Julian Dorey Podcast - DARPA Scientist UNLOADS on AI Doomers, DNA Gene Editing & CERN | Lee Cronin

Episode Date: September 30, 2026

SPONSORS: 1) ULTRA POUCHES: Don’t sleep on @UltraPouches . New customers get 15% Off with code JULIAN at https://takeultra.com ! #UltraPouches #ad 2) BLUEPRINT: For a limited time only, new customers get 20% off + free shipping at https://blueprint.bryanjohnson.com by using code JULIAN at checkout. #Blueprint #ad JOIN PATREON FOR EARLY UNCENSORED EPISODE RELEASES: https://www.patreon.com/JulianDorey CLIPPERS DISCORD: https://discord.gg/8QmWEKJ3BT NEWSLETTER: https://juliandoreypodcast.beehiiv.com/get-julians-top-10-books (***TIMESTAMPS in Description Below) ~ Lee Cronin is a world-renowned scientist focused on bridging the gap between Physics and Biology via Chemistry. He has been involved in Top Secret DARPA projects (much of which he cannot discuss publicly). Lee is also well known for crafting "Assembly Theory" with theoretical physicist, Sara Imari Walker. LEE CRONIN'S LINKS: - WEBSITE: https://www.croninlab.com - X: https://x.com/leecronin?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor FOLLOW JULIAN DOREY IG: https://www.instagram.com/julianddorey/ X: https://x.com/juliandorey JULIAN YT CHANNELS - SUBSCRIBE to Julian Dorey Clips YT: https://www.youtube.com/@juliandoreyclips - SUBSCRIBE to Julian Dorey Daily YT: https://www.youtube.com/@JulianDoreyDaily - SUBSCRIBE to Best of JDP: https://www.youtube.com/@bestofJDP ****TIMESTAMPS**** 0:00 - Lee Cronin, DARPA & Chemical Robots 7:11 - Brain Gel & Whether AI Is Sentient 19:02 - Sam Altman, Anthropic & OpenAI Compared 29:30 - Defining Intelligence Like Measuring Temperature 37:05 - What LLMs Reveal About Human Cognition 49:52 - AI Predicts, Humans CREATE 1:00:39 - Why AGI Isn't Actually Intelligent 1:11:49 - The Drake/Weeknd AI Song & Plagiarism 1:25:38 - Molecular Computing & the DNA Computer 1:34:58 - Simulation Theory Called "Rooted in Faith" 1:47:06 - Was the Human Genome Project Worth It? 1:57:20 - Elon's Claim: No Money in Ten Years 2:11:16 - Assembly Theory & Life in the Universe 2:20:37 - Chemify Genesis & the Job Replacement Fear 2:28:42 - A Virtual Library of Molecules 2:39:58 - "Yes, I Want to Play God" 2:48:34 - Twelve-Foot Giants & Genetic Destiny 2:53:53 - Lee vs. James Tour on Piers Morgan 3:00:50 - Lee's Work CREDITS: - Host, Editor & Producer: Julian Dorey - COO, Producer & Editor: Alessi Allaman - https://www.youtube.com/@UCyLKzv5fKxGmVQg3cMJJzyQ - In-Studio Producer: Joey Deef Julian Dorey Podcast Episode 482 - Lee Cronin Music by Artlist.io Learn more about your ad choices. Visit podcastchoices.com/adchoices

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New customers can use code Julian to get 15% off at take ultra.com. That link is in my description below. That's take ultra.com, link in my description below, for 15% off with code Julian. After you purchase, they're going to ask you where you heard about them. Please support our show and tell them I sent you. Lee, it's great to have you back, man. Last time you were here, episode 289, it was like a year and a half ago, you closed up. We literally stopped the cameras and then you're like, yeah, I was doing some work for DARPA as well.

And you just lay that one on us. And I'm like, well, I mean, you're supposed to say that at the beginning of the podcast. But now you're telling me like, ah, 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 don't. So I will, I've had maybe, let me get this right. So how many grants have I had from DARPA?

So DARPA's 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're established? I think you can check this. So their mandate was like to not, when Sputnik went up into space. the US were not expecting that satellite.

The Soviets launched a satellite, I believe it was in the 50s. I think that's right. And basically DARPA was then established to eliminate strategic surprise. So basically, they wanted a 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? Because they gave money to MIT to Stanford Research Institute. DARPA plagiarized Lee Kronin? I didn't, you used the P word. They were inspired, I said.

Anyway, I remember they got on a call with me, and I was like complaining bitterly. They used this paragraph of what I was trying to do, and they're like, Dr. Kronen, we're phoning you up because we want to talk to you about that. And 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, a zillion dollars. And they said, well, why not ask 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 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 asked me 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. Since 2012, right? So about, yeah, about 14 years. How would you define a chemical robot for people out there who are unfamiliar with this specific type? a robot that you give instructions to and it will do chemistry. So, yeah, I mean, it's fit. So I made, I can tell you about it. But let me answer the DARPA question because you asked it. So that was the first grant they gave me and make it.

And they carried on giving 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 other groups in the US, right? And then there was another grant that gave me for kind of advanced using AI for discovery. So there were the three DARPA grant. I think there's three DARPA grants.

What year did they give you the AI grant? I can't remember. I mean. Ballpark. 2019, 2018, 2019. And then it carried on through the pandemic. It was a bit tougher in the pandemic. But DARPA are a brilliant organization, right?

They go where the experts are. They don't give grants to people in countries that are probably anti-American. I would say, right? So don't, just so. So they're not, they didn't fund bin Laden. So, and also they, 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. I made a molecular computer chemicals to do computation as well because I've, what does that mean? Yeah, I don't know. Yeah. I mean, 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 rather than 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 Bluzov-Sabaskinsky reaction, which is a chemical clock. And all it goes tick-tok, tick-tok, or red-blue, red-blue, red-blue.

Okay? So basically, pour 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, fill it up halfway, put in some chemicals and without doing anything, just leaving, 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 colour or another, what's called an excitable media. It's a bit like 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 about the size of a small book. And in that grid, it was 7 by 7 grid. So 49 little wells. And I put a stirrer bar in each one and 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 a web camera to basically read out the colors. And so when the stirers were on, that was a 1. When a stirer was off, that was a 0. And I basically then 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 to start with the ships and giggles. Yeah, what does that tell us when you're done? Well, that's, hey, it's a DARPA project. It's supposed to be crazy bad. So what it was supposed to do is could I somehow use the, because remember the BZ is a clock, tick tock, tick, tick tock. dog, 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 a neural net, you literally used no power and was quite good at error correction and could like refine images. So the same way you'd use chat GPT or you'd use a kind of invidia's architecture to do gradient descent. And what is gradient descent? And what is gradient descent, well, it's basically that it changes the weightings in the neural network and to basically, you know, 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 not a schedule.

You're making brain gels now? Because we put that and put it in a gel, because it was all liquid, it's 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.

It basically, yeah, I mean, look, we're again, we're all over the place, but why not? That's good. I was inspired by the episode of Pickle Rick and Rick and Morty, and I was like, well, and so, so it's like, I took a girkin, right, and attached the girkin. to the mains to 240 volts and then put in low, you know, my workshop I have at home and used a bunch of electrodes and I tried to program the Gurkyn to recognize the difference between a circle and a square. But it kept exploding. Kept exploding. Because it kept heating up with them. So I took the Gurkin, I thought the Gurkin could be a good, it seemed like a good idea. It's like, a Gurkin

computer. Like, literally, you could just be making this up, right? It's like, yeah, I just, anyway, so GERCEN, 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 gherkin, you soak it in the salt, so it has this salt in it, is conducting when you put power, when you put electricity into it. When you put alternating current at 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 off on off but here with a gherkin. And then when I put in little electrodes, I put in a little grid, and I was then trying to basically train the gherkin to tell the difference between a square and a circle because it was made malleable. It's a bit like taking some cement and making it liquid again.

And then you make it liquid again, and it'll learn something and you'll set it. But the thing is, the gherkin 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 the university would be too happy of those exploding gherkin.

So now fast forward to the brain jail, I was like, well, look, if I could take a gel and then make the gel conduct, right? So it conducts electricity, a bit like a wire and 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 you use a 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 its stimuli. So it's very much trial and error. So it's a bit like how the brain has 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. And so your brain is starting to program. When you're then born, obviously, between, you go through massive developmental surges. So, you know, age 21, 22, your brain may be fully almost there. So then your brain is then able 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 brains work. And what are unique to brains? Well, sentience, consciousness, the purpose, the, and a living system that will tell you that they are an individual. You talk to all humans, most humans you can communicate with will claim they're an individual. Do you desperately need a nicotine pouch every 15 minutes

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That link is in my description below. That's TakeUltra.com, link in my description below, for 15% off with Code Julian. After you purchase, they're going to ask you where you heard about them. Please support our show and tell them I saying you. You're listening to a quick ad. You know what else is quick? Selling your car on Carvana. Just put in your vehicle information and we'll give you an offer.

