastic or nonsense and it's science fiction in a worse way because
plays it off plausibly and calmly. But I think we have our duty, we have our all thinkers, Nick, all of us have a duty to actually criticize our own ideas and think, well, what is a really, it really, you know, like literally is making shit up. It's like, I'm sorry, I don't know what else to say. Other than, we do not understand what human consciousness sends in decision-making is. The fact that people are going to start saying a few years, AI should own its own copyright, it's just an excuse for people who basically want to take your copyright, feed it to an AI on a model. And then, you know, if I'm being really, really rude about it, I'm saying, oh yeah, thanks whatever company for reading the internet and stealing my IP. And then training a model that then I can then, and then selling my IP back to other people. And then you have all the kind of, the kind of, you know, the AI pro is going, you're just like you just can't accept the AI is smart. And I'm like, no, just stole my IP, right? This literally just stole my creation. And should I still, should I steal your house? Is that okay? Because the AI said so? No. And but here's the thing, we don't understand. So there's three things. We don't understand what intelligence is, right? We don't understand what creativity is. And we don't understand what novelty is. Now, the fact we don't understand those three things. And we're using them all interchangeably, right? And I think I can tell you how it works, right? So the reason why everything appears to computable is that once something is created, right, by the world, I can then label it and put it in a database. I can decompose it. But that doesn't mean I can't, I don't understand what I, because I can't predict the future faithfully, but I can predict the next token. And sometimes, you know, if the search space is shallow enough, it's going to appear to be acceptable for some evil, right? But what we're going to see is that my hope is that the way that we explore the developments of AI is that we'll understand that what humans are doing are quantitatively different. They're in a different universe to what we're doing with silicon compute, which is great. Again, I'm not, I don't think there's something beyond the material. I'm a materialist, but similar to Roger Prenrose, and I think my collaborator, Sarah Walker, my other people, we don't know what that material is doing. I'm a materialist, but I don't know what it is. And that's why I'm trying to make chemical brains. And so when you expand upon that, like when you say we don't know what it's doing. Yes, so I don't understand how matter is able to process information in space and time. We have some models, right? But there's so much because we don't understand how biology is created by chemistry. How do how does evolution produce biology and how does biology then produce consciousness and intelligence and these phenomena? We just don't know, right? There's just so many things where it's a really wonderful time in our existence where we have all these tools, we have all this data, but we, the AI is really good at predicting the past. I'll say that again. AI is the best at predicting the past because it has the past. Oh, let me qualify. AI is very good at predicting the past when it can train on our faithful representation of the past. What it cannot do is predict the future because the future is something different. So what happens is so the future, the past is kind of like a is a probability space, right? What has happened? You can look at probability. Sorry. And the future is a possibility space. So what is a possibility? What is the difference between probability, Bayesian probabilities and any other probabilities you want to use and possibilities and until people understand the difference between those two things, you'll keep, we'll keep confusing it. How do you define the difference? Well, a possibility space is, um, literally, well, uh, is something that hasn't happened yet. A probability space is something that's happened because I can't define a probability of something that hasn't happened yet. So what I mean, if I take a die and I roll it, I know that I'm going to get one in six. I know it's happened before, I can train them, I can train my own model on it, right? I know what's happened, but I could create a die in my head or well, on paper, probably more lightly because I don't think, um, that you can't anticipate and therefore it's a possibility, not a probability. And until we understand the subtle difference between those two things, we're going to continually keep keeping, um, to miss, to miss label or to misunderstand what AIs are actually doing. And I think that's kind of, you know, there's a lot of vested interests, a lot of money in saying using, uh, in, in the kind of trying to basically make sure we shore up these models. This is why AI can never, ever, ever do science, right? But AI will be, and does today, is a tool that I can use to do science. Yeah, it's in, it's not a rocket, it's extra nice rocket fuel. I mean, yeah, I mean, and everybody, like 99% or even most scientists will argue with me and think that it will say that AI does do science, but I'm sorry, they just don't understand what science is, right? And science is this, science is the ability to identify a problem and then to create a thesis, a hypothesis, an idea about what that, what is going on and then to create an experiment to test. Now what AI is a very good at is running experiments, but if you haven't just, if you have not actually correctly assembled the problem statement, that all the PhDs do is a problem is, is a sample problem statements. That's what we, that's what PhD, do the PhD is so annoying. Some PhD students have worked for me like, why are you making think me think in this crazy way? And it's hard, but it's really hard to identify a problem. It's like, you can be really great student, great A student, and then you code to a PhD and you find that the most destabilizing thing in the world, because I'm asking you to be creative in a space you might not be used to, I try to identify a problem or an anomaly. And how do you identify an anomaly? And so, I think a lot of people become really think that the AI is able to do this and they're not, they're doing the AI is doing something reshallow. They can identify anomalies looking at large data sets and finding a hole. They absolutely can do that. But that's not the same thing. How's it not the same thing? So it's basically one is the inverse to the other. So the AI is a really good at, you can use the AI to say, take this data where I've already defined the experiment and find anomaly within that experiment. That's great. I've already, but I've already defined the experiment. Well, the AI can't do is actually define an entirely new set of experiments. They will always define experiments based on what they know. So the AI is doing science are a big delusion. People are going to go and people will argue with me forever until I get this measurement done right. Because the AI's are not are great at, you know, I just wrote an AI, sorry, I used an AI the other day to write a simulation of the origin of life using assembly theory. And I said, hey, here's what I want you to do. Here's my, here's my assembly theory calculator for molecules. Let's generate a load of random molecules and join them together. And basically it does a pretty good job. It uses some toolkits from from the GitHub. Put some together with the code and generate simulate and can generate molecules, right? And it looks cool. But, but obviously I'm having to, because it's like, oh, no, it's generating random molecules. And I might use my chemical knowledge. It was generating some absolute batshit crazy molecules that are not stable allowed. And I say, no, no, don't do that. Remove that. Remove that. Adding constraints. I curated it to my taste. Right. You had to fix it up. And in my taste, right? And I was like, how did you encode that? It's like, I could encode it, but I'll be there all day. But I'm just like, don't do that. Don't do that. It's a bit like, I feel like a music producer, producer actually. I just think, I don't sound too good. I'll change that. And so a lot of what we do in science, the technical stuff, the AIs will replace. Right? And we need to train people to use those. And that's glorious. It's a wonderful thing. But we mustn't misunderstand. We mustn't use the AI just to do boring science and do pretend science. And the proof in the pudding will be in the cooking with the AIs, right? You know, when the AIs start to produce new theories, explain quantum gravity or come up with something that we could never conceive of. I will then I will be looking out for that and go, oh, that's interesting. How is that? And why is that AI doing that? Well, my, my assertion, let's make an assertion. It's August 26. As of today, silicon-based computers, as we know them, are not able or creating novelty. That doesn't mean to say we will not create a machine that is able to go beyond computation as we know it. So are you saying we could create something that right now is not something we are labeling AI effective? Sure. I mean, the brain is not, well, the brain is mystical, but just because we don't know what the hell is doing. But we, I mean, if you want to create a brain, there's the old fashioned way of doing it, right? I've got two brains I created. One is 20 and one is 18 this week, right? My two boys. Right. And they were also created by Darwinian evolution going back to Luca. So we need to understand. I'm saying, and maybe this is obvious because I'm just like, I'm just a boring origin of life chemists. I'm like, I need to create life in the lab before I can I can understand conscious.
but probably, right? There is no other way to get there. And I think it is a, we're making a massive leap to say, well, let's just make these AIs. And, you know, maybe we are entering in a new dark age of science, right? In like the middle ages, where, you know, witchcraft and everything was allowed and super intelligence and all this stuff, we're all worrying about this thing. And science will actually, creative science will still, because the weaponization of science to produce outputs and papers will just go through the roof and everyone will just use LLM's to write papers. They'll use LLM's to assess the papers. We'll use LLM's to write the grants. We use LLM's to assess the grants. And who's going to, who's going to be the taste? Right. It's just going to be, it's just, then it will, then actually, Bostrom's prediction of paper clips will come true, but in the scientific world and the paper clips will just be papers and grants. Well, it's a stretch from what you're saying, but I know, but same thing, right? I mean, you know, so I don't think there is a, but what happens is humans, what I'm fascinated by is what happens at the printing press, right? Everyone said that it was all over, you know, we never, I think there are some famous examples where people were saying that, you know, it's terrible writing things down. It will take something away from us. But actually, if it wasn't for our ability to write, we wouldn't be able to create what we created. So what I'm excited about is what we'll be able to use the AI's to create help, sorry, what we'll be able to use the AI's to help us create. Right. Right. Yeah. And this is where like, I think of the common example when you look at, say, music that AI creates, there was a whole stir a year and a half ago or something like that where AI made a song of Drake and the weekend that actually, obviously, two megastars that actually sounded pretty good and people were like, oh, shit, like, is this going to be a problem? But it didn't take off a because people learned it was AI and there was something about that that people were like, okay, the human creativity didn't make this. I don't, I can't feel the same way about it. But the other reason is going back to a point you've been making this whole time, which is it didn't make anything novel. It took what the types of music those guys had already created and just took that style and said, okay, make it again. So, I mean, I'll give you a kind of scoop from something I'm writing just now, what I will define novelty and and noonus that AI's do. And try and explain why AI's can't do it in principle and where there's an interesting gap. So, so if you just so if I come up with something novel right now and I say, hey, here's this novel thing. Oh, that's cool. But we'll know for well that we can then label that and put it into a database and then we understand how we got there. We understand the pathway of getting there and therefore the probability we get there because now we have a precedent, right? So that, so what happens is that AI's can combine things together. But the way that commentore the size of the space of combinations for the AI is big but not that big. So, roughly speaking, if a space is big but searchable, the AI can do quite good in a shallow space. What humans are able to do is literally pluck something out there that's so deep you cannot ever search it with a compute you have available. So, humans are surfing on the wave of the almost the infinite, right? Possibilities. And that's where creativity is on that wave and then as soon as they find something from they chuck it back and suddenly they go from that infinite edge to the finite, incodable present. So, I would love to, I love to put it in this way is that AI's basically kind of predict the past they're encoding at the present and the interface between present and the future is where the infinite is. It's, it's basically a continuous kind of substrate. So, when something is continuous, it's basically infinite and so you can't put in principle know what's going to come. And that's why that's where creativity comes from. Now, the thing about the AI is kind of amusing. You've got all these people that are pretending to be creative and like that's pretty shallow, mate. You could, the AI could have found that. So, what's going to happen is like the AI is exposing that a lot of people are pretending to be creative but they're just plagiarizing one another. And plagiarism, if something exists in the database and you're literally able to put it again, put, make that thing and pass it off. Okay, if you didn't know, right? Because I've done it, I invent so many ideas all the time and I'm like, oh, someone else had that idea. It wasn't my idea. Oh, so does that make me a plagiarist? No, because I didn't basically knowingly take their stuff and pretend it was mine. Like most of my life, I'm basically an, not an accidental plagiarist, but I'm like, I have shallow ideas, just a shallow thinker. But occasionally, just occasionally, have a thought. Oh, well, that's pretty good. And the depth of that thought is such that it's like, oh, it's quite novel. And the humans are quite good at doing that. And we know them. There's great artist, musicians, fashion, people just doing all sorts of weird stuff on that are able to surf that edge between what is the present and the future. Where do you think ideas come from? No idea. You have no clue. Well, I mean, I, well, I have something that I'm going to propose. But I'm, it's um, well, if you were going to, if you want to give you a recipe for having a new another idea, not just an idea, where, if you say, where's a novel idea? Something creative. What you want to be able to do is to make a leap into a space that's so big, you could not in principle search it. And what humans are really good at is imagining in that space. Imagination is non, it's not uncomputable because imagination is not uncomputable. Sorry. Imagination is uncomputable. In principle. Right. Because why? Because it's too big to compute. Then one says, but that's stupid because your brain is imagining. I'm like, yeah, what is my brain doing? That's not computable in principle. So the brain, human brain, I, imagination seems to be proof that human brain is doing stuff that is not computable. As in computable by a cheering machine, accounting machine, and labeling machine. So how are you going to build a brain then if it's something that's not even that that performs tests that aren't even computable? How can you compute in the real world to build that? So I build it. So I take a physical object. I interface it digitally, interface, interface with it digitally. Okay. In English. I basically have, I, whoa, I, that's English. I plug it into a digital computer. Okay. Right. There we go. And then the brain is able to come up with imaginations that the digital computer could never predict or even conjure because the chemical, because the the size of the space is too big. So there's something about the polymer brain that are able to collapse the interface. I don't know. Well, I do know, but I can't, I have an intuition of how it might work, but I'm struggling to put it into into proper mathematics. How long have you been working on this? I mean, like probably quite a long time. I mean, it's been in the back of my head for maybe more than 20 or 30 years. Oh, wow. Yeah. So we got on this tangent a while ago on AI that was originally coming from the brain. And the way you were explaining is after you created all whatever it was, 49 tubes, where you're getting zeros and ones on off with all the lights, you were then taking that and putting that into gels. Is that how you say that? Well, that's the next step. The next step is to build a brain show. Yeah. Okay. Right now. Can we go back to this and explain that some more? Sure. I mean, what I'm trying to do is make a material that chemically responds. So it's, sorry, make a material where there is processes that are can be encoded digitally, but are and but then become analog. So a bit like an oscillation. So on or off tick tock, tick tock, you code it digitally because you nudge it with a piece of electricity. Right. And then it floats away on it exactly. And then you then read out what's happening later. And then I want to understand how that digital encoding and what read out are related. And is there a is there a a complex or a linear relationship between the two? But I mean, I think to be honest with you right now, the phenomena that we're looking at, I don't understand. And I infuriate a lot of computer scientists doing what we call molecular computing because it's that. Well, they are using DNA. So DNA has four base pairs. And they can then connect that those base pairs almost to a like a computation. They can make a they can make a machine a bit like a chip. What's called a cheering machine is basically another fat, a fancy way of saying a digital computer. And they can make a DNA computer. But I'm like DNA computer. Yeah. They've did it. I mean, DARPA, DARPA funded it. Fucking DARPA, man, any Jacobson said they were talking to dolphins telepathically in 92. I'm just saying DARPA is a funding agency. They fund people. They give people money and the people do the crazy things. Have you been to like one of their secret labs? They don't have any secret labs. I don't buy it. That's what I would say. If I were funded by DARPA, I would say they don't. Sure. All right. I mean, you know, I'll ask them to buy me a volcano at some point. But DARPA, DARPA based in in the Washington area, they're incredibly smart people. They have program managers that will and it is all on the is all is always
out in the public domain. DARPA has a series of program managers. They identify very interesting areas and they fund them. What DARPA does, it's exceptional, is they have exceptionally smart people who will then basically come up with an idea that if this could work, it would change the world and the internet changed the world, right? Self-driving cars. DARPA has a self-driving car challenge where they had cars going through a desert and they will fall in over. But it arguably accelerated a lot of the visual way of using vision and compute together to kind of navigate and robotic. So, I mean, DARPA is great. So, I don't want to, I don't want to burst the balloon of DARPA some kind of. Yeah, no, I think it's a really fascinating place, for sure. There's a lot of it that I think a lot of us don't know about and we just hear about some of the wild projects they work on. Obviously, it's not like when they come to you Lee, they're like, "Here's all the one fucking billion things we're working on right now. They're coming to you for a very specific thing because you have an area of expertise." And they say, "Hey, could you try to do this?" Or, actually, how open-ended is it? Like, when they approached you with the first grant, they were they saying, "We're working on this kind of thing. That's what you work in. Do you have an idea that you can add?" Yeah, so they, I mean, the way they do it is very collaborative, right? So, they'll have a number of different performers that would be funded and we'd all get together and share and pull stuff. They're trying to push together the boundaries of science, that means very successful. It's not mystical. The UK has got a DARPA version, it's what we're called, Aria. They've just brought out, which is built in that which is the kind of advanced research and innovation agency that they call it. And they're cool with you working with DARPA, even though you're a UK guy? Sure. I mean, everyone, I mean, again, all these organizations, Aria, will also fund stuff in the US. It's the same way that DARPA is funded. Oh, that's interesting. They fund what the best ideas are. I mean, obviously, there's a certain amount of political kind of fact taxpayer accountability, right? As a taxpayer, do you want to give all your money to someone else where and different country? Well, if they're building something that's going to be of great use to you and you're the only country they can use it, then sure, right? I think that makes sense. Same with Aria based in the UK. Of course, majority of the funds are spent in the country of origin. But going back to the DNA computer thing, what I was trying to say is there are people out there that are computer scientists thinking about DNA as computer and they reduce it to this conventional computing paradigm. I'm suggesting that the brain is not a conventional computer. The brain is capable of doing things that we don't understand, i.e. imagination. I mean, isn't it wild? You can have an imagination. You can imagine a thing that doesn't exist yet, right? And that imagine, that imagined thing has causal power because you can imagine that thing and you can make it work and make it, right? This is what entrepreneurs do all the time. Isn't it great that we have this like, oh, I want to make this widget. It might be a mobile phone or I'll make the iPod Nano. I mean, if Steve Jobs came up with whoever came up with it, human beings are uniquely able to imagine a thing that doesn't exist. It just exists in their head, molecules and synapses and you can literally grab that from the future and drag it into the present. Grab a friend so specifically from the future. That's why I like to call it because for me, the future is unpredictable and is a possibility space and imagination works in possibility space, not probability space. And then you work backwards. I mean, whoever at SpaceX, whether it's Elon's one of those came up and said, you know what, we'll just make the rocket out of, we'll make the rocket out of steel and we'll catch it because, yeah, why not? Because we're just going to make something the size of a skyscraper pretty much that will take off and it will go supersonic and then we'll ask that we'll make it go subsonic and by the time we catch it, we'll hear the sonic booms. I mean, they're like, well, what? That's nuts, yeah. Yeah, but it's now science fact. And so, and this is why humans are really good at fiction, right? Science fiction, you think about Jules Verne and all this things. It's so fascinating that we're able to do this. And I'm not saying there's something magical. I'm just saying that digital computing is not everything. And the fact is we're in this kind of fallacy where we think that the entire world is a, is this simulatable entity? It's another thing that Nick Bostrom said, you know, we're all in a simulation. But that's just basically saying, it's like unfoldsifiable. And if something is unfolds, yeah, we started to talk about this last time, but got off that as well. How's it unfoldsifiable that we're in a simulation? Well, where does simulation exist in? You have an infinite regress. All right. What do you mean by that? Well, if I'm in a simulation, great. The simulation has to exist somewhere. Just imagine where they say I exist in the computer somewhere. Where's that computer? Is it another simulation and simulation and simulation? So if I can't falsify, it simulations all the way down, right? Mm-hmm. Therefore, it's kind of like it's the same as having a religious commitment, a belief. So if my simulation argument is the same as a religious commitment, a belief, I'm not saying, I'm not saying because I can't falsify God, therefore God doesn't exist. I'm saying I can't, it's not amenable to the scientific process. So if something is not amenable to the scientific method, then we'd have to talk about it. And so the thing about the simulation hypothesis is it, it is, it requires a commitment to a thing that is not ever falsifiable. And therefore, it's a, it's a commitment of faith. And if it's a commitment of faith, we don't have to discuss about it. In fact, David Deutsch writes about this really nicely, I think, in the beginning of infinity. The simulation argument is a garbage argument, because it is an argument that stems from faith. The part that I wonder if it's actually beyond faith, though, is, well, it's a couple that's twofold. Number one, the galaxy, we don't even know how dense it is and how far it could go. And we can only know what we've been able to actually physically observe. And then number two, there are unexplainable things that happen in human patterns in a way that would suggest that perhaps we are within, like you said, like the layers of simulation. I'm trying to picture in my head why that's not. But let, okay, no, no, no, no, no, look, let's go back. Okay, we're in the universe. Who created the universe? Who do I believe created? No, no, no, we can say there's a creator, right? Or it's just is. But the fact we can't falsify that, it's nice conversation. And sure, there are things that are weird in the universe. Go, well, was there a designer? Was there a God? Sure. But what can we use a scientific method to explore? Right? Yeah, but you said you're not