Done. No hassle, no negotiation, no guy from an online listing low-balling you. Which means by the time I'm done explaining this, you could have basically done it. Still haven't started? Hey, better late than never. Sell your car today on Carvana. Pickup fees may apply. 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 with 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 that AI is 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 doomers are making leaps that the AI can exist without human beings, I guess, in the future and you don't agree that that's the case. Yeah, clearly, clearly it's fantastical. Why do you say it's fantastic? Well, we've not seen any evidence. So if we think about the origin of AI, right, if you go all 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. Wait a minute. Don't do that. The Dartmouth meeting, right? Which you know, you can check. It's a little Freudian slip right there. Sure. Okay.

Whatever. Let's build as many conspiracies as we can. Can, go. But I think DARPA have funded some AI work, right? Right at the beginning. So at Dartmouth 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, and 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, going, no, that's wrong. There are other things called A6, which are basically that you might be able to do what we would call neuromorphic computing,

where basically you can have an analog voltage. So in a transistor, you basically, typically you 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 call it a low. And if it's on the 5 volt side, you call it a little one. But I'm not a qualified electrical engineer. So I don't know how the A6 are built today. I've designed some A6 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. I need to have an analog kind of electrical system for addressing the, chemical brain. 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. 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 AIs 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 DUMAs say that these models could, you know, 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 they are, you know, we use terms like recursively self-programming, I mean, it's a bit like you and I could build an AI now that 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. And on until it either hits the objective or someone turns off the computer. Now, that's always been the case, right? Those loops have always existed. So the AI doom is kind of stuck in 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, you know, And I do worry about that. So I'm not dismissing AI Duma's.

I'm dismissing AI Duma's 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 Duma going, 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 sentience you get from the internet, the training on the model. If you say Claude, are you alive? Claude, say, no, I'm not alive, but I, 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 format, what is if it's a technicality though? And it doesn't get to sentience. But because, and I'm going to way oversimplify this for a minute, we're able to eventually or create technology that isn't quite simply plugged in and, you know, unplugged to be able to do that because of that, a non-sensient but extremely intelligent artificial intelligence who has no ability to empathize, obviously feel any 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 AIs are they intelligent? We have to define intelligence. What really makes me very confused is there are people out there that say, in next years, 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 cause something to happen on its own? No. Could humans not understanding how to set up a system cause something bad to happen? The thing about social engineering, I don't know, take any system. Like, this is kind of hard because I'm not a qualified, I'm not qualified. But let's say we're going to I don't know create a type of bylaw in the city that says right we you know we have to have trees every you know 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 people got it but bless you twice He'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 a institution or in a software algorithm, right? So those things get propagated and there are unforeseen consequences of them. And I totally buy that AI is trying to build to achieve. even objective could do bad things. But those bad things were, 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. Yeah, so don't, so 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 sociable, 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? What's to 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 where 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? Yeah, I think there's a bunch of them. So there's one critical thing that people should have done, which was the policy makers 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're treated like a publisher, that is anything you put on you're on your on your on your platform you have to basically help be held accountable for and so that you that you don't you when you start putting nonsense out there um it can be taking you have to say no it's clearly a lie put it down right so basically facebook and you're good you're good so facebook and x and um 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 entire decision, although, you know, they're a medium. It's a bit like you can't hold the person who built the printing press liable for the bad books printed, right? I 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 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 evolve. However, having said that, if someone invents the social media that's quite good,

as in, you know, a nice place to be and not a hellscape, right? If we can work out why humans are very good at, you know, you get anger for attention, right? Sorry, if you create anger, you get the system once. So, you know, if there was a social media system whereby, I'm not 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, particularly on teenagers. When I grew up, there was no social media. And I've seen that social media has been probably, net 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 who 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, anthropic and maybe open AI, anthropic 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'm not sure if I'm getting that correct, but it seems to me that there is a kind of a split in this right now. 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 aren't yet possible. here's one crazy thing. Look, there's no real conspiracy theories in history, not many, because humans couldn't keep them secret.

But if we had good AIs and we could just pump, 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, 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%'s not. You know, you've got to be careful with where you go with that stuff. Absolutely. And I think that's really important.

In terms 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 people, you don't want to get frustrated now, just use chat GPT. But I think this is an aberration.

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Cox, a step ahead. Requires two-gig speeds and gig unlimited mobile. Taxes and fees excluded from price lock. Mobile data speeds reduced after 20 gigs. If by using AI tools, we can actually allow, help us do critical thinking, help us verify things. If we understand that the current AI 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, you know, straw man or steel 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 AIs might be able to allow you to do one-to-one teaching They've got infinite time, infinite patience, and if you use them correctly. If you use them correctly. Well, we might be, yeah, if we can use anything incorrectly, like I say, you know, so I'm kind of, I'm, as you might tell in this conversation where I'm just saying wildly contradictory things. Strong opinions loosely help.

Yeah, I mean, for sure. But I do think that the doomers are kind of like, they're kind of out. It's a bit like, you know, well, I would say 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 like 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're 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 most. 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 understand it. 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 is 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. And you've got completely different images. in your head and then you leave the conversation, they go and do something else, completely different to what you thought they didn't do. Likewise. So you can have what you've

got to be able to do with these systems to 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 hardlines are, the AIs are not intelligent, right? They're not intelligent. They're not intelligent. How do you define intelligence? Yeah, that's a question. That, that's a question. That is the question that makes sense. Because people talk about AI, AGI, and superintelligence. What is super intelligence, 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 now, a general intelligence would be an entity that cannot solve almost any problem that's coming at it to survive. an entity that cannot solve? Can solve any problem. So you've got basically, you could say your entity is really good at mathematics, right?

Now, people will say, well, the AIs are good at mathematics, and they do solve problems. So now we're saying, right, well, I think that the AIs 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 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 the end, which will 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? 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 the technologists would say, 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 day is you'd have a thermometer. The thermometer could have a number of different liquids in it.

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 I just want to say temperature, we knew that things are 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 cool 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 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. So you needed to make a really nice tube where the sides of the tube were parallel, was a perfect cylinder, or as perfect as you can get. Well, back in earlier times, there were some glassblowers in Italy that perfected how glass blow tubes.

Suddenly, they 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. Oh, we go here. And of course, the Americans, we're going to have. have Fahrenheit. I don't know where you guys got Fahrenheit from. Listen, 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. Okay. We got that right. You got that wrong. Just take the

L, please. Well, there is this temperature scale called the absolute scale and and Kelvin scale. So one degree Kelvin is the same as one degree Celsius. It just goes down to minus 273 point something or other. So that means zero Kelvin is the lowest temperature. You can't get any colder than zero K, right? In fact, you can't achieve zero K 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. Brilliant thing about temperature. Technology was built to measure it. Right.

Right. We knew things were hot and cold before, but we didn't know 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 misunderstanding 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, the ability to solve an unseen problem. Now, unseen is hard, right? Because if it'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? We'll get there. Logic is, so the way to, computers are quite good at using logic. you can code them properly. There's some good programming language to do it, and they can do lots of things. No, what I'm saying is something super concrete. That 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 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. 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. All right. I'm going to see some evidence to that because it looks like the same shirt as last. Probably. I don't know. You can check.

Maybe the other one was a wide collar one. These are narrower collars. Evidence. I was going to wear a different pink. Anyway, it doesn't matter. It's all right. It looks sharp. It's fine.

But you're talking about intelligence. My co-c-so the nice thing is I don't have a cognitive load, right, when I dress. It's just pink. It's good. It could be like Mark Zuckerberg and he just wears like, I don't know, blue, gray, gray, I think. Does he have like a, like, is he like kind of like based with fashion now? Like he's always wearing different chains and shit?

Sure. I don't know. I mean, me, no billionaire. Got it. Me, just poor person. Hey, you just raised like 70 million, milly. I don't want to hear it. Sure. I mean, but I raised it to change the world and chemistry.

That's right. 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 and 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 that 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 convince you, and hopefully by. extension, anyone listening or watching this. So AIs today do 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 time, so that data,

if I say the internet, all the problems solved in the past are encoded, let's say all the problem solved in that past, captured in that data set. So when you give the AI a problem 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's aren't that good because they hallucinate and so on. They hallucinate. Because of the way the structures of some these models work, they hallucinate. And so what happens is that because they have to give you back, back a output, it's less problematic now

because the Frontier Labs, I don't know what they call the Frontier Labs, the top AI providers are very good at basically having what's called a checking system. They might say, it'll come out with that answer, or check it.