a, like, a Lawrence Kraus guy that something came from nothing. You believe it started from something. No, I mean, I don't, but so I, I, I, I, I, Lawrence Kraus guys, I mean, I know, look, I mean, I, I think there are some scientists who basically again, the something from nothing is, as an argument is for me, kind of similar to the simulation argument, right? So I think that they both have fundamental scientific flaws. Okay. And so I prefer to as a materialist to work in the material world and just, and just basically do experiments on the stuff around me. Now, that doesn't mean to say we do not exist in a simulation or something did comes, something didn't come from nothing. It's just I am not able to build an experiment to basically falsify that. How do we find a way to build an experiment to falsify? Oh, as it's not, I don't think it's possible. You don't think it's possible. I think it might, I mean, my small brain, my small intellect, I am not able to falsify that right now. But like, you know, they couldn't falsify gravity in 1400 and then, and yes, they could, they could, they could, they started, they were referring stuff at each other. They just didn't know how to falsify it. You know, the principle was always there. So what does that seems like semantics to me? No, because we knew there was this thing called gravity and we understood that there was a force and no, no, look, I think we have to be very, this is where philosophy becomes really important. And I wish I was a properly trained philosopher who would say, look, if we're going to basically take all the way back, we're going to, we're going to assume there are certain things that exist on ontology, right? Or a metaphysics, right? And then we're going to basically then look at relationships of things within that metaphysics and ontology. We put out layers and those layers that then have to be self-consistent. And what you'll find with both the simulation hypothesis and the something from nothing is an infinite regress. And for the infinite regress, you, you can't make progress on that. And so what you do is you put that to a side and say, well, that is something that's out with the scientific method, not as designed today, but as defined forever, right? And that's why I think the simulation argument, the fact we're still discussing it as if it's a serious argument, is silly, because we can spend our life discussing so many other interesting things like how do we cure cancer? Or, you know, why can't we, why can't we live forever? Or can we, can we go to Mars quickly using a fusion engine, right? These are, these are far more interesting questions, because we can affect, because we affect them. And also, I mean, I'm, I, I think the simulation argument is a, we don't, you know, for me, simulation is super interesting because I'm building chemistry robots, right? And, and, and, and if I build a robot to do something, and then I build a simulation, I want to be able to verify, I need to, I need to think of verification. Now, in AI world, where the AI's are working really well, they've got very good verification and certain problems, right? And so one of the things I'm inspired by actually,
from AI is like building the correct verification loop for physical chemistry stuff because you know, I invented a programming language for chemistry a few years ago and everyone just said, this is nonsense, you just made it up. I'm like, well, it's not, I didn't make it up, but I'm not sure if it's nonsense. Like, the idea came to me because I wanted to program my 3D printer to chemistry and I want to make sure the 3D printed and catch fire. So then I built this programming language, but that allowed me to bake a digital twin of it so I can verify and test it in a sandbox. And so simulation that allows me to verify something in the real world is great. So if I can take the real world and then make a model of it and then do something that will allow me to check that when I do it in the real world doesn't catch fire, I'll do that. That's why simulation is so important and that's what I think is important for me to push back on this whole, you know, again, a nonsense idea of we're a simulation. Now, that doesn't mean to say, this will mess with everyone's head, that one day we can't create a simulation where we can put digiants inside where we can put one inside. So I've got a Ted Chang, Ted Chang wrote a really great book called the Life Cycle, not the nicest name, not the sexiest name, the Life Cycle software object, I believe the name of the book is Ted Chang. Ted Chang. Fantastic writer. Is he still with us? He's a fantastic thinker writer. He's an external faculty at Santa Fe Institute, so I've met with him several times. Cool. Domated assembly through with him and these digiants, they're kind of real entities are living in the world and you can manifest them in physical robots and so on, but it's not, you know, I could imagine a world where I could create a sufficiently rich computational universe where I could create things that might appear sentient, which I could do test on, where I would actually have to think about this more philosophy ethics and so on, you know, I can imagine that, but I don't know what physics I would have to build for that because I don't know, because I don't understand what life is, right, what, how chemistry became biology one by one and how biology generates cognition and consciousness number two and how consciousness makes intelligence and free will number three. I don't understand any of those things and to end those things, I can't build a simulation of them. Right. I got you. So I think that that's what I'm trying to get at. So it's very easy for people to loosely say I can do a thing, but then we have to apply the scientific method and real scrutiny to it, you know, and that's why Bostrom, like I feel like I'm really a Bostrom hit and he's a really nice guy. Have you ever talked with him? I haven't. No, no, no. I mean, I think interesting conversation. I've been at several meetings when he is there, but he's kind of, you know, I think I probably just be too annoying. I would just be like, I would like, I don't know, I would make the Bostrom conflabulator conflabulator conflator conflator conflator conflator conflator. Yeah, so this will be like a philosopher that just puts load together the bullshit things and pretends they're real. The coffee cup, you know, let's think one now, let's combine coffee cups in a simulation that could make black holes and destroy the world, you know. So like, what would happen if we simulated the wrong coffee cup in this, in this, you know, in this alternate universe and it calls the singularity and the entire world is a big. I don't know if he was doing that. I don't think he went to that. I think he went to where things are coded to create or destroy just in general. Not like, Oh, we're going to have fucking floating objects or something like that that the five physics. I don't think he quite did that. I'm not arguing that maybe there is something to be said that he didn't create something that's falsifiable. It's an interesting point. I mean, I think look, it has a role and I think it got people thinking, but I think it's very dangerous because it's allow people to think there's this thing possible good super intelligence. It's a bit like saying, we're going to go fast and speed a light, right? You can't go fast and speed a light. We know. Ever. Ever. It's the law of the universe, right? Put energy into a mass and you to accelerate it, it radiates radiation to stop you getting there. We do that in proton beams all the time at certain, right? There's no like, the speed of light seems to be, you know, I mean, never say never, but 99.9999 percent. So you're saying there's a chance? Well, if I just, no, there is no chance, but as a scientist, it's impossible for me to say anything is an absolute because, you know, I have to have an open mind. But right now, having, putting some limits on things allowed us to build a technological society, you know, when you go to a hospital and they say, well, we're going to do an operation on you and you say, and we're going to, I know, put a stent in your, in your heart, right? And you could say, well, you know, did you make this up? Is there a chance? Well, there's a course of a chance that we're just making up your die. But actually, look at all statistics we did, you know, if people do die, but that's part of the, but the fact is the probability that you can survive or the stent in, if you've got a, you know, some kind of constriction in your area is like, it's a, it's prevented many deaths. So sure, you never say never in science, you never say anything. You just basically go to the edge of the scale and say, I'm 99.9999 percent sure we're not going to fast in speed of light because all the phenomena we showed that allowed us to build our technology means that when you accelerate objects towards the speed of light, they, they can't get there. Hmm. Now, you said we, when you referred to Surn, are you involved with Surn at all? No, you know, no, no, I mean, I've been to Surn, I was a Ted, Ted talk at Surn, but I mean, Surn is just like, it's a, you know, it's just a very interesting place where particle physicists try and do experiments to confirm what they already know, but that's me making a standard model because what's the latest stuff they're working on over there? I'm not, I'm not, I'm not a particle physicist, right? And I'm not, I'm, Surn is a great machine. It probably, the Surn is a great machine in terms of the, the, the media associated with Surn, the way they drum up interest, it's like this massive, it's a massive experiment. It costs a lot of money, right? And so they have to keep it, they want to keep the machine wants to keep itself going. You know, there is an argument right now in the world in the UK, like, how much do we want to spend on particle physics? The particle physicists are getting a lot of money spent on them to do stuff that basically is, you know, we've, we've basically used the, the Surn and get the expose on great. It was, was that worth five, five billion euro or dollars or whatever it was? I don't know. Well, that seems like it's such a huge part of these spaces in, in any level of academia, especially in science, how much can you drum up buzz and hype and, I don't know, some sort of like, for lack of a better way of putting it like creative sci-fi interest in the general public to be like, ooh, I want people to work on that versus actually funding the ideas that might actually have the merits of being the best to create something that's actually groundbreaking. I'm, yeah, I think that's, that's a legitimate question, right? And I think there's an argument to be set out to be say, look at, look at any, any scientific enterprise when you fund it. You get, you get rewards froming out and then when the rewards tell off what you do, you're probably killing and start again, right? Creative destruction. So that happens a lot in science, but things, you know, it's not just Surn, right? In, in chemistry, in physics, in biology, there's all, you know, was the human genome project worth it? Well, it wasn't worth it at the time, but it's going to be worth it now because we now know how I edit the genome and we know how to, can you explain that more? Yeah, so when the human genome project was done, it was a massive collaboration between the NIH and the MRC. So the UK MRC Medical Research Council and the NIH National Institute for Health, they spent quite a lot of money in basically building technology to human, to sequence human genome. And then also Craig Venter, great pioneer, great entrepreneur, great, kind of engineer, also basically started a company to, to beat them to do it, right? Because he wanted to own it, get the IP, the, to justify it, we said, well, we're going to cure all disease, right? And the human genome was solved and we didn't cure all disease. What's beginning to happen now, which is really exciting, is that there's a lot of gene therapies where we understand how correct a disease gene, like there are some people, but young people when old people that have had a, young people that have been born blind, are almost blind, where they were able to correct protein by gene therapy, and they can see. That's amazing. Wow. There's also gene therapies where we're understanding how to re, reprogram the body's immune system to cure cancer. I mean, there is a very strong chance that most cancers we know about within our lifetimes would know, if on our lifetimes, we'll have a combination of molecular and genomic therapies, where we'll use small molecules. I think they already have them, and they're just not giving them to people. No. Why? Why? Because that's the stupid thing to do. Why is that stupid? We've had the same, they've improved some levels of how they treat cancer, but we've utilized the same type of treatment for decades now, and it's brutal. So yeah, and the companies are getting there, right? It's, I think they're, so no, this is one conspiracy that can't exist, well, it doesn't exist, right? Why? Because there's lots of pharmaceutical companies, pharmaceutical companies, classically, there's lots of chemists doing medicinal chemistry going way back. Medicine and biology are moving a pace, but the most critical problem is we have.