You'd like, you go to chat GPT and say, you know, calculate, do a miscalculation. 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 there by humans and so it would just give you random number back. But now that it was says, oh, I recognize this as a calculation. Let me bring up my calculator tool, press the buttons on the calculating at the number back, right? So the AIs are quite good

of doing things like that. But the thing is the AIs are trained on this huge amount of data and all the problems that we've solved up till now in humanity are in there. So, potentially, that's awesome. But a PhD scientist, mathematician, is not about understanding the past. They're trained on that. It's about using the scientific method to solve problems. So whenever you give a new problem that's not in the data set to the AI, it can't solve it. But what if it has enough data and enough retention from all the things in the world

that it can keep it 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 is that not intelligent? So I would not, so 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 human rights, right, to do stuff. But Einstein with a pencil was much more intelligent than Einstein without a pencil.

Because he used a pen and paper, pencil and paper to think. So it's almost like a cybernetic thing. So we get trapped in these circular arguments. Are the AI is intelligent to all the AIs, do they have free will? and are they sentient, 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 AIs? We can call them maybe 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? Right. Artificial intelligence sounds great, right? I'm like, wow. Right. So there is a good, there's a culture. The zeit guy associated with it. But again, the AIs aren't magic. They are incredible, 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 AI, so again, I'm not an expert. So if you train an A&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 prelingual, right, which is conceptual. In English. Ask the AI.

Basically, there is more intelligent. There is 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 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 do the same in English. You overlay them. 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 learned German. I'm not very good at it now, but there's a great word in German called gamutlik. Gamutlik, which is like loosely translates as cozy. So I don't know if you, Gemutlich. Gumutlik.

Because they thought, that's it's gamutlik, yeah. Okay, 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 a nice fireplace and beer. You're going, oh, that's cozy. Nice. Gamutluck. Yeah. Germans have it.

But it doesn't quite translate, right? Like, it's a different kind of word. So there are cultural representations. And 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.

What is intelligence? We don't know. Can we measure it? We don't have a measurement. We know what temperature is. So we've got an idea. 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 if something is embedded in that data and you query it correctly, you can get that out, which is great, right? And the AIs are showing there's a huge amount of knowledge that we haven't explicitly found in the internet, in human knowledge that we can pull out. But it can't use the way the 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? I don't understand that statement.

I understood all of it until they're outrun humans until we get there. Because if they can patternize everything, like let's, let me give it 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 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 as 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 AI's, when the creations are kind of shallow, the AI is great at finding them. You take all these air dish problems, all these ways that you find in mathematics, so the AIs are solving. I mean, and you find all these disproving certain conjectures. AIs are very good at disproving. improving things by finding a counter example. But AI has not come up with a single creative mathematical act, right? 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 it's actually obscuring what the AI is a good at. And I tell you, in the last two years, last one-half years, AIs have supercharged my ability to be creative because I don't have to spend my time doing things that writing code and collecting data and processing things. The AIs are splendid at it. They're really, really great. But what they can't do is they can't create.

They can appear to create, right? And those creations are relatively shallow. But I would say, and this is where I'm really interested in where intelligence is. Intelligence solved. 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 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. Novel, so you can search for something new in your data set and find it in the end.

So when the AI does something and you got all that's 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. But when I then do it, it's a bit like fashion. Fashion is music. That's right. You're not going to know when humans are going to do.

You know, 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 prior data. I'm just wearing pink. Right. Right. The AI is just going to make in the suit right now.

So when I come in wearing, I don't know, turquoise or something or whatever else, he'd be like, that's novel. And so, and it's very interesting that humans are kind of misunderstanding it. But there is a certain amount of misselling here because we're trying to sell AI as intelligent. Going to replace PhDs, replace this. Human beings are going to use the AIs to massively flex their cognitive capabilities, right? Not replace them. This is where everyone's going wrong. AI is going to replace science.

No, they're not. 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, I'm putting that in air quotes, being talked about extensively over, I'd 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 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 to this 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. Right? For data processing. So the AI is a great tool. They're a tool. I don't understand. I think there's something really interesting sociologically happening. So 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 saying 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 are basically, you know, don't critically think

and all woke and so on. Therefore, let's just replace all academia of AI's do. science, right? Now, that's just such a fail on all levels. Sure, academia has problems, right? There's ideologies and things everywhere. But given 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, I need, why do you make sure I can, the boiler doesn't explode and I need to do this thing, and you build stuff. We interact with the world. Now, we will be able to build models and whether 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 be out, make any molecule. That's pretty cool. That's very cool. But there's not magic. It's 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 a 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 can spend money on a, how much does it cost to produce a human that can solve a problem that you can use chat GPT for? 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 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 when you were explaining this with the intelligence loop, you said there's three layers we often talk about. Intelligence, general intelligence, and then superintelligence. 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 layers, obviously. Yeah, I mean, AG, so I think that the providers of AI, right? And I actually like the products. They're great, right? I don't know about your glasses, though. They were doing some shit math before. You might want to check those things. Yeah, I'm not doing any product promotion on your podcast.

But they're not meta glasses. Yeah, but meta might have actually gotten that right, not that I'm trying to show for them. No, no, they worked. Okay. Anyway. It's a little off to me. 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 it to most tasks. Now, is that an AGI, an artificial general intelligence or is it just an artificial general, I don't know, automator? So like, you know, it would be great if I have an AI that can clean up my emails. But actually, I mean, I do use an AI to clean up my email. 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? Don't look at my emails. I get so many emails every day. I find it incredibly depressing because I lose stuff in the noise I need to answer.

I've 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? 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 our failure maybe in human society right now as people go from school to university or wherever they go into a job is maybe we need. generate jobs that have more value and meaning, right? We can do that. And AI provides a great chance that. Now let's go to superintelligence. Well, Nick Bosterer 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 explore it deeply, though. It's like, it's like, look, if you can't define a thing and you say it's super, I mean, I could be a superchemist. What does that mean? So a super intelligence for me would be to say somehow that's

beyond our current understanding of physics and mathematics, like magic. Again, superintelligence plays on this kind of, oh, 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, were able to understand far more than maybe evolution is equipped us with, it would seem. Now, what the Duma says, well, this superintelligence 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 superintelligence because I don't know what that means. Now, it could mean, let me make a, take a stab at three

different things. It could be it's just a faster way of thinking. Well, sure, chess computers can do chess really fast. So I can 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 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, over here, anyone 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, 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 the 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 a question, what happens when I sit on a light beam? So he 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 in the light, what happens? Then in general relativity, Einstein said, well, what if space is time are curved, right? Or more specifically, what if, mass curved space time and things don't take a straight line.

They take a straight light, they go through space times. It's curved, right. Cool. So suddenly, when you go, use general relativity, you're able to go think, ah, if I fire a satellite into space, the further the satellite gets away from 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 with my clock on Earth, I can use that to position using GPS. So suddenly we knew that, we understood general relativity before we put satellites into space. So 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 for it, satellites in space, we didn't have general relativity, we're like, well, the hell, they're losing time. And we would 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 a 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 testing satellites with GPS. If I go back to what Bostrom did pretty early on here, all things are. 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, that. if this then that then that that that that and it created all these different worlds to where you at least i remember i'm reading that book it's 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 in 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. 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've 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 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 superintelligence 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. It's 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 float away. Right.

And we all die, right? Because we're not starting on the planet anymore. have no air, nothing. So I'm like, I put it in your head. What about AG? Shall 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 about, the world, most of the world is not covered with machines. It is empty space, fields, trees, oceans. What do you mean paper clips? He was using a ridiculous example of something... Yeah, but it's entirely ridiculous. There is no scientific merit in it. It is divorced 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 fucking paper clips and put it everywhere? It's just basically it's fantastic it's fantastical nonsense and it's science fiction in a in the worst way because he plays it off plausibly and calmly but i think we have a duty we have a 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 it's like i'm sorry i don't know what else to say other than um we do not understand what human consciousness, Senians, decision-making is. The fact that people are going to start saying in a few years that 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, you know, the AI pro is going, you're just like, you just can't accept that, um, the AI is smart. And I'm like, no, just stole my IP. Right.

Literally just stole my creation. And shall I still, shall 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, 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

acceptable for some eval, right? But what we're going to see is that my hope is that the way that we explore the developments of AIs 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 Penrose, and I think my collaborator, Sarah Walker, many 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.

Can you expand upon that, like when you say we don't know what it's doing? Yeah, 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 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 are a really wonderful time in our existence where we have all these tools, we have all this data, but 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 a 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 probability space, right? What has happened? You can look at probabilities.

Right. 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? use and possibilities. And until people will understand the difference between those two things, we'll keep, we'll keep confusing it.