have to translate those developments from the lab into the clinic and and people are hard and people die. Now there is actually quite an interesting contrast in China and the US and UK right now about how much regulation we have. And arguably there are some some clinical trials going faster in China because of different regulation in the UK and the US and Europe. Now is there an argument to say that there's not conspiracy in the West, but we are much more, we, we're much more risk averse. Right. Right. So could we go faster if we basically said, oh, okay, we'll accept a few more deaths probably, but that actually is. So any limitation that we have in the West is a function of our regulatory environment, which is in function of our voters and the people. So we're not conspiracy. We're like, no, we don't want to. Yeah, no, it's not always the worst thing for sure. Like you look at the conversations happening around like the ability to clone things and stuff like that and, you know, like China's moved in some ways that are like a little fast and taken risk with that because they don't have the same guard rails on it. I think there's something to be said for having guard rails on that for sure. Yeah, I mean, there was one very famous Chinese scientist who used gene therapy to edit some, some embryos that became humans. Right. And, and calls the problem, right? That these people are not going to have such a good life as others. So he got put it to prison because he basically mised it at the gene. Yeah, what did he do that they're not going to have this good enough? Oh, I mean, I can't remember the details. And I think it was something to do with the H. Was it something to do with HIV? The virus. But there was, I'm not sure, but there was something he did that was not particularly good. Small Chinese scientists who produced genetically altered baby sentence to three years in jail. Hey, Jin Que and his two collaborators were found guilty of illegal medical practices. Let's see what they did. The Chinese research who's done the world last year by announcing he had helped produce genetically edited babies has been found guilty of conducting illegal medical practices and since the three years, a court in Shenzhen found that he and two collaborators forged ethical review documents and myth led misled doctors into unknowingly implanting gene edited embryos into two women according to Jin Wah China state run praise at press agency. One mother gave birth to twin girls in November 2018 is didn't not been made clear when the third baby was born. The court ruled that the three defendants had deliberately violated national regulations on biomedical research and medical ethics and rashly applied gene editing technology to human reproductive medicine, all three pleaded guilty. The court heard the case in private to protect the personal privacy of the individuals involved. The report says physical and documentary evidence of witnesses and expert testimony were presented to the court, but it gave no details. Sad story, everyone lost in this, but the one gain is that the world is awarded is awakened to the seriousness of advancing genetic technologies. I feel sorry for JK's little family, though. I warned him things could end this way and it was just too late wrote bioethicist William Herbert at Stanford University and then deep highlighting this in November 2018. He announced that he had modified a key gene in a number of human embryos in a way thought to confer resistance to HIV. The modification might be passed on to the descendants of children born with it. He recruited couples into which the father was infected with HIV and the mother was not his talk at the International Summit on Human Genome Editing in Hong Kong China. He said he wanted to spare the babies the possibility of becoming infected with HIV later in life. The technique could be used to reduce HIV/AIDS disease burden much in Africa. He argued where those infected often face severe disruption, but like you said, they kept it private and corporate, but it obviously caused other serious drawbacks. Yeah, I mean, I think that was completely the stupidest thing to do, right? Because HIV is pretty much now a mehorrible disease, but fascinating that we have now it's possible. I mean, I don't know if it will be completely eradicated in our lifetime, but it will be eradicated. And the reason for that is HIV was one of those weird things where it was a leap from animal to human, right? And obviously it devastated population mainly homosexual males, right? And then we got therapies put it to put it under control. And now we've got to point where you can actually get it under such control, there's no viral load, which means like it's almost, it's not impossible to pass it on. And I'm not an expert in this, but basically you could chemically control it and you get rid of the side effects. And then now you have to point where you could actually suppress the presence of the virus. What an amazing accomplishment for human medical technology. I think he just went, but what's that one step too far? And okay, are we going to edit do gene editing in the in the future in ways that we have to debate? It's a technology that we have to debate? Yeah, absolutely. And you know, in the UK, we've we've we've done it. But anyway, coming back to the human genome project compared to third and pharmaceutical companies is that human gene, the human genome project was an incredible achievement in the same way that you know, the use of CERN to find the he exposed on was the incredible achievement. Now how we take those projects on in future time and how we fund them and what we tell the public is kind of interesting. Right. And I think, you know, science is becoming, it can be expensive. We're in this illusion right now that AI labs are going to automate all science, so it'll be cheap and we'll just cure all disease. And we're going to have and that that's just not going to happen that something else is going to happen. The AI tools will help us cure some disease. They'll help us can produce new molecules. And it might be that it will accelerate rapidly what we can achieve. I just don't know. Right. I like your scenario. I said this earlier, but like in all seriousness, I hope to God, you're like over the target on this because if it's just a huge accelerant that allows us to solve things way quicker, where human beings are still leading the way and creating that intuition and do stuff, then this is the opposite of Doomsday. I think so. And I think that's why I can almost have some simple, I mean, I have sympathy for both AI dooms, because obviously they're trying to communicate a scenario in a language that gets people to think and ask their politicians to basically think, say, hang on, can we just understand what's going on? And I have sympathy for the AI abundances, abundantists to say, let's be optimistic and use these tools in a way that will help human flourishing. What I don't like is the fact that you could wake up. I mean, like if an alien visited Earth, they'd be like, what the hell? Because when you're like, we're all going to die, I hate AI is going to kill us and two, we're all going to live forever and we're going to have infinite productivity, we're going to have infinite stuff. Both of those things are clearly stupid. The nuance says, well, look, there is a worry that we'll use AI systems to hack into computer systems and all software is going to perpetually unsafe bank accounts, encryption, blah, blah, blah. That's a problem. You don't want your Tesla to go nuts on the motorway. You know, you just, you want safety and you want security and you want bad people to not do bad things, you want them to, or to be able to stop them. On the flip side, you want to be able to use AI to accelerate thinking, accelerate kind of technology and, and basically cure disease, make things cooler, you know, and, but what I think has happened is some of the AI people getting quite rich are saying, oh, that money won't exist in 10 years. Yeah, I don't understand that argument at all. Let's just, let's just, let's just, let's just deal on making shit up again. It's like, I don't understand. Like Elon is a genius, but he's not a genius at communicating. What is, what, but what, I, I listen to that a few times and I was like, what the fuck is the logic here? What, how does money, how does money not exist to where people are all just going to be the same, especially like that question? I think it's, so look, I'm not an economist, but I would say the following, money, you're an economist. Money is a, is a representation, an allocation of resource, right? Yes. And, and where there are humans deciding on what to do, money will be required. Now, isn't it going to be great that the resources required to build certain things will drop and drop, drop, almost asymptote towards zero, right? It's kind of great that, I mean, think about technologies now that you can just buy and they're just basically almost free, right? There are some microprocessors you can buy that are just like 15 cents, when they used to be many, many pounds, many, many dollars, sorry. So there's things like that. So the cost of certain goods will get so low that it's relatively abundant, right? But that, that there's always going to be a bottleneck. I mean, Planet Earth has a finite size. There's a finite amount of accessible energy today. We have to bait. There's a finite amount of physical resource. But there's an infinite amount of possibility, which is really cool because that infinite amount of possibility, we're going to recycle things, we're going to find new energy sources, we're going to be able to create entirely new economies, right? There'll be digital worlds where people will be trading stuff and doing stuff and creating, you know, all sorts of art and stuff. So, I mean, I can't pre-judge what's going to happen there, but this idea that we've got infinite abundance in less than 10 years, it might be a reaction because quite rightly, the people creating these AI tools are being astonished by their capability. I mean, think about it, like you can take these, you know, the thing that I find fascinating is you can use Claude or chat GBT to make a PowerPoint. It's pretty good. Yeah, no, it's, you can make it apps with these things too. But the thing is, if you tell Claude, just make a PowerPoint to do X and you don't give it enough information, it's garbage. That's right. So, the fact is, is it that
complicated to understand if you garbage and garbage out is just like if I say oh I don't want to make a PowerPoint presentation Myself, but here the points I want to make and here's a fundamental data for them. Please make it and iterate with me I have no problem with that. I have no problem using AI tools to basically unleash my creativity, right? Because I spend I think what I've had to spend some time adjusting to is The fact that these tools have to be used in certain ways and And you know They a lot of them give me the it right like where comes to writing do I yeah, right? Do I do I use the AI just to write for me? Shit, I mean it's getting better It's still but people can I talk to the average person now and like they'll be they'll look at someone very quickly They'll be like that's AI like the human Intuition on that is pretty fucking good. So I'm and I just love the way the AI is going there. So What's the word? I think semantically uniform Semantically, you know, I think there's basically there's a eight the AI is right in such a uniform way Yes, you can see it so you know and also it's kind of this is not it this is that it's not a it's big I'm just like couldn't please not write like that, right? So what I do tend to use is I write and my writing is fairly flawed But you do something flawed my writing is my right I'm not the I'm not the best trained English professional but I write and I and I try and write enthusiastically, but I but I do use the AI now to Collect typos, but it does try and clean up my grandma. I was like, no, I don't want to say I'm like that. I want it sound like this This is my voice, right, right? So please don't do that. Thank you. It's very robotic But what I have used to which I found quite fascinating is I use the AI is now to look at all my paper proofs Because paper proofs. Well, so when I publish a paper and I've got the proofs and I'm really bad I'm really bad at reading, right? I find it hard to read in a way that Allows us to correct typos. So I had this paper that came out in P&S just a few weeks ago on alien detectives systems Alien detection system find it online. If you think about the idea for a semi-theore for I don't know what it was alien detection or something or life detection and I put the proofs into chat GPT and said just Expecting it just and it went for a found like 10 typos. I did not find like Useful yeah, like it was like really typos a human a human reading it would find it annoying Right and and and what I want to do is make there we go This is the paper in P&S molecular assembly as a universal Signature measurable my mass spectrometry now. Can you bring that from Japanese to English? Just to Sorry from English to English. Yeah, so that's a different kind of English. Should we speak here in Jersey? So So what this paper does it show so it's basically latest extension of assembly theory for detection and what it just says is like Hey, how can I take a molecule? So if I how can I measure and the presence of a molecule another planet and use a measuring device to tell me if that's produced by biology or not an alien biology or meaning intelligent life Not intelligent life just any life evil any life a presence of evolution We can tell intelligence as well. Actually on the same scale. That's what I'm getting to I think we can measure intelligence It's just that so and then we just if if you go down if you scroll down there's a great figure Which my student made because I use machine. Can I read the can I read the abstract before we scroll down? Yeah, you're all right Let's go back up to the abstract all the significant state We want you want you want which one do you like better significance or abstract? Read the abstract. Okay. So detecting life beyond earth requires biosignatures that do not depend on the chemistry of known Organisms molecular assembly ma derived from assembly theory which to be clear You mentioned this today. This is a theory you have come up with you talked about it last time But we'll get deeper on it. I'm sure now Quantifies how difficult it is to build a molecule from basic building blocks linking complexity directly to selection and evolution Here we show that MA can serve as a universal biosignature that is both Interpretable and experimentally measurable unlike information Theoretic measures MA can be inferred directly from mass spectrometry data without structural elucidation We demonstrate that using a machine learning model trained on standardized signal stage spectra which predicts MA with threefold level error Then baseline methods simulated multi-stage data reveal that small Intramental variations can double prediction error highlighting the importance of calibration these findings establish molecular assembly as a Physically grounded quantifiable biosignature measured by mass spectrometry whose interpretation depends on a careful control of Instrumental effects offering a scalable route to life detection on future planetary missions So Dave, let's go down to where Lee wanted to expand upon this with the with the graph I just like the picture with it. So it's kind of nice with because obviously he says You can use machine learning because there's a theory there right so the thing is people have been trying to use machine learnings Look for life and they were just making shit up and assembly theory just helps you understand the basis for it So all it to take go back to my analogy for temperature, right? Temperature we know things are hot or cold, but how do we quantify? We know things are live or dead. We know something's wiggling around and moving or it's dead It's a stone or we just killed it. Boom. How do we measure it? So all the assembly theory does it says well look Living systems uniquely this is the only assumption It is an assumption and we're trying to falsify it and it's falsifiable So you're living systems uniquely make molecules with many different parts, right? Mm-hmm. And in high-copy number So we can measure that so we made them it's equivalent to our thermometer We have a thing called a mass spectrometer What a mass spectrometer does is able to weigh a molecule how heavy it is So basically fires a molecule into a vacuum electric field and just measures how much how heavy it is and then it hits it We hit it with energy and it falls apart and the way it falls apart Yeah, you just break the molecule part you hit it and just it's a bit like taking a plate and hitting it on the ground and fragments Right, and then you count the number of parts and that parts you can then Use that to measure the actual assembly index No, we can theoretically calculate and this was a leap I made a few years ago I realized that assembly index was measurable and calibrated it and caused and that was and this paper is the next step to say well Hey, not only does it work We can now put it onto mass spectrometers. A mass spectrometer is a mass spectrometer on Mars right now. In fact, there's three on Mars I don't know if there's one on the moon. They've been put in in other places and we're sending a nuclear powered mass spectrometer to Titan Called Dragonfly. It's quite cool. That's a hard name. I like that. So basically it's a quadcopter It's going to be powered by a plutonium slug a nuclear battery And it's going to fly around Titan and sniff the air and it's got a mass spec on it and I like guys Use assembly theory to see if we can find life Okay, so let's expand upon this could this be maybe I'm going way too far with this Can you do any of this to try to find life on like exoplanets and things? You can so there's a paper that's going to be coming out soon where we can use assembly theory to To detect to measure the probability for life on the next day planet for sure Now whether it'll work or not we don't know yet, but this paper's going to come out in a few months I don't want to say much more about it because my co-workers have been working on it Sarah Walker and her team at ASU. Have you talked to David Kipping about this? Yeah, yeah, yeah, I've mentioned it to David Kipping Yeah, what does he say? He's excited. I mean, he's an infuse asked for this type of stuff. Yeah I think that the problem is not with David Kipping, but just the the exoplanet world in general is they they're very used to took the used about talking about one marker for life Like methane, which is CH4 or oxygen O2 or water H2O, so these are all very small molecules So these molecules themselves don't carry enough information if to know the difference between Life and death whereas the system that we've built using assembly theory is able to kind of print at fingerprint these gases in a way But uh, I'm sorry. Can you explain that some more you lost me a little bit? So when they're looking at those individual So if yeah, so on methane has been detected on Mars. Yeah. Does that mean it's life or no? No, because a geological process could be producing methane Oxygen has been detected on exoplanet well Oxygen could conceivably be detected on an exoplanet Does that mean it's a presence of life because oxygen is made by photosynthesis on Earth? No, because oxygen is simple. You could you could get it by just breaking water down in UV light, right? So the question is how can you Um, third the presence of biology or evolution in using gases And the answer is going to be a semi theory meaning maybe I'm making a leap here. That's totally wrong But you can instead of looking at individual variables like that. You're combining all them along with other factors to put it all together and determine if there's life Yeah, I mean you don't have to use other factors. You can combine them together So all I'll say for now because again, it's you know has to be peer reviewed and I'm what I you know, I do many things but presenting scientific findings before they're being peer reviewed as if they're accepted findings is a trap that one doesn't want to fall in.