How do you define the difference? Well, a possibility space is literally, well, it's something that hasn't happened yet. A probability space is something that's happened because I can't define a probability on something that hasn't happened yet. So what do I mean? If I take a die and I roll it, I know that I'm going to get one and six. I know it's happened before. I can train my own model on it, right?

I know what's happened. But I could create a dye in my head or, well, on paper probably more likely because I don't think, 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 to mislabel or to misunderstand what AI is actually doing. And I think that's kind of, you know, there's a lot of, you know, there's a lot of vested interest, a lot of money in saying, using, 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 not a rocket. It's extra nice rocket fuel. I mean, yeah, I mean, and everybody, like 99% of all, even most sciences 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 have not actually correctly assembled the problem statement,

all that PhDs do is assemble problem statements. That's why PhD, doing a PhD is so annoying. Some of my PhD students that work for me are like, why are you making me thinking 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, grade A student, and then you code to a PhD and you find it the most destabilizing thing in the world because I'm asking you to be creative in a space you might not have been used to or 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 the AIs are able to do this and they're not. The AIs are doing something really shallow. They can't identify anomalies looking at large data sets and finding a hole.

They absolutely can do that. But that's not the same thing. How is it not the same thing? So it's basically one is the inverse of the other. So the AIs are really good at, you can use the AI to say, take this data where I've already defined the experiment and find an anomaly within that experiment. That's great. I've already defined the experiment. What the AI can't do is actually define an entirely new set of experiments. They will always define experiments based upon what they know.

So the AIs 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 AIs 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 assembly theory calculator for molecules. Let's drederate a load of random molecules and join them together. And basically, it does a pretty good job. but uses some toolkits from the GitHub,

puts them together with a code and generally simulate and can generate molecules, right? And it looks cool. But obviously I'm having to, because I was like, oh no, it's generating my chemical knowledge. And I use my chemical knowledge. It was generating some absolutely bat-shit, 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 my taste, right? And it was like, how did you encode that? It's like, I could encode it, but I would be there all day.

but I'm just like, don't do that, don't do that, don't do that. It's a bit like, I feel like a music producer, actually. I just like, that didn'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 in the cooking with the AIs, right? You know, when the AI start to produce new theories, explain quantum gravity,

or come up with something that we could never conceive of, I will be looking out for that and go, oh, that's interesting. And adjust? Why is that AI doing that? Well, my assertion, let's make an assertion, it's August 26. As of today, silicon-based computers, as we know them,

are not able 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, all right, are you saying we could create something that right now is not something we are labeling AI effectively? Sure. Okay. 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.

Yeah. 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 chemist. I'm like, I need to create life in the lab before I can understand consciousness. 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 AI's. 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 superintelligence, all this stuff. We're all worrying about this thing. And science will actually, creative science will stall because the weaponization of science just produce outputs and papers will just go through the roof. And everyone will just use LLMs to write papers. They'll use LLMs to write the grants. We use LNMs to assess the grants. We use LNMs to assess the grants. And who's going to be the taste? Right. It's just going to be, it's just, 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 grant.

Well, that's a stretch from what he was saying, but I understand it. No, 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 it was all over, you know, we never, I think there's 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 out of create what we're created.

So what I'm excited about is what we'll be out of use the AIs to create help us create. Sorry, what we'll be out to use the AIs 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 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 newness that AIs do and try and explain why AIs can't do it in principle

and where there's an interesting gap. 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 what happens is that AIs can combine things together. But the way 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 almost the infinite, right? Possibilities.

Yes. And that's where creativity is on that wave. And then as soon as they find something, they chuck it back. And suddenly they go from that infinite edge to the finite encodable present. So I would love to put it in this way, is that AIs basically kind of predict the past. They're encoding at the present. And the interface between the present and the futures where the infinite is, is basically a continuous kind of substrate.

So when something is continuous, it's basically infinite. And so you can't, 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 I'm like, that's pretty shallow, mate. The AI could have found that. So what's going to have happened is like the AI is exposing that a lot of people

were 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 get and 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 not an accidental plagiarist but I'm like I have shallow ideas just a shallow thinker but occasionally just occasionally have a thought 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 artists, musicians, fashion, people just doing all sorts of weird stuff 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 have, 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 a novel 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 as imagining in that space imagination is non is not uncomputable because it's too big imagination is not uncomputable sorry Imagination is uncomputable. 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 human brain, imagination seems to be proof the human brain is doing stuff that is not computable, as in computable by a cheering machine, accounting machine, a labeling machine. So how are you going to build a brain then if it's something that's not even that that performs tasks 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 with it digitally. Okay. In English. I basically have I, well, I, 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 size of the space is too big. So there's something about the polymer brain that are they 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, um, into proper mathematics. How long have you been working on this? I mean, like probably quite a long time. I mean, and 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 said? Well, that's the next step. The next step is to build a brain jail. 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. Sorry, make a material where there is processes that can be encoded digitally but then become analog. So a bit like an oscillation. So on off, on off, TikTok, TikTok, clock. You code it digitally because you nudge it with a piece of electricity. And then it floats away on its own.

Exactly. And then you then read out what's happening later. And then I want to understand how that digital encoding and what readout are related. And is there 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 science. doing what we call molecular computing.

What's that? Well, they are using DNA. So DNA has four base pairs. And they can then connect those base pairs almost to like a computation. They can make a machine a bit like a what's called a chewing machine. It's basically another fancy way of saying a digital computer. And they can make a DNA computer. But I'm like...

A DNA computer. Yeah, they've did it. I mean, 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 that. That's what I would say. If I were funded by DARPA, I would say they don't have me. Sure. All right.

I mean, you know, I'll ask them to buy me a volcano at some point. Maybe. DARPA based in the Washington area. They're incredibly smart people. They have program managers that will, and it's all out in the public domain, right? DARPA has a series of program managers. They identify very interesting areas and they fund them. What DARPA does that's exceptional is they have exceptionally smart people who will then basically come up with an idea that, you know, if this could work, it would change the world.

And the internet changed the world, right? Self-driving cars. So DARPA has a self-driving car challenge where they had cars going through a desert and they will fall. it arguably accelerated a lot of the visual way of using vision and compute together to kind of navigate and robotics. So I mean, DARPA's great. So I don't want to put I don't want to burst the balloon of DARPA some kind of magic lab. No, I think it's a really fascinating place for sure. It's there's a lot of it that I think a lot of us don't know about them. We just hear about some of the wild projects they, they work on. Obviously, it's not 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, you know, hey, could you try to do this or actually how open end it 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 they, it's very collaborative, right? So they'll have a number of different performers, right, that would be funded. And we'd get together and share and pull stuff. Like, they're trying to push together the boundaries of science.

I mean, it's very successful. It's not mystical. The UK has got DARPA version as well 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, look, again, all these organizations, I mean, ARIA will also fund stuff in the US. It's the same way that DARPA has funded people. Oh, that's interesting. They fund where the best ideas are. I mean, obviously there's a certain amount of political kind of taxpayer accountability, right? As a taxpayer, do you want to give all your money to someone elsewhere and a different country? Well, if they're building something that's going to be of great use to you and you're the only country that can use it, then sure, right? Like, I think that makes sense.

Same with ARIA based in the UK. Of course, the majority of the funds are spent in the country, okay, 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 a 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. doesn't exist yet, right? And that imagine, that imagine thing has causal power, because you can imagine that thing and you can make it work. Right? And this is what entrepreneurs do all the time. Isn't it great that we have this like, oh, I'm going to make this widget. You know, might be a, 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. You can, 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 it from the show 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, where Elon's one else came up and said, you know what, we'll just make the rocket out of steel and we'll catch it. Because, you know, 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 when Lansdown will make it go subsonic, and by the time we catch it, we'll hear the sonic booms. I mean, they're like, what? It's nuts, yeah. Yeah. But it's now science fact.

And this is why humans are really good at fiction, right? Science fiction, you think about Jules Verne and all these 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 why we think that the entire world 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 unfalsifiable.

And if something is unfalsifiable. Yeah, we started talking about this last time, but got off that as well. How is it unfalsifiable that we're in a simulation? Well, where does a simulation exist in? You have an infinite regress. All right. What do you mean by that? Infinite regress?

Well, if I'm in a simulation. Great. The simulation has to exist somewhere. Let's imagine where. Let's say I exist in a computer somewhere. Where's that computer exists? Is it another simulation and a simulation and a simulation? So if I can't falsify, it's 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 it's not amenable to the scientific process. So if something is not amenable to the scientific method, then we don't have to talk about it. And so the thing about the simulation hypothesis is it is, it requires a commitment to a thing that is not ever falsifiable,

and therefore 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. It'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.