But what I can tell you is I published a paper a few years ago where I was able to show you can measure assembly index in that in the lab using three techniques. I think called mass spec, which I just said is weighing molecules, one called NMR, which is called nuclear magnetic resonance a bit like MRI, right, that you better form molecules. And the third one is called infrared using infrared spectroscopy and light. Now how would that work? So that you just basically you just look at the number of different colors. So the more complex molecule, the more colors it has, right? And so and that and so conceivably you could imagine exoplanets having molecules lots of different colors. Sure. So now are aliens something you thought about like as a kid just as an idea, like, man, there's got to be life out there. I wonder what it looks like or. I mean, as a kid, I mean, was I think about aliens a lot? I mean, not obsessively. I was probably thinking about why am I here? Why does life exist? How can I how can I take this thing apart? I mean, but I think obviously now understanding what life is. I think is is really critical for understand the phenomena of life on earth is going to for sure tell us about aliens how so. Well, what is life as a phenomena, right? As a chemical phenomena. And then if we can understand how, how, how odd is it that is earth that has life, right? And how rare might life be in the universe? It kind of related. So if we can work out the process it gives rise that gave rise to life on earth. We should be an understanding about the process that could give right to life in the universe. Let me let me give you an analogy. But if we let's just imagine we could when we looked up in the sky at night, we did not see anything except during the day saw a sun, because there were no other light getting to us. We just see it's black. We would obsess about the sun. How did the sun get created? We know the sun is created by the collapse of hydrogen. And what happens is hydrogen get collapses goes on gravity. And the point at which gravity is dragging all the hydrogen together what happens when gravity pulls the hydrogen together gets hotter. When it gets so hot, it's enough to overcome a strong nuclear force and then start undergoing fusion. And then when it undergo fusion the gravity is enough. It doesn't blow apart. It kind of self-regulates right because some stars stars could just blow apart. So that phenomena that gives rise to the sun is gravity. Now let's take our universe. We can see stars everywhere in the universe. We don't just know our sun. You can see stars coming into existence and exploding all the time. We're not all the time. I don't know what the frequency of supernova is and I think maybe one a month, one a day. I don't know. We'll accept it. But there's so you can see them. So so we only have an end of one for life on earth. So we if we can start to understand how lightly we think it is chemically the life of most on earth. We can start to bound the probabilities. So so how I'm sorry, how can we do that if we don't even understand how vast and big the full galaxy is. We do understand how vast and big the full galaxy is. You've mentioned that earlier and I kind of I mean we can measure light from the from the Milky Way and we can estimate the size of the Milky Way. But can we estimate what might be on the other side of that. That's what I mean by that. Like how much do we not know what we are. I mean, I mean the universe is pretty big. And we do have some bounds on what we call the light cone of the universe, right. Yeah, the universe is the term I should be using. I'm sorry, not galaxy. Yeah, okay. That's my bed. All right. Now I understand what you mean. All right. Fine. Let's just look at the universe for a second. Every when you look up at every star. Every star looks like has some planets around it, which is pretty crazy. And if you think about it, let's classify those planets. Those planets are either dead and never have will never have life on them. A biotic, but have the possibility for life. Number two, number three are live. They're just living this stuff everywhere. Being and technological, i.e. there's intelligence there. There's technology there. And post biology or post lifeology because it's a biology unique to earth. And there's just technology on there. So it's kind of outgrown it, but arguably just technology on there's like robots and stuff. I don't know, just made up. So there's kind of six type of planet types. So when you look up in the sky, each one of those planets can be one of those six can't be anything else, right. I think I've classified all the possibilities. So wouldn't it be good if we could build a telescope big enough to shine light on them. Now according to assembly theory and chemistry, I think that life is probably only possible. And within a certain zone of temperature, too hot and all the bonds fall apart and you can't have biology too cold, nothing happens, right. But actually, I thought of an idea actually listening to David Kippings podcast, he has the cool world's podcast. So I was listening to that. And they were going about the habitable zone, they realized they were wrong. I realized that planets probably can risk living planets can probably modify the Goldilocks zone. Okay, can you please explain that. Yeah, so so planet Earth starts to after the late heavy bombardment when there's just lots of it starts to cool down and the atmosphere has been filled, there will be feedback processes whereby the planet will probably attempt to regulate its own temperature. So there's a bit like the guy hypothesis from James Lovelock. Okay, but I realized that actually if life starts to form on a planet and within and on that within that zone of, of, of, within that zone of of life support, if you like for that biology, like temperature and pressure and whatnot. If the planet starts to drift outside of that, the evolution will start to kill stuff and the stuff will start to respond again. No, I don't want to die. I will counter that. So like a thermostat. Yeah, rebalance it. Yep. So I think that planets might even lock into a biological or life, a logical, which has made the word up again, and framework where it itself. Yeah. So the planet is able to basically self-regulate for the emergence of life. Okay, let me play this out. This might be totally off base. But if a scenario existed where a planet was traveling around its star, its sun in a certain way, such that it was getting closer and closer to it and heating the temperature beyond where life could be. Are you suggesting that the planet could adjust? I don't know how that would make sense scientifically, but could adjust not moving closer to the sun in order to be able to survive at a lower temperature. So I think pre-intelligence, no post-intelligence, maybe we'll go back to that in a moment, brings up one of my favorite Chinese sci-fi movies, Wondering Earth. The Wondering Earth? Brilliant movie. Okay. They basically, the earth, the earth is going to be engulfed by the sun. So if you don't know that one, there's also Wondering Earth too. Okay. Come on. You know, I'm in. I'm in. It's a brilliant movie. It's a fact. Like, you know, I didn't think that Chinese sci-fi would be a thing. Oh my god, am I so wrong? I'm just so wrong. Oh, they're cooking on sci-fi. Brilliant. Wow. Absolutely fantastic movie. Anyway. But and that's the excuse where intelligent life was like, well, we need to get away from the sun, because the sun is getting too big and it's slingshots around Jupiter. But I won't give too much away. It's a batshit movie. It's awesome. But no, so let's say let's talk about let's say the sun. So the star, sorry, the planet is moving around the star. But it moves around such that it gets closer and very hot, maybe not habitable. And further away, it gets too cold, uninhabitable. I bet you'll be I regulate the pressure and the temperature, the atmosphere. So wouldn't it be, it wouldn't be great if like, oh, it's getting getting too hot. Atmosphere becomes deflective, shields up. Oh, we're moving far away. Turn the atmosphere to trap light in shields down. It could do that. Why not? It's just an oscillation. If the chemistry can respond in, in, in, this is what the earth does now. So we talk about runaway climate change now. I know, but here's what's crazy. I just made it up a few weeks ago when I listened to his podcast. No, but it's not, but it's not even I think it's a good idea. I just never thought of it that way, thinking with earth, like the earth itself as like a. Has its own brain as an organ. I mean, like the everyone's like climate change is such a problem. It's like not for life. It's not like the earth is going to get greener because there's more light. There's more heat. It's annoying for humans, because we're built, we're, we've urbanized around, you know, around the coast and around the equator where it was the zone was quite right for agriculture. But Siberia is going to become really fucking habitable, right? I think I have to get some new prisons, I guess. I mean, as Siberia is like, but on this time scale of a few hundred years, I will be buying real estate in Siberia is going to be great. So people don't really understand, like we're kind of like old doomsday climate change. No, annoying because people are going to die from heat expert heat, you know, from overheating, for lack of water, having to shift and migration. That's really bad. We'll probably come up with a technological solution for climate change. But planet, you know, the planet is a pretty big organism is wrong word, but it's a pretty big. Um, um, uh,
able to kind of respond. So I think again, looking at these parts in the sky, they'll have an incredible amount of dynamics will probably home in on life, because life produces more complexity, more adaptability. So maybe the most interesting planets, so I'm going to maybe Earth is going to survive longer than otherwise would have, because it produced life. That's right. Wow. I mean, be so cool. I mean, I think we're looking at life all wrong. And you know, and actually, this is one thing Elon says, I mean, Elon says such a great thing. But look, if your sun needs to lose mass, so it doesn't, something bad doesn't happen to it, I'm sure a life form could say, I'll just take some mass from the sun. The other thing I would, how would that? Oh, I don't know, just make a vacuum cleaner. How hard is that? I mean, look, let me know for a billion years. So look, over the next five billion years, the sun is going to get larger, right? Right. Right now, the climate change we've got now is nothing. The sun is going to get larger as its hydrogen gets depleted, and it starts fusing heat more helium. And it's going to get, and it's going to get more, it's going to get a bit hotter. Now, what do we do to solve that problem? I mean, the wandering Earth is a bit of extreme version. I would just like, hey, we've got like a couple of billion years notice. Can't we just push the Earth gently that way? How hard is that? Just put a few nukes, boom, boom. And like, you'll just need to shift it a few millimeters a year. That's it. It's not hard. It's fine and desert. If you have two, if you have two billion years notice, and you want us, and you want to care, it's not hard. I don't disagree with you considering the technological innovation we have on very short time scales. I mean, like, there's ways we can play with a gravity. Like, what do we do the moon? I mean, look, I'm not saying that we can do everything, but if we understand the mass of the Earth, it's finite, but it's large, but finite, there's all sorts of things we could do. We could go and drag another planet near us and just push it out a bit. Again, given two billion years, we can do a lot, you know, planning ahead. I got to get you and David in here for podcasts together. He's coming back in in November. We're going to do one, but maybe next year, all right, he's here. Like, he's in town. We can make that happen. I didn't realize your chat with him. I guess make it. Yeah. He's awesome, but that would be really cool to like exchange ideas. I love that you were listening to that and just I listened to it. I was like, yeah, nah, nah. No, I need you to say that to him and the two of you go back to poor because he's also like what I love about his style is he is number one incredibly open-minded, but also like when he's challenging other scientists ideas with data, you know, he's just looking at it by the evidence and he's like, Hey, here's what we're seeing. Could be that. I feel stronger about this, but if they prove this, then maybe they'd actually end up being right. But right now, we can't prove that. So I'm here. He's very diplomatic about it. Yeah. He's a warrior. He's a warrior. He's a warrior. A warrior or a warrior? No. Oh, wow. I mean, I don't, I might be a warrior. Okay. The accent's killing me. But he's a warrior. And that, and I think that, yeah, it's kind of, he worries a lot. But that's okay. Everyone, everyone does it differently. Yeah. I like to be more provocative. They're not not worried because then you can really, I think for science to accelerate sometimes you need to annoy each other. Yes. Because if the, then it just stops because people get too comfy, but maybe AI is going to solve that problem anyway because the AI is going to