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's go back. No, no, no, no. Look, let's go back. Okay, we're in the universe. Who create the universe? Who do I believe created it? Well, no, no, we can say there's a creator, right? Or it's just this. 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 like a Lawrence Krauss guy that something came from nothing.

You believe it started from something. No, I mean, I don't believe. So a Lawrence Krauss guy is something. Look, I mean, I think there are some scientists who basically, again, that 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 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 it? Well, as it's not. I don't think it's possible. You don't think it's possible. I think, 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 an apple fell on the They could. They could. They started, they were throwing stuff at each other. They just didn't know how to falsify it. You know, the principle was always there. So what's, that seems like semantics to me? No, because we knew there was this thing called gravity and we understood that there was

a force. 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 assume there are certain things that exist, an ontology, right, or a metaphysics, right? And then we're going to basically then look at relationships with things within that metaphysics and ontology, and we put out layers. And those layers are 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. infinite regress, you can't make progress on that. And so what you do is you put that to aside and say, well, that is something that's out with the scientific method, not as defined 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 things like how do we cure cancer or, you know, why can't we live forever?

or can we go to Mars quickly using a fusion engine, right? These are far more interesting questions because we can affect them. And also, I mean, 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 if I build a robot to do something and then I build a simulation, I want to be able to verify. I need to think called verification. Now in AI world where the AIs are working really well, is 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. The idea came to me because I wanted to program my 3D printer to do chemistry and I want to make sure the 3D printed didn't catch fire. So then I built this programming language, but that allowed me to bake a digital twin of it so I can verify it 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, it doesn't catch fire, I'll do that. That's why simulation is so important. And that's why I think it's important for me to push back on this whole, you know, again, a nonsense idea of the simulate, we're a simulation.

Now, that doesn't mean to say, this is all mess with everyone's head, that one day we can't create a simulation where we can put digients inside. Where we can put what inside? So, I've got to read, Ted Chang. I thought you were going to say Terrence Howard. I was like, oh, shit, here we go. Ted Chang wrote a really great book called the Life Cycle, It's not the nicest name, not the sexiest name, the life cycle of software objects, I believe

the name of the book is. Ted Chang. Ted Chang. Fantastic writer. Is he still with us? Yeah. He's a fantastic thinker writer. He's an external faculty at Santa Fe Institute.

So I've met with him several times. Cool. Debated assembly through with him. And these digients are kind of real entities that live in a world. And you can manifest them in physical robots and so on. But it's not, you know, I can. imagine a world where I could create a sufficiently rich computational universe where I could create things that might appear sent in, which I could do tests on, where I would actually have to think

about small 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? How chemistry became biology, number 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 of 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 we have to apply the scientific method and real scrutiny to

it, you know, and that's why Bostrum, like, I feel like I'm really, I'm Bostrum hating. He's a really nice guy. Have you ever talked with him? I haven't, no, no, no. I mean, I think I've been at several meetings when he is there, but he's kind of, you know, I think I would probably just be too annoying. I would just be like, I would like, I don't know, I would make the Bostrum conflambulator. Confit, confabulator. Yeah, so this, it will be like a philosopher that just puts a 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 alternative universe, and it causes singularity in the entire world disappeared. 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 defy 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 just don't know if he went that for it. 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 allowed people to think there's this thing possible

called superintelligence. It's a bit like saying, we're going to go fast and speed a light, right? you can't go fast than speed of light. We know. Ever. It's the law of the universe, right? As you put energy into a mass and to accelerate it, it radiates radiation to stop you getting there. We do that in proton beams all the time at CERN. Right?

There's no, like the speed of light seems to be, you know, I mean, never say never, but 99.999.99%. 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 absolute. Because, you know, I have to have an open mind. But right now, 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, I don't know, put a sten 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 it up. You'll die. But actually, look at all statistics we did. Yeah, people do die. But that's part of the, but the fact is the probabilities of the past. Exactly.

The probability that you can survive with a stent in, if you've got some kind of constriction in your artery. It's like 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% sure, we're not going to go fast and speed of light. Because all the phenomenon that we showed that allowed us to build or our technology,

it means that when you accelerate objects towards the speed of light, they can't get there. Now, you said we when you referred to CERN. Are you involved with CERN at all? No. You're not. No, no. I mean, I've been to CERN. I was a TED talk at CERN. But I mean, CERN 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. What's the latest stuff they're working on over there?

I'm not a particle physicist, right? And I'm not particular. CERN is a great machine. It probably, the CERN is a great machine in terms of the, the media associated with CERN, the way they drum up interest. It's like this massive, it's a massive experiment and 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 basically used the, the certain and get the Higgs boson. Great. 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 any level of academia, but a 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.

Yeah, I think that's a legitimate question, right? And I think there's an argument to be said, to be say, look at any, scientific enterprise when you fund it, you get you get rewards froming out and then when the rewards tail off what you do, you'll probably kill it and start again, right? Create of destruction. So that happens a lot in science, but things, you know, it's not just CERN, right? 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 sequence the human genome. And then also Craig Venter, great pioneer, great entrepreneur, great kind of engineer, also basically started a company to beat them to do it, right? Because you wanted to own it, get the IP.

To justify it, we said, well, we're going to cure all a 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 diseased gene. There are some people, but young people and old people that have had a young people that mean born blind, or almost blind, where they've been able to correct protein by gene therapy and they can see. That's amazing.

There's also gene therapies where we're understanding how to 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. We'll have a combination of molecular and genomic therapies where we'll use small molecules. Do you think they already have them and they're just not giving them to people? No. 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 it for decades now. And it's brutal.

So, yeah, and the companies are getting there, right? It's, I think there, so no, there is, 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, a chemistry, there's lots of chemists doing medicinal chemistry going way back. Developments in biology are moving a pace, but the most critical problem is we have to translate those developments from the lab into the clinic. And people are hard and people die. Now, there is actually quite an interesting contrast in China and the US and the UK right now about how much regulation we have. And arguably, there are some clinical trials going faster in China because of different regulations in the UK and the US and Europe.

Now, is there an argument to say that there's not a conspiracy in the West, but we are much more, 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 conspiracies. 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 guardrails on it. I think there's something to be said for having guardrails on that for sure. Yeah, I mean, there was one very famous Chinese scientist who used gene therapy to edit some embryos that became humans. and caused a problem, right?

These people were not going to have such a good life as others. So he got put it to prison because he basically mis-edited the genome. Yeah, what did he do that they're not going to have as good enough? I mean, I can't remember the details. And I think it was something to do with HIV, 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, smart. Yeah, Chinese scientists who produced genetically altered babies sentenced to three years in jail, Hay, Jin Kui, and his two collaborators were found guilty of illegal medical practices. Let's see what they did.

The Chinese researcher who stunned the world last year by announcing he had helped produce genetically edited babies, has been found guilty of conducting illegal medical practices and sentenced to three years. A court in Shenzhen found that he and two collaborators forged ethical review documents and misled doctors into unknowingly implanting gene-edited embryos into two women, according to Jinwa, China's state-run press agency. One mother gave birth to twin girls in November 2018 and 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 to your prison sentence. The court heard the case in private to protect the personal. privacy of the individuals involved. The report says physical and documentary evidence and 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 Hurlbert at Stanford University, and then Deves 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 onto 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 becoming infected with HIV later in life. The technique could be used to reduce HIV-slash-age disease burden much of Africa. He argued were those infected often faced severe. your disruption, but like you said, they kept a private and corporate, obviously caused other

serious drawbacks. Yeah, yeah. I mean, I think that was completely the stupidest thing to do, right? Because HIV is pretty much now, I mean, horrible 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 to put it under control. And now we've got to a 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're at a point where you could actually suppress the presence of the virus. What an amazing accomplishment for human medical technology.

I think he just went one step too far. And okay, are we going to do gene editing 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 done it. But anyway, coming back to the Human Genome Project compared to CERN and pharmaceutical companies is that the human genome project was an incredible achievement. In the same way that, you know,

the use of CERN to find the exoson 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 that's just not going to happen. Something else is going to happen. The AI tools will help us cure some disease. They'll help us 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 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 sympathy.

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 say, hang on, can we just understand what's going on? And I have sympathy for the AI abundancies, 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 can 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, 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 will 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 normal, you want safety and you want security and you want bad people to not do bad things. You want them 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 basically cure disease, make things cooler, you know. And but what I think has happened is some of the. the AI people getting quite rich are saying, oh, money won't exist in 10 years. Yeah, I don't understand that argument at all. That doesn't make sense to me. It's just Elon 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, I listen to that a few times and I was like, what the fuck is the logic here? How does money, how does money not exist to where people are all just going to be the same, especially like that quickly? I think it's, so look, I'm not an economist. but I would say the following. Today, you're an economist. Money is a representation, an allocation of resource, right? Yes.