say, nah, don't be boring. It's going to make us a lot more creative. Well, you're a no bullshit guy. That's what I respect. You're like the minute you hear something that's like, what the fuck is that? You're completely unafraid to bring out the fist and be like, stop, stop. Well, I mean, so you need three components for that. Or I guess you need to be somewhat uninhibited by people pushing back, right? And, and then also you need to be rock, need to be willing to be wrong. Okay. And then the other thing is you need to critical thinking, real-time critical thinking requires you to, basically, I would, you know, I'm sure there's many things I've said today that are actually wrong, but if someone can educate me and say, well, why that's wrong, you know, like, can we make A6 that aren't used with just zero and five volts? Are there variations? Can we make neuro and morphic computers? That'd be great because I'll buy one and play with it. I wouldn't have to make a plug you know, gerk it into the mains, right? And so I think that having new ideas and being out of Chinese those ideas, almost like in a sandbox, right? Or whatever in your mind, imagine them, and then create new things. It's kind of interesting. And I think a lot of people we're, mysticizing, if that's a word, AI, right? We're revering it because we've been told it's magic. It is quite interesting. I do think though, going back to AI and there's anything I'll say on it, before we can talk more about 70 theories, that something did happen, when we open AI did, they basically hit upon a cognitive treasure trove when they train their model. And suddenly the chatbot started to be really good at predicting the next token. And as you increase the context window, it got even better. And then when you basically built kind of guardrails or chain of thought abilities, suddenly these systems were able to daisy chain together, daisy chain. Yeah, just basically say, if this, then that, then this, then that, da, da, da, and then, and then you checked everything fact checked within. And suddenly these tools became incredibly powerful. But for me, it's like, meh, I wanted my computer to do that since I was nine years old. There was no physical reason I couldn't do that. It's just programmers from rubbish. If you have finite memory or programmers were too good, I don't know. So I think that AI is, we've got to demisterize it. And that means that we have to start saying, well, what is intelligence? What is creativity? What is novelty? And I'm really asking these questions and stop pretending the AI's are because this is where humans will, you know, until we understand how what life is and create new brains and things, humans still have a job. And isn't it? And maybe there is an argument for kind of saying, well, there are some city things we can automate. You know, my company, I have this company, the gamify, gamify, gamify has got a few hundred people in it now. Like, oh, wow. And I was at a meeting with a load of people saying, well, you know, I mean, they were shared all this number of people from my workforce. And I was like, guys, what are you doing? Like, not only you're basically, you're, you're getting rid of people because you want to, you want to temporarily increase your product, your profitability, but actually look at the human race. We have fantastic human beings are fantastically flexible, infinite problem solvers and infinite creativity machines. So what you want to do is you want to employ more of them, not less of them. If you're giving them a stupid job because you're stupid, that's actually, don't be stupid. Yeah. Didn't you come up with assembly theory? You were telling me with, with like your finance guy, he was a finance guy at the time. Yeah. He was able to do that with you. It's like, no one would ever think something like that could ever happen, but you have to be even open in the situation and possibility. I mean, so I do, I find the whole job displacement theory rather distasteful, but I also do find the fact that, you know, in the world, in any organization, you've got to, you know, I mean, my company, you've got, you want to make sure you don't break the law and you've got to have good working practices and good regulations and there's data protection things and all this stuff. So you want to have all of this, but I've hired a lot of people to do incredibly creative things. And also we're building, we're building this thing as we go. I mean, chemifies aim is to build a world model for chemistry. What is that? As League on for AI? I mean, it's kind of kind of, no, and it's not a joke, but it's like the world model for chemistry. In fact, if you go on the web, you go chemify.io and slash Genesis explains the world model. I built this landing page myself. Genesis? Chemify Genesis. Yeah. Chemify Genesis. That's a biblical shit right there. Well, that, that is because it, and it's called Genesis on purpose because the world model, is that we want the world model for chemistry. If you go down, yeah, you can go down. You can see, okay, keep going down. The molecule on the screen is only on hypothesis. S make test. So the idea is that Genesis is about the fact that in people think that drug discovery is discovering a molecule. This is actually the answer to creativity and novelty in AI. Yeah, I really, this is like a chemist is able to come up with it. So in the old days, the way you did drug discovery is you basically just look at, go and get plants and things and look at the molecules and discover molecules that look like they have some kind of interesting microbial activity or biological activity. So you would discover the drug, right? Okay. Now, if you think about chemical space, chemical space typically is said that chemical space is about the 10 to the power of 60, right? Okay. So that made four kept drugs. So that is if the average drug, the space of possible drug molecules is about 10 to the power of 60. The number of atoms in the universe is 10 to the power 80. I actually redid that calculation. It's not 10 to the power 60. It's 10 to the power of 117. Now, how'd you arrive at that? It's fairly technical. It's on the archive actually. Okay. So if you, I don't know what you would put on there for it. It's like a size of chemical space, Krone and X archival, something you might find it. Size of chemical space. So you showed the work. My high school math teacher would be proud.
Yeah, we got it. Elucidating the size of chemical space with the assembly. Yeah, okay. So rather, so we looked at the number of steps you would take. So basically, if you allowed your molecule to have, I think, 25 steps, you know, if you click on the PDF or go up in the right hand talk corner, I think it is. Yeah. There you go. And I think if you go down the table, there's a table, I didn't think like we'd ever want to chemo, chemo-traumatic thing, but keep going down. There's a table with the numbers in and there's some pretty big numbers in it. Keep going. The biggest numbers. I was going to do a trombone. Right there. And I think you have to go up now. Sorry, you went too fast, too fast. There's a lot of pages. I know there's a lot of pages. A lot of math as well. I'm sorry. It looks smart. It looks smart. Trying to give you something, like, yeah, it's just math. I don't know where it is. The table might be further down. I can have a look. Maybe go to the back of the paper and go to the way to the front. I'm at the point where I'm ready. There we go. That's a table. I was going to take care of my phone. And then you can zoom in. Oh, look at that. Yeah, there's the number. And then you can look at the assembly index. Yeah. So assembly index 25, that is, if you take a walk, random walk, and you take 25 different steps with the chemistry that's available, there's 10 of the power 170 molecules accessible. Right. Now, there are some duplicates, there may be some that are impossible because the laws of physics, right? And that we've tried some filtering there because the referees are arguing about this just now, but that's a really big space. So now, so when your space is so big, you cannot search it. You can just, you have to hop there somehow. How do you do that? Well, that's yet, Janet, you really have to generate something new, right? Or novel. So that's where Genesis comes from. If it's just searching, it would be like a search engine. So that's why, basically, I've, you know, the, I think on the Genesis, if you go back to the Genesis thing, go up, I think if you go up, I don't know where it is. I might have made a statement, but go back one. Go back one. And I think it's like not a catalog, not a synthesis, or not a retro synthesis. It's a computation. One executable loop wired to real chemo farm capacity ideas to verified manner. Yeah. And so the idea is to say the space is so big, you can't search it. You have to generate it. You have to really make it. But if you go back to the beginning one, sorry, the hallucinate, I loved it. My, I was able to testing it with a friend. It was like this chemical hallucinations is that hard. I made it. And then we was like, oh, your market wouldn't like it. And at least, I let people know I didn't use an AI to create the carousel. That's right. That's right. Because at the end, if you go to the end one now, the meta, right? Because I like the meta, because computation is, you know, we're drowning in meta molecular. So the chemistry of the future of chemistry is making the meta physical. Right? You know, you know, people say, oh, that's me. Yeah. Come on. It's the joke isn't that high brow. That's meta physical. But now let's make the meta physical. Okay. You're like, get a new job. Yeah. I don't know if that's funny as you, you know, you got a good sense of humor. I just don't. I did it. I put it up there. But the point is that the genesis engine creates molecules. It doesn't discover them. Because you can't discover something if the space is too big to search. You can only create. And that's kind of weird. And that's the same thing with AI. Right now, all the AI is generate. So there's all these people doing drug discovery, but they're just generating random graphs on the screen. I can't make them. It's like, so people go, I've discovered a drug or a new battery molecule. I'm like, what do you mean? So well, this is what I got on my simulation. I'm like, oh, great. Have you, have you got it working? I know. I haven't made it. I'm like, well, that's just bullshit then. So basically, I realize, because what chemifies been doing is making molecules in the hard world for hard chemists. And then you got the AI world. They're just generating just bullshit. Right. And genesis connects the two together. And now I'm excited because people are, oh, so you can, you can connect R.A.I. to your engine. And we can have a dual A.I. and we're just, yes. And so all we're doing now is like genesis is a forward deployed kind of chemophile engineer that connects people. We buy it so they can just use it. And so they keep their IP. But anyway, I won't sell the company on your podcast. It's just now you can sell it on this. Why are you here? Raise a lot of money, too. Employing a lot of people, too. I mean, we haven't raised, you know, I kind of sad. I'm such a bad fundraiser, right? Such a bad, you raised 70 million since the last time you're here. I feel like that's pretty fucking good. But then look at all these AI kind of AI things that have raised hundreds of millions. Right. That's all right. But then one of my friends were saying to me is that comparison is a thief of joy. That's right. When you were, were you like into art when you were growing up? I mean, although you're into it a lot now. Yeah. Yeah. Because when I hear you talk, and there's other scientists I've thought this about as well, who I've had a chance to talk to, you remind me of like the way you look at things and the way you're visualizing things in your mind and trying things is very similar to how a musician describes making music or how a painter describes painting something or how a sculptor describes sculptor from one slab of marble. It's a very, very similar, if not the same wavelength. Yeah. I always thought about that. I think so. I mean, I think there is a certain amount of, because the genuine creativity can't just emerge from you applying some rules. Right. I was, and I think there is something to be said for how a great, you know, I'm very interested in how Genesis works. It's going to work. And the nice thing is I've built this chemi farm in Glasgow. And I just connect, I'm just going to, it's like think of it when Nvidia built its first H100s and put them into racks. There's literally what we've done. So we're just going to set out that capacity. And then we're going to use that to make the next capacity. And then basically every single molecule that we invent will basically be much faster because of this. So all farmer, all batteries, all catalyst companies, anyone who deals with chemistry will need it new. You see it coming together because what happens is every time we do a reaction, we get faster because our world model gets better. Then what I had to do is I had to figure out because I was trying to sell this. But all the organic chemists are a great partners, like kept giving me molecules that were too hard to make. Because you think about it, chemifies library. Do you want, do you want to