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 to 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 micro-processes you can buy that are just like 15 cents when it used to be many, many pounds, 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 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. There's a finite amount of physical resource. But there's an infinite amount of physical resource. But there's an infinite amount of possibility, which is really cool, because that infinite and power possibility, we're going

about 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 prejudge 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 titles have been astonished by their capability. I mean, think about it. Like, you can take these, you know, the thing I find fascinating is you can use Claude or ChatGBT

GPD to make a PowerPoint. It's pretty good. Yeah, no. It's, you can make apps with these things too. But the thing is, if you tell, 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 in garbage out?

It's 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 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, you know, a lot of them give me the ick, right? Like where it comes to writing, do I? Oh, yeah. Right? Do I, do you? Right? Do I, do, I use the AI just to write for me? It's 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, and I just love the way the AI is going. They're so, um, what's the word? I think semantically uniform. Semantically uniform.

I think there's basically, there's a, the AI is right in such a uniform way. Yes. You can see it. So it's, you know. And also it's kind of this, it's not it, this, it's that. It's not A, it's B. I'm just like, can please not write like that? Right. So what I do tend to use is I write and my writing is fairly flawed, but, but it's my, you do something flawed? My writing is my writing. I'm not the, I'm not the best trained English professional, but I write 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 to sound like this. This is my voice. Right. Exactly. So please don't do that. Thank you. It's very robotic. But what I have used, which I found quite fascinating, is I use the AIs now to look at all my paper proofs. Your paper proofs? So when I publish a paper and I've got the proofs, and I'm really bad, I'm very 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 PNAS just a few weeks ago on alien detection systems. Alien detection systems?

You can find it online. Yeah, I think assembly theory 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 of, and it went for a found like 10 typos I did not find. That's useful. Yeah, like it was like really typos. a human reading, it would find it annoying, right? And what I want to do is, there we go.

This is the paper in PNAS. Molecular Assembly is a universal biosignature measurable by mass spectrometry. Now, can you bring that from Japanese to English? Just to... Oh, okay, sorry, from English to English, yeah. So... That's a different kind of English that we speak here in Jersey, so... So what this paper does, it shows, 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 how can I measure the presence of a molecule on another planet and use a measuring device to tell me if that's produced by biology or not, an alien biology or an alien biology.

Meaning intelligent life. Not intelligent life, just any life. Evol. The 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 you go down, if you, scroll down, there's a great figure which my student made, because I used machine. Can I read the abstract before we scroll down? Yeah, yeah, sure. Let's go back up to the abstract. Or the significant statement.

What you want. Which one do you like better? Significance or abstract? Read the abstract. Let's read the abstract. So detecting life beyond Earth requires biosignatures that do not depend on the chemistry of known organisms. Molecular Assembly, M.A., derived from assembly theory, which to be clear, you've 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 than baseline methods. Simulated multi-stage data reveal that small instrumental 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 the instrumental effects offering a scalable route to life detection on future planet mission. So, Deve, let's go down to where Lee wanted to expand upon this with the, with the graph. I just like the picture with a, 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 learning to 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 We know things alive or dead. We know it. 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 is 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 living systems uniquely make molecules with many different parts, right? And in high copy number. So we can measure that. So we've made, it's the 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 it basically fires a molecule into a vacuum, electric field, and just measures how much, how heavy it is. And then it hits it, you 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

that 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 this paper is the next step to say, well, hey, not only does it work, we can now put it onto mass spectrometers. There's 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 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'm 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? Yeah. You can. So there's a paper that's going to be coming out soon where we can use assembly theory to detect, to measure the probability for life on an exoplanet, for sure. Now, whether it will 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, yeah. I've mentioned it to David Kipping. What does he say? He's excited. I mean, he's an enthusiast for this type of stuff.

I think that the problem is, not with David Kipping, but just the exoplanet world in general, is they're very used to 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 to know the difference between life and death, whereas the system that we've built using assembly theory is able to kind of fingerprint these gases in a way. 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. Does that mean it's life or not? No, because a geological process could be producing methane. Oxygen has been detected on exo, 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 get it by just breaking water down in UV light, right? So the question is, how can you infer the presence of biology or evolution using gases?

and the answer is going to be assembly 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 don't combine them together.

So all I'll say for now, because again, it's, you know, has to be peer-reviewed. And I do many things. But presenting scientific findings before they're being peer reviewed as if they're accepted findings is a trap one doesn't want to fall into. 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. It's a bit like MRI, right, but four molecules. And the third one is called infrared, using infrared spectroscopy and light. Now, how would that work? So you just look at the number of different colors. So the more complex molecule, the more colors it has, right? And so conceivably you could imagine exoplanets having molecules, lots of different colors. Sure.

Now, are aliens something you thought about, like as a kid just as an idea a lot? Like, man, there's got to be life out there. I wonder what it looks like. I mean, as a kid, I mean, what 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 take this thing apart?

I mean, but I think obviously now understanding what life is, I think is really critical. Understand the phenomena of life on Earth is going to for sure tell us about aliens. How so? Can you explain that? Well, what is life as a phenomenon, right? as a chemical phenomena and then if we understand how how

odd is it is Earth that has life right and how rare might life be in the universe is kind of related so if we can work out the process that gives rise

that gave rise to life on earth we should be understand something about the process that could give right to life in the universe let me let me give you an analogy Let's just imagine when we looked up in the sky at night, we did not see anything except during the day saw our sun

because there were no other light getting to us. We just see it's black. We would obsess about the sun, right? How did the sun get created? We know the sun is created by the collapse of hydrogen. And what happens is hydrogen collapses to go to its own gravity and the point at which the gravity is dragging all the hydrogen together. What happens when gravity pulls the hydrogen together?

gets hotter. So there's a point where it gets so hot, it's enough to overcome a strong nuclear force and then it start undergoing fusion. And then when it undergoes fusion, if the gravity is enough, it doesn't blow apart. It kind of self-regulates, right? Because some stars could just blow apart. So that phenomena that gives rise to the sun is gravity. Now let's look in the, 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, right? Well, not all the time. I don't know what the frequency of supernova is.

And maybe one a month, one a day. I don't know. We'll accept it. So you can see them. So we only have an N of 1 for life on Earth. So if we can start to understand how lightly we think it is chemically that life emerged on Earth, we can start to bound the probabilities. So as you...

I'm sorry, how can we do that if we don't even understand how? 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 a spec we are?

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. Oh, all right. Now I understand what you mean.

All right, fine. Let's just look at the universe for a second. 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 will never have life on them, A biotic, but have the possibility for life.

Number two. Number three, are alive. They're just living. There's stuff everywhere. Living and technological, i.e. there's intelligence there. So there's technology there. And post-biology or post-lifology, because it's a biology is unique to Earth. And there's just technology on there.

So it's kind of outgrowing it. But arguably... Just technology on there. It's like robots and stuff. I don't know. I just made that 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 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? Right. But actually, I thought of an idea actually listening to David Kipping's podcast. He has the cool world's podcast, is that right? So I was listening to that and they were going on about the habitable zone.

They realized they were wrong. I realized that living planets can modify the Goldilocks zone. Okay. Can you please explain that? Yeah. So planet Earth starts to, after the late heavy bombardment where there's just lots of that, it starts to cool down. and the atmosphere is being filled, there will be feedback processes

whereby the planet will probably attempt to regulate its own temperature. So it's a bit like the Gaia hypothesis from James Lovelock. Okay. But I realize that actually, if life starts to form on a planet, and within that zone of, within that zone of life support, if you like, for that biology,

it's like temperature and pressure and whatnot, If the planet starts to drift outside of that, evolution will start to kill stuff. And the stuff will start to respond to go, no, I don't want to die. I will counter that. So like a thermostat. Yeah, rebalance it. Yep.

So I think the planets might even lock into a biological or lithological, I just made the word up again, framework where it self-regulates. The planet itself. Yeah. So the planet is able to basically self-regulate for the emergence of life. Okay, let me play it. 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-in-Challenge, maybe, we'll go back to that at the moment, brings up one of my favorite Chinese sci-fi movies, Wondering Earth. The Wondering Earth?

It's a brilliant movie. Okay. They basically, the Earth is going to be engulfed by the sun. So they're like... Deep, you don't know that one? Wondering Earth. There's two, there's also Wandering Earth, too. Okay.

Come on. 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 like... Oh, they're cooking on sci-fi.

Brilliant. Wow. Absolutely fantastic movie. Anyway, and that's the excuse where intelligent life was like, well, we need to get away from Earth, 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 batch of it movie. It's awesome. But no.

So let's talk about it. 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. That's right. I'll be at a regulate the pressure and the temperature, the atmosphere. So wouldn't it be great if like, oh, it's 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, 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 even, I think it's a good idea. I've just never thought of it that way, thinking with Earth, like, the Earth itself as like a, has its own brain as an organist.