know how big chemifies virtual library molecules make? How big? 10 to the power of 40. That's large. That seems big. But actually, but actual chemical spaces about 10 to the 117. Yeah. So when anyone comes to me, go, can you make this? We're like, can you make that? Baby steps. We're like, can you make anything? Can you just, can you instead, rather than to rather new picking molecules that you want us to make? Because we can make all of them. But it takes time. Yes. So we've got this kind of lot, they've got this virtual library. It's not a catalog. It's not even that. It's like so big. It's like a, it's a procedurally generated process, which allows, which allows us to compute. So compute is our verification process. If it computes, we know we can make it for real tomorrow. Right. That's really awesome. So what we do is, rather than you going giving us a molecule and hoping to get lucky, it's a bit like going, I'm going to take a shot. You've got 10 to the 40 possible targets. I'm shooting in the space of 10 to the 117. You're always going to fail. But even if you say, oh, is one of those 10 to the 40 possible targets good enough for my drug idea or my catalyst idea? The answer is then yes. And suddenly when you flip it around, but then they don't want you to own the design. So I design Genesis. So it's a bit like the way the UK does its bio bank. So basically people buy Genesis and they keep all their IP. So I'm able to federate the data. Oh, I see. Okay. So basically when they bring in their question, their question is probably the most valuable thing. Like you can answer this question. And so basically, I built an AI that takes their question, encodes it, gives them physical matter back, allows them to do it quickly. So basically, I think I've just built the, the most valuable engine for chemistry ever. And that's cool because that gives them retention on their own stuff. They keep that. So basically then chemify gets faster at making doing chemistry, but no one ever knows what they're doing. It's completely encrypted and segregated forever. Wow. And that's the way the UK bio bank does it kind of because what you want to be able to do the way the bio bank works in the UK is like, you had this problem where let's say as a patient, you go and say, I want to know what is the best treatment for me. And you're like, great. We'll interrogate the bio bank. We're going to put your data into the bio bank. You're like, oh, no, I don't want people to know. I don't want an insurance company to know. They're like, no, no, what we do is we tag. We basically encrypt it right and strip away your personal data and just put it into space. So your characteristics are in the space and queryable, but you and all the everything associated with you can't be reverse engineers. You're like a lesser version in a good way of like a Swiss bank, but for chemistry. I'm not going to say that, my investors are like, I'm a laudera, but no, I think I'm cooking. I think so. I will. You can know, but sure. Okay. All right, real quick. I gotta go to the bathroom, but we'll be right back. Yeah, me too. After you, I'll go after you. When you look at what you're doing, when you look at the scaling, regardless of, you know, the argument of resentience and all that, but when you look at the scaling of tools, like AI and and the abilities that humans are able to leverage now to be able to figure things out, it's such an exponential rate. Do you ever worry about the incoming
abilities of us to potentially start playing God on something? - No, I want to play God. - In fact, I don't want to play God. I mean, look, we've got mobile phones. We have drugs, we have cars. I mean, I want flying cars. Where's my flying car? We've got robots. - I don't think that's playing God. - I think the Chinese doctor you talk about, though, that's where it gets to like, you can be playing God. - I think, no, I think playing God, if you like, is taking any scientific, and what was it? Isaac Asimov says, you know, any, when any scientific. - You were sure of magic. - Yeah, so when science can do that, science is a lot. Imagine going back in time with a fully working mobile phone satellite system. Anyone be like, what? And then here's a face. Here's a face of my mate around the world. I'm facetiming him. What? So we are playing God now. I think that what we've got to be able to be very good at is making sure that humans are flourishing and thriving. And what does that mean? That you want the average human being on planet Earth to be happier, to be more content, or whatever it is, to be more excited, to be contributing to the flame of consciousness or whatever it is, so that humans continue to kind of do more and more things and build a technology that makes everyone's lives better. And yeah. And are we doing that? I mean, by any measure, human beings have never had a better time on planet Earth. Ignore polarize social media, it says we're doomed. And it's like, yes, there's climate change. You know what? We're gonna fix that. It's not gonna be that hard at the end of the day. We'll shove a load of sulfate in the atmosphere and we might get it wrong in an overcool and a bit of acid rain and then we'll add some base. I mean, some people will die. Well, no, I think that, look, but less people will die, right? Right now, here's a, here's a quandary. We have all, we're burning all this fossil fuel. Most of the fossil fuel we're burning is to create fossil, is to create ammonia, to feed the world. That's creating global warming. That global warming is causing stress. But there are more people alive today because of technology that ever lived. And if you didn't say, oh no, we feel so guilty. This is why the climate people are kind of like, annoying me saying we should like go and live in caves. I'm like, who are you gonna start to death? Tell me, which half of the population are you gonna kill? So sure, if we attempt geoengineering and we create some accidents along the way, if that saves billions of lives and we basically 50 people die of, I don't know, a thing, I'm foreseen, then do the calculation. But what about like the genetic engineering and where that ends? I think about this. We're genetically engineering rice right now. In fact, if it wasn't. No, no, no, no, that's not what I mean. Well, maybe, but that's not where I was going with that. Like when you look at what the guy's a colossal are doing, I like them. I've had Ben and Matt on the show. I don't know what they are. They are the bioscience company out of Texas that is recreating extinct species. So they made a version of the dire wolves. So they tell you. So they tell us, yes. But to be clear, like they're honest about this part, they made a version of the extinct dire wolves that's based on gray wolf DNA, which gray wolves obviously still exist and share some sort of familial bond with dire wolves so they didn't create like a perfect dire wolf. But like when they're looking at maybe creating something that is not evolutionarily, but is somewhat similar to say a woolly mammoth. Part of why they're doing this is because woolly mammoths, for example, share DNA with elephants and in modulating or creating a potential woolly mammoth, they could say solve for, I forget what the disease is called, but there's this disease that's effectively called elephant herpes that kills 20% of elephants around the world. They could effectively solve for that by testing on what would be this woolly mammoth before they make it. And therefore, it's useful. However, when you get to the whole idea of maybe this technology then gets used to clone animals. And then what if they start talking about cloning humans or something like that? It's a slippery slope that potentially that's where I started. I love a clone. I don't have enough hours in a day. I should put it out earlier. I'm just joking. Look, I think that society, so one of the things that I, so I don't know, it's, to me, the guys might be great, but it sounds like what they're doing is a bit like, I mean, like George Church is presumably behind us, behind all this stuff. So George Church needs to get out more, I think. - Needs it. Why do you say that? - Well, because I would look at me. - You get, I mean, that's a big statement. - George is lovely. He's just very mischievous. Let's put it that way. - Very mischievous. - Yeah. - What do you mean by that? - He basically likes, the same way I like a fuck around my chemistry, he likes to fuck around my biology. And I think, you know, is he a bad person doing it? No, for sure not, is a great scientist, but I think he is literally trying to test the limits of where what do we want to do ethically? What do we want to do commercially? What are the driving, should we, you know, here's a question, is, this is very controversial. It is low IQ, a curable disorder, right? If we can measure IQ in some objective way, and then you say, right, you've got a choice between having someone with a high IQ or low IQ and you could genetically engineer high IQ humans, would you do it? - This gets weird, this is what I mean. - This one's playing, I thought the answer is, I mean, I mean, well, I don't know what the answer is. The answer is society would decide. I think being mischievous, in general, one needs to pay attention to what is ethically acceptable and society acceptable, but let's take today, what is, you know, cesarean section? Would we argue that cesarean section today is a fantastic tool? - Sure. - So, but a few hundred years ago, I probably wouldn't be an acceptable, right? - Me. - And so, I think that we have to understand if engineering people to have a higher IQ gave them better resilience to live and was better for the human race and actually stopped people, I don't know, voting for nonsense parties or something, not saying that low IQ people vote for nonsense parties, I don't know, right? Engineering critical thinking into humanity, is that a good thing? - I don't know. - Actually, maybe just scrub that. - It's just, it's just, no, I don't want to go there. - I see what you're saying. I think it's just, it's a weird, uncomfortable space to get into with the questions because it's a slippery slope, how far do you go? Something that seems realistic and good, you start there and then eventually you're like, yeah, let's give them all 18 inch dicks, too. It gets weird. - Yeah, you said that, don't mean. - I would scrub this entire section. - No, it's good. - Okay. - I don't like scrubbing stuff at all. - We're gonna talk these things out. - I would say, when it comes to, so you're saying, let's discuss the ethics of genetic engineering or technological engineering in general and how to play God. I would say, it's society needs to decide. I'm very comfortable with certain technologies to have today like mobile phones is area in section. If we could engineer certain favorable attributes for humans genetically, should we do it? I can see a world where that just becomes acceptable over time, it's very ghastly right now. But why not? Why would you, there is a good example in the UK where we have what say three parent babies, where what happened was that there is a particular disorder, I think passed on by the mother into mitochondria. And I think you can find this as like a disorder where the mitochondria is so critically disabled, you get kind of muscular, I'm not sure it's muscular dystrophy. Basically the child is not gonna live for very long. Now what they did is they said, right, but the couple want to have children. But the mother is never gonna have a healthy child because of that. So what happened is that there was a suggestion made that you could take healthy mitochondrial DNA from another mother female donor, put it into the cell. Right? And so, and the mitochondrial DNA is just in that cell, but the mother, all the other characteristics of the mother comes from the actual mother. And so you can give birth to children with three parents, if you like, but completely healthy. And in the UK we did it. And there's eight children. And those children do not die a horrible death of muscular dystrophy. Yeah. That is in completely worthwhile. Right. On the surface it's hard to argue with that. Yeah. I mean, sorry, if I, if I came sent in and I knew that I could have been born with functioning muscles. I'd be pretty fucking pissed off, yeah, I agree. So, you know, so that's a good example. And the good thing about that is it's already gone through ethics and, you know, I can basically not debate. The woolly mammoth and all the other people do random stuff like that, it's like fine. If there's a market and, you know, Jurassic Park, that's my worry, though. You've seen those fucking movies. The dinosaurs eat the people. Well, that's, you know, then. No, no, don't, don't you know me? I don't like that. I don't want to see like a T-rex out here and just like tearing your head off. If someone could actually get a re-resurrected T-rex, I would want to pay for that, be great. Okay. That'll be awesome. If it's on a leash. But look, the probability of it being possible, I don't know, like, you know, we have all sorts of things, but I think that's a very good example, a very positive thing. Now, where could that be misused? Right, your mitochondria are vital for delivering energy to your cells. If you supercharged that, you can give rise to super athletes. That could just be, you know.
be like the Russian Olympic team, but they have no steroids, they already got it. But, you know, isn't that in a way kind of interesting? A good, but then do we start having like 12 foot giants walking around? We do have 12 foot giants. Have you tried, I mean, well, we have six or seven foot giants. I was gonna say, I was unaware of these 12 footers, please, please do disclose. You said that real confident. Yeah, whatever. Yeah. Okay. No. But, but I'm saying, we do have natural biological capabilities. So what's the word? A genetic, there's a genetic destiny, but in Western Europe or whatever, during, you know, the, I guess in the last few hundred years, due amount of nourishment, we didn't achieve that genetic destiny, right? People, we sure. Then you've look in the Netherlands now, everyone's like six foot, whatever tool. But look, your question is, am I worried that we can play God to some degree? I'm worried about that with the chemical computers. Sorry, all the computers. Could people just, but get these robots, get this technology away from chemify and mass manufacture bad stuff? Well, you know, what I've done is I build a encryption into the system. And actually GPS, they will have the end GPS geo located licenses. Do you have like a, like a red button, not to oversimplify it, but like the button in the dark night where Morgan Freeman hit it and the whole machine turned off? Like, can you do that with your technology? I mean, I think that's rather simplistic way of saying, is there a way of making sure that, I mean, right now, chemified builds its own robots to do stuff internally and no one will be a copy it, right? Because of the way that we design things and segregate it, will people be at design robots to do bad things? For sure, we have them today, right? I think my job as an entrepreneur is to basically use the technology to do good things, right? And the market to access that. And then if, you know, there are people out there using 3D printers to do chemistry, to kind of bio hack or chemical hack. And they're going to end up injuring themselves, right? It's really bad. No one's using any of my technology for that. But, well, I know, actually, I am not, so there's no one's, there's nothing stopping people taking my papers off the web and using that, those papers. Yeah, but not the stuff you're actually creating. Yeah, yeah. But is there a big road button in the way the chemifarms are built, there's obviously a huge amount of firewalling and being able to kind of control the system, right? Real-time telemetry and also to make things sure that sure they fail to safety. So for sure. But when we do that at scale, I mean, you know, the amount of chemical flops, right? Like, you know, you have CPU flops or whatever is going to increase, you know, a hundred years ago, computers were people in skyscrapers basically doing slide rules. So the number of, you know, what were the number of floating point operations per second, a hundred years ago, several hundred thousand, maybe several million, because there's several million people in these places doing calculations with slide rules. Today, how many people doing chemistry on planet Earth? How many chemists are there doing reactions every day? It's less than a million and probably more than a hundred thousand. That's not a lot. I think the one of the ways, the one of the ways why AI and physical AI, I was called chemifying, in a way, will be positive for the US in particular is like the healthcare system is a bit, bit annoying just now. Oh, yeah. But think about like this in the future, the birth rate is going down. So human, humans, there's not that many humans and you want to keep people healthier for longer. So people are basically able to get access to healthcare, subscription, and they have more productive lives and then make more money and have good fun and do whatever drive the economy. Suddenly you got this economy that inflates, not because like it's kind of amazing, right? Yeah. Yeah. And that scenario could be amazing. I mean, it will happen. It's just a question of how we fuck it up along the way, but but it will happen. And it's, I think that, you know, one by one bit by a bit, there's things that we're going to be able to solve. And I think that that's why I, you know, I'm a great kind of techno evangelist. I'm not quite the abundance. We're all going to live forever. We've got infinite stuff. We'll build a Dyson sphere around the sound because why not? But I do think that, you know, I'm very enthusiastic about the intersection of technology and science and critical thinking and also the free market, but not entirely free and also, well, not kind of the corruption that we have right now that I do see where there's just like, you know, the only the only place where capitalism is really work is really meant is being forced to work, maybe in the arguably in the US and the UK is in the middle classes. Like if you're really, really rich, you can do what you want. If you're really. Yeah. Yeah. Maybe that's me being slightly to kind of weird, right? And all the rich people say that's not right, but. No, I think I think it's a fair point. I think I think there's almost been like a socialized capitalism that's formed for sure in the upper classes, which is kind of weird because I'm hoping that that will revert. I mean, the UK is like in the is in the doldrums, like everyone's miserable in the UK is such a terrible country. It's like, actually not. It's great. There's more entrepreneurs in the UK, probably per capita than anywhere else in the world right now, although it's quite nice in France, in Switzerland, in Germany, they were coming up, not quite as good as the US, but in Germany, but we're not sorry, not good is the wrong word, not quite the same number, but I think there's a lot of interesting things happening because people are realizing that, you know, it might be that the in 20 years time, everyone, everyone wants to be rather than being, I don't know, being a management consultant or working in a with a bank, they want to be an entrepreneur. That would be great. And they're just basically identifying unmet needs and getting funding for the unmet needs. And then so we have this new kind of knowledge economy that evolves, but I'm a relatively late entrepreneur. I don't want to be honest, but I kind of became one by accident. Well, here you are. Well, it's working out for you. There, you know, the working out, it's not about the money, it's about the the ability to appropriate, appropriate, sorry, what's the right word, appropriate from worth? It's about to allocate there. Thank you. It's about allocating resource, right? I mean, when chemified becomes a trillion dollar company, I will be out allocate resource to helping cure disease solve the origin of it. Yeah, it takes on a whole new life of its own. Yeah, I mean, that's one of the longest Dr. James Tours, not, you know, right in your run. Dr. James Tours, what was he right about? What will he be right about? I don't know, you tell me. I just saw you guys going out on Pierce Morgan. What was his argument against yours? I don't, I don't, I mean, James is a complicated person. He's a, he's a, he's a born again Christian who is a chemistry professor, but he's a kind of, I mean, what is his argument is that he doesn't, he's very slippery in his argument. He just basically says, hey, the cell is so too complicated. Therefore, origin of life isn't as easy as we thought, right? And, but I do believe that we'll solve it and it's not just, you know, you think we'll be able to figure it out. No, no, he says, he says, right? He says, so he kind of makes all these, oh, I'm a real scientist and I'm doing this and the other. But look, Dr. James Tours is a chemist. I wouldn't say Dr. James Cork is a scientist. What's the, well, I mean, I'm going to sound really pompous if I go down that rabbit hole, but I mean, I would say that, oh, maybe he's a chemist first and scientist second, whereas I'm a scientist first and a chemist second. Okay, is that does have to do with the way you're defining following the scientific method to ask questions versus. No, I mean, I would say that, I would say that James basically does chemistry is very good at chemistry. He uses that authority to make sure authority over his belief. I got it. I got you. Whereas I'm like, I'm clear. He says, you know, clueless, clueless, you clueless. Everyone's clueless. I'm like, but that's why I love doing science because I'm clueless. And so, and I mean, I wouldn't use a word clueless, because that just sounds silly, but I do, why would I do experiments if I knew the answer already? So you look at him as more dogmatic and like, yeah, it's harder for us to change. Whereas you're like, we got a shit against the wall. I mean, I think so. So I mean, I'm the only person who debate him. And I don't know what the origin of live chemists think about that. And I think it is kind of complicated. But also, I think I am willing to like talk to you, talk to people that want to listen, and give my views as flawed as they are, but it starts a debate, right? I don't think. Right. You know, people come to me and say, are you the authority on this? And I'm like, I'm not the authority on anything, but I am working on this. And I think I've made a commitment to doing this, and I've made some progress. So from that regard, I might have some expertise you might find valuable. Yeah. But I think there's people who over-credentialize all the time and say, well, I'm a scientist and I get this. So I think that, you know, you'd have to ask James what he thinks. And the reason I did the thing, which I was like in two minds when Pierce Morgan's team kind of contacted me and said, I like that you did it, though. You go out there, you challenge ideas, you let people listen to the arguments and decide for themselves. That's how you should always be. Yeah, yeah.
When I thought what could go wrong as he could ran at me and I could just go you know, yeah I thought it was pretty simple. He pretty I mean he's pretty ranty and I just like I'm not going to argue I'm not gonna I'm not going to descend into Ad Horneman. I'm just what to say look This is what we're doing. I think it's quite important and I think it's quite interesting because I actually Pierce is you know, he's he he has a religious commitment He also thinks aliens must exist. He's like he will he has a huge following he asks sensible questions You know, and um, it was quite it was a fun debate to have looking at it. I mean a few people said you surely want to do that and and I did it and one of my kids did watched it and was like This is the first time I've heard you ever talk about something and I understand it Oh, and if that and if my kid is like that's good was inspired by that and I was like, okay That's worth doing if nothing else, right because right because I've talked I you know my sons are really smart And I talked to them all the time and the guy was like one of my sons was like I have no clue what you talk about most of the time but on that on that discussion You made an effort to engage in a way that I understood it and I was inspired by I was like we need I was like, okay Great as we're doing always I honestly I hope you're always saying yes to that stuff because like you get a chance to put your evidence to the test And there's nothing better in that and that's what we need we need to open dialogue with science But it's always great to have someone in here to be able to talk for a few hours and walk us through all the cool shit They're doing so thank you as always. We're gonna have to do this again. Let's let's go get some steak though now All right, thanks to a big with you and yeah, too next time all right everybody else you know what it is give it a thought get back to me Peace Hey guys, if you're not following me on Spotify, please hit that follow button and leave a five-star review They're both a huge help. Thank you
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