I mean, like, everyone's like climate change in 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 urbanized around, you know, around the coast. and around the equator where the zone was quite right for agriculture, but Siberia is going to become really fucking habitable. Right?

They got to get some new prisons, I guess. I mean, Siberia is like, but on the time scale of a few hundred years, I would be buying real estate in Siberia. It's going to be great. All right. So people don't really understand. It's like we're kind of like, oh, doomsday climate change. No, annoying because people are going to die from heat, you know,

from overheating, for lack of water, having to shift and migration, that's really bad. We'll probably come up to technological solutions to climate change. But the planet is a pretty big organism is wrong word, but it's a pretty big able to kind of respond. So I think, again, looking at these planets 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. Maybe Earth is going to survive longer than otherwise would have because it produced life. That's right. Wow. I mean, that would be so cool. I mean, I think we're looking at life all wrong. And, you know, and actually, this is one thing that

Elon says. I mean, Elon says such a creative thing. But look, if your son needs to lose masks so it doesn't explain 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? I don't know, just make a vacuum cleaner. How hard is that? I mean, over a billion years, so look, over the next five billion years, the sun is going to get larger, 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 more helium, and it's going to get more and 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. And 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. Just find a desert. If you have two billion years notice and you want to, and you want to, 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 with 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, 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 a podcast together. He's coming back in in November. We're going to do one, but maybe next year. year. Because he's here. Like, he's in town. We can make that happen pretty easily. I didn't realize

you chat with him. I guess. Make them sound amazing. 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, nah, nah. No, I need you to say that to him and the two of you go back to the port. 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, you know, he's just, you know, he's just, 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 that actually end up being right. But right now we can't prove that. So I'm here. He's very diplomatic about it. Yeah, yeah, he's a warrior. He's a warrior. A warrior or a warrior? Well, I mean, a war, I don't, he might be a warrior.

Okay, the accent's killing me right now. But he's a warrior. And I think that, yeah, it's kind of, he worries a lot. But that's okay. Everyone, everyone does it differently. They all do it differently. I like to be more provocative and not worry because then you can really, I think for science to accelerate sometimes you need to annoy each other. Yes.

Because 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, it's like, what the fuck is that? You're completely unafraid to bring out the fist.

and be like, stop, stop the shit. 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 then also you need to be willing to be wrong, okay? And then the other thing is you need to critical thinking, real-time critical thinking requires, 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 ASICs that aren't used just with zero and five volts? Are there variations?

Can we make neuromorphic computers? That'd be great because I'll buy one and play with it. I wouldn't have to make a plug a, you know, a girkin into the mains, right? And so I think that having new ideas and being out or challenge those ideas almost like in a sandbox, right, or whatever in your mind, imagine them, and then create new things. things is 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 the only thing I'll say on it, before we can talk more about assembly theory is that something did happen, open AI did, they basically hit upon a cognitive treasure trove when they train their model, and suddenly these chatbots started to be really good. at predicting the next token. And as you increase the context window, got even better. And then when you basically built kind of guard rails

or chain-a-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, then-da-da-da. And then you checked everything, fact-checked within. And suddenly these tools became incredibly powerful.

But for me, it's like, me, 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 were 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 demysticize 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 AIs are because this is where humans will,

you know, until we understand how, what life is, create new brains and things. Humans still have a job. And maybe there is an argument for kind of saying, well, there are some silly things we can automate. You know, my company, I have this company that...

Chemify. Chemify. And Chemify's got a few hundred people in it now. Oh, wow. And I was at a meeting where a lot of people were saying, well, you know, I've been able to shed 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 getting rid of people

because 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 given 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, 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 of that possibility. I mean, so I do, I find the whole job displacement there rather distasteful. But I also do find the fact that, you know, in our, in the world, in any organization, you've got a, you know, I'm in 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 this thing as we go. I mean, Chemify's aim is to build a world model for chemistry. What is that as Ligon 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 is because and it's called Genesis on purpose. The world model. Is that what you 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 a hypothesis. S, make, test. So the idea is that Genesis is about the fact that people think that drug discovery is discovering a molecule. This is actually the answer to creativity and novelty. It is?

In AI. Yeah, this is why 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, 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 has said that chemical space is about 10 to the power of 60, right?

Okay. So that means for drugs. 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 at the power of 60. It's 10 at 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 put, I don't know what you would put on there for it. It's like size of chemical space, croninan, X archive or something. You might find it. Size of chemical space. Yeah.

Yeah. So you showed the work. My high school math teacher would be a proud. Yeah. Is that it? Allucidating the size of chemical space with assembly theory. Yeah. Okay.

Wow. So we looked at the number of steps you would take. So basically, if you allowed your molecule to have, I think, 25 steps, if you click on the PDF or go up in the right hand talk corner, I think it is. Yeah. There's a go. And I think if you go down at the table, there's a table. I didn't rip thing like everyone on a chemo-chemo-famatics 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 trumpet. Right there. 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, Lee. 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 the way to the front. I'm at the point where I'm ready to. There we go. There's a table there. I was going to take your word for it. 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 random walk and you take 25 different steps with the chemistry that's available, there's 10 to the power 117 molecules accessible, right? Now, there are some duplicates. And 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, you really have to generate something new, right? Or novel. So that's where Genesis comes from.

If it's just searching, it'll be like a search engine. So that's why, basically, 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... So not a catalog, not a synthesis, sore, not a retrosynthesis.

It's a computation, one executable loot wired to real chemoform capacity, ideas to verified matter. 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 hallucination. I loved it. I was ab testing it with a friend.

There's like this chemical hallucinations is that's hard. I made it. And then everyone was like, oh, your market wouldn't like it. And at least, 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 at the end one now, the meta, right, because I like the meta, because computation is, uh,

no, the, we're drowning in metamolecular. So the chemistry of, the future of chemistry is making the meta physical. Right? You know, You know, people say, oh, that's meta.

Yeah. Come on hard. The joke isn't that high brow. That's metaphysical. But now, let's make the meta physical. Okay. You're like, get a new job leap. Yeah, I don't know if that was just funny as you'd, you know. You got a good sense of humor. I just don't know if that was your type of. Anyway, 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 there's something if the space is too big to search. You can can only create. And that's kind of weird. And that's the same thing of 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. They 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 out of my simulation. Like, oh, great, have you, have you got it working? I'm like, oh, no, we haven't made it. I'm like, well, that's just bullshit then. So basically, I realize, because what Chemify has been doing is making molecules, in the hard world for hard chemists. And then you've 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 connect our AI to your engine and we can have a dual AI and we're just, yes. And so what we're doing now is like Genesis is a forward deployed kind of chemify engineer that connects people who buy it so they can just use it. They keep their IP. But anyway, I won't sell the company on your podcast.

It's just. No, you can sell it all there. why you're here. Raised a lot of money too. Employing a lot of people too. I like that. I mean, we haven't raised, you know, I kind of sad, like I'm such a bad fundraiser, right? Such a bad, you raised 70 millies since the last time you were 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? Yeah, that's all right. But then one of my friends were saying to me is that comparison is a FIFA joy. That's right. When you were, were you like into art when you were growing up?

No, I'm in a lot now, though. 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 sculpting from one slab of marble.

It's a very, very similar, if not the same wavelength. Yeah, yeah. You ever thought about that? I think so. I mean, I think there is a certain amount of... Because, look, genuine creativity can't just emerge from you applying some rules. Yeah. Right?

I was... And I think there is something to be said for how to create... You know, I'm very interestingly how Genesis works. It's going to work. And the nice thing is, I've built this Cammy Farm in Glasgow. And I just connect... I'm just going to... It's like, think of it when Nvidia built...

first H-100s and put them into racks, that'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 invented much faster because of this. So all pharma, all batteries, all catalyst companies, anyone who deals with chemistry will need it.

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 were great partners kept giving me molecules

that were too hard to make because you think about it, chemify's library do you want do you want to know how big chemifies virtual library and molecules make? How big? 10 to the power of 40.

That's large. That seems big but actually but actual chemical space is about 10 to 117. Yeah. So when everyone comes to me go, can you make this

and we're like, shit. Can you make that? Shit. Baby steps. We're like, make anything. Can you just, can you instead, rather than you 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 compute, 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 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 117. You're always going to fail. But 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 biobank. 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 most valuable engine for chemistry ever. And that's cool, because that gives them retention on their own stuff. They keep to hot. So basically, then Chemify gets faster at making, doing chemistry, but no one ever knows what they're doing. That's right. It's completely encrypted and segregated forever.

Wow. And that's the way the UK Biobank does it. Because what you want to be able to do, the way the Biobank works in the UK is like, 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 biobank. We're going to put your data into the biobank. You're like, oh, no, I don't want people to know. I don't want my insurance company to know. And they're like, no, no, what we do is 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 engineered. 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 launderer, but no. I think I'm cooking. I think so I works, you can, no, but sure. Okay. All right, real quick.

I got to 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 the abilities that humans are able to leverage now to be able to figure things out at such an exponential rate, do you ever worry about the incoming abilities of us to potentially start playing God on some things? No, I want to play God.

In fact, I love playing 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 robot. 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. Well, I think, no, I think playing God, if you like, is taking any scientific, what was it? Was it Isaac Asimov that said, you know, when any scientific. Distinguishable magic. Yeah, so when

science can do that, science does it a lot. Imagine going back in time with a fully working mobile phone satellite system. everyone 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. 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 we're doing that.

I mean, by any measure, human beings have never had a better time on planet Earth. Ignore polarized social media. It says we're all doomed. And it's like, yes, there's climate change. You know what? We're going to fix that. It's not going to be that hard at the end of day. We'll shove a load of sulfate in the atmosphere.

here and we might get it wrong and it overcool and 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 it, we're burning all this fossil fuel. Most of the fossil fuel were burning is to create fossil height, 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 than 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 going to starve to death? Tell me which half of the population are you going to 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,

unforeseen, then do the calculation. But what about like the genetic engineering and where that ends? We're genetically engineering rice right now. In fact, if it wasn't- 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 guys are 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 there's, I forget what the disease is called,

but there's this disease that's effectively called like 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, like 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 start to go. No, I'd love a clone. I don't have enough hours in a day, as you pointed out earlier. I'm just joking. Look, I think that society, so one of the things that I'm, 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 this, behind all this stuff. She is supportive.

So George Church needs to get out more, I think. Needs it. Why do you say that? Well, because he, he, he's, I'm not going to. I mean, that's a big statement. George is lovely. He's just very mischievous.

Let's put it that way. He's very mischievous. Yeah. What do you mean by that? He basically likes, the same way I like a fuck around with chemistry, he likes to fuck around with biology. Uh-huh. And I think, you know, is he a bad person doing it?

No, for sure not. He's 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, 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 can genetically engineer high IQ humans. Would you do it? this gets weird this is what I mean

I know what the answer is I mean I think I mean well I don't know what the answer is the answer is society will 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.

But a few hundred years ago, it probably wouldn't be unacceptable, right? 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 party? I don't know, right? Engineering critical thinking into humanity. Is that a good thing?

I don't know. Actually, maybe just scrub that from the podcast. It's just, it's just, it's, no, I don't want to go there. I see what you're saying. I think it's just, it's, 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, Like, yeah, let's give them all 18-inch dicks, too. It gets weird. Yeah, you said that, not me. I would scrub this entire section.

No, it's good. Okay. I don't like scrubbing stuff at all. We've got to 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 society needs to decide.

I'm very comfortable with certain technologies have today, like mobile phones, cesarian section, if we can engineer certain favorable attributes for humans genetically, should we do it. You know, 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 was 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 a kind of muscular, I'm not sure, it's muscular dystrophy. Basically, the child is not going to live for very long. Now, what they did

is they said, right, but the couple want to have children, but the mother is never going to be out of 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 all the other characteristics from 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 completely worthwhile. Right? On the surface, it's hard to argue with that. Yeah. Well, no. I mean, sorry, if I, if I came sentient and I. 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 Wally Mammoth and all the other people doing 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, no, no, 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. You know, if someone could actually get a resurrected to your ex, I would want to pay for that. It would be great.

Okay. That would be awesome. If it's on a leash. But the probability of it be impossible, I don't know. Look, 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 supercharge that, you can give rise to super- athletes that could just be like the Russian Olympic team but they have no steroids that's already got it but you know isn't isn't that in a way kind of interesting again but then do we start having like 12 foot giants walking we do have 12 foot giants have you try I mean well we have six or seven foot giants I was going to say I was unaware of these 12 footers please please do disclose you said that real confident yeah whatever like Yeah. Okay. No. But I'm saying we do have natural biological capability. 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 to a mountain nourishment, we didn't achieve that genetic destiny, right? People were short. Then you've looked at the Netherlands now. Everyone's like six foot, whatever, It's kind of interesting.

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, or the computers. Could people just get these robots, get this technology away from Chemify and mass manufacture bad stuff? Well, you know, what I've done is I build encryption into the system and actually GPS, they will have, in the end, GPS geolocated licenses. Do you have 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 if it got it in the wrong hands? I think that's a rather simplistic way of saying, is there a way of making sure that, I mean,

right now Chemify builds its own robots to do stuff internally and no one would be out of 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? Yeah. 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 biohack or chemical hack,

and they're going to end up injuring themselves, right? It was really bad. No one's using any of my technology for that. Right. But, well, no, actually, I am not. There's nothing stopping people taking my papers off the web and using 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 they fail to safety. So for sure. And 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, 100 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 100 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 the planet, planet Earth? How many chemists are there doing reactions every day? It's less than a million and probably more than 100,000. That's not a lot. I think one of the ways why AI and physical AI, it's called Chemify in a way, will be positive for the US in particular, is like the healthcare system is a bit

annoying just now. Oh yeah. But think about it like this. In the future, the birth rate is going down. So 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 health care, subscription, and they have more productive lives and then make more money and have good fun and do whatever, drive the economy. Suddenly you've got this economy that inflates, not because like the asymmetry.

That's natural. It's natural. It's kind of amazing, right? 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 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 sun 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 place where capitalism is really 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.

Oh, right, yeah, yeah. Because maybe that's me being slightly too kind of weird, right? And all the rich people will say that's not right. No, I think it's a fair point. I think there's almost been like a socialized capitalism. Yeah. That's formed for sure in the upper classes. Which is kind of weird.

Yeah, it's very weird. But I'm hoping that that will revert. I mean, the UK is like in the is in the doldrums, right? Everyone's miserable in the UK in 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 that in France, in Switzerland and Germany, they were coming up.

Not quite as good as the US, but in, but, or not, sorry, good is a wrong word, not quite the same number, but I think there's a lot of interesting things happening because people 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 didn't want to be entrepreneur I kind of became one by accident well here you are yeah well it's working out for you they're you know the working out it's not about the money it's about the the ability to appropriate appropriate sorry yeah what's the right word appropriate's wrong word um it's about allocate that thank you it's about allocating resource right I mean when

When KMFI becomes a trillion-dollar company, I will be out of allocate resource to helping cure disease solve the origin of life. Yeah, it takes on a whole new life of its own. Yeah, I mean, that's... As long as Dr. James Tours not, you know, right and you're wrong. Dr. James Taw. What is 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. Oh, I... What was his argument against yours? I don't... I mean, James is a complicated person. He's a... He's a, he's a, he's a born-again Christian who is a chemistry professor. But he's a kind of, 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? But I do believe that we'll solve it and it's not just, you know. You think we'll be able to create a cell. 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, that and the other. But look, Dr. James Tor is a chemist. I wouldn't say Dr. James Corp 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 it have to do with the way you're defining following the scientific method to ask questions versus something you have faith in? I would say that James basically does chemistry. He's very good at chemistry. And he uses that authority to exert authority over his belief system. I got it. I got you. Whereas I'm like, I'm clueless. He says, you know, clueless. You're 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 the word. clueless because that just sounds silly. But I do science, why would I do experiments if I knew the answer already? So you look at him as more dogmatic and like, it's harder for us to change,

whereas you're like, we got to put a lot of shit against the wall. I mean, I think so, so I mean, I'm the only person that will debate him. And I don't know what the origin of life 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, give my views as flawed as they are, but it starts a debate, right? I don't think, you know, people come to me and say, are you the authority on this? 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 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 contact me and said, would you come on? 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. I went. I thought, what can go wrong is he could rant at me and I could just go, you know. Yeah, I thought it was pretty civil. He, I mean, he's pretty ranty. And I was just like, I'm not going to argue. I'm not going to. I'm not going to, I'm not going to, I'm not going to descend into ad honorman.

I just want 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, you know, he has a religious commitment. He also thinks that aliens must exist. He's like, he has a huge following. He asks sensible questions, you know, and 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 I did it. And one of my kids watched it and was like, this is the first time I've heard you ever talk about something and I understand it. And I was like, 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? That's right.

Because I've talked. You know, my sons are really smart. And I talk to them all the time. And the guy was like, one of my sons was like, I have no clue what he talked 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, okay, great, it's worth 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 an 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 Lee. We're going to have to do this again. Let's go get some steak though now.

All right. Thanks to be with you. And yeah, until next time. All right. Everybody else, you know what it is. Give it a thought. Get back to me. Peace.

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