Where Does Genius Come From? | Michael Levin

In the last couple of years, we've made novel living beings that have never been here before. So xenobots and anthrobots, these are these are novel creatures that have never been on Earth before. They're made of living cells, but... Or frog and human in in 1 case and the other. Adult human cells.

We are living through an unprecedented moment in human history. Neuroscience, the science of consciousness, and artificial intelligence are all converging, and everything is moving faster than most people even realize. On this show, I sit down with the scientists, philosophers, and technologists working at the frontier, the people whose work is actively deciding what we could become as a species. Too much of that work is happening out of public view. I want to bring the frontier into the open, sort out what's real from what's hype, and what it all means for the future of human potential.

I'm Doctor. Scott Barry Kaufman, and welcome to the Human Potential Potential Lab. Michael, Evan, thanks so much for being on podcast today.

Yeah, thanks for having me. It's good to see you.

Good to see you too. I'm very excited to talk to you. I've wanted to talk to you for a while, and I understand in this limited time, I can't ask you the million questions that I put on paper, so I thought we would just dive in and treat this as a little bit of a collaboration in a way between my life's work and your life's work. How does that sound?

Sounds great. Yeah. Yeah. Tell me tell me about it.

Awesome. Well, I've spent my entire career trying to appreciate different kinds of human minds and not trying to condense intelligence on a single spectrum, the g factor or general intelligence. And you've spent your career trying to illustrate how there's minds everywhere, even across species, not even within humans, but across species. And I was wondering, kind of thinking about intelligence, how do you define intelligence, and are you also equally as resistant as I am to measuring intelligence on a single spectrum?

Well, I'm not going to claim that I have 1 definition that captures everything that we want to know about intelligence, but for the purposes of our experimental approach, define it as competency in reaching... Basically in problem solving. I focus on the problem solving aspect and and degrees of of ingenuity in reaching one's goals as circumstances change. So we look at a wide variety of systems, not even just, when, you know, you say species, but but we look far beyond the living things, and we we look at cells and molecular networks and slime molds and inorganic materials and populations of... I mean, also sorts of different things.

And we look at different ways in which they they solve problems and they achieve their goals in navigating some kind of problem space. So I don't think this is everything. This doesn't capture play and exploration and the some other things you wanted, but but for for our purposes, it's it's plenty.

Wonderful. So does it have to be a cybernetic system in order to, produce intelligence? Would you say that goals have to be related?

Well, I I... I'm I'm open to the idea that there are other forms of intelligence that have nothing to do with with pursuit of goals. So so for example, exploration, creativity, play, those kinds of things. Right? That's that's great.

I'm sure those are those are very important. Those are harder to quantify. And so for us, because because, you know, we we we already have a fundamental problem, which is that people are very resistant to study and to find intelligence in unfamiliar substrates. So if if I start getting into things that we can't quantify in an objective way, then it becomes very difficult to convince anybody that we're doing more than some sort of, you know, wishful thinking or or or, you know, some sort of animist approach where you just sort of paint a spirit on every rock and and and so on. So so we try to...

Just just for the experimental work, we try to stick to things that that are that are easier. Still not easy, but but easier to quantify, which is goal directedness. But but, no, I don't think that captures everything of of interest, of course.

Cool. How would you describe yourself? I know you've described yourself as a natural philosopher. What... If you're speaking to a 10 year old who said, what do you do, Michael Levin?

What would you say?

Well, what do I actually do? I try to do research on things that interest me. So so deep deep questions that... About life and mind and and and meaning and things like that. I try to figure out ways to ask nature about those things and to do experiments and then try to interpret the answers in some way that allows all of us to have a better life.

I think that's that's what we do.

Yeah. Your defined intelligence, and and I I find your definition of intelligence, I guess it ties back to William James and the way that he thought about it a lot, the founder of my field of psychology. What would you say doesn't count as intelligence? Like, where do you put the boundaries? Like, what would you look at and say, okay, that doesn't have a mind?

The 1st thing I would say is that all of these things are empirical questions. In other words, I don't think you can answer any of this sitting in an armchair. So people often say, well, that's just a whatever. It can't. And I say, have you done the experiment?

Do you do you know it can't? And so and so the 1st thing I would insist on is that whatever we say about this is the result of experiment that you tried and, to the whatever extent that... And, of course, intelligence is, I think, a 2 way IQ test, so it's very easy to to give something a low score of intelligence because we're not smart enough, we're not creative enough to know what it's doing. So we have to be very humble about those things. The only 2 things I've...

I insist on strongly is that 1 is that it's an empirical fact that we try to discover, and 2, that it's a spectrum. I don't think it's a it's a yes, it is intelligent versus it isn't. I think the question is what kind and how much, and I agree with you that I don't think any 1 particular metric is gonna be sufficient. I think probably it will be a a, you know, some sort of a complex descriptor. But we can ask the question, does it go all the way down?

In other words, in this in this spectrum, what's a 0? You know? What what earns a 0 on that spectrum? And if we if we wanna think about that, I would say there are 2 criteria for being on the spectrum in the 1st place. The 1st criterion, I think, is that you have to have some degree of, goal directedness.

So simple homeostatic kinds of properties where we can identify some kind of state that the the system is working to achieve. That's a. And b, another thing that's good to be on that on that spectrum is that the information you need in order to meaningfully relate to that system, for example, to know what it's gonna do next or to communicate with it or or whatever, that information goes beyond adding up the immediate pushes and pulls on that system right now. So so if you know exactly what's gonna happen just by figure... By by adding up everything that's happening to it, you're looking at a billiard ball of some sort, and most of the tools of of behavioral and cognitive science are not gonna be of of use to you.

And and we quantify that with this notion of a cognitive light cone. So the cognitive light cone I define as the size of the biggest goal state that you can pursue. So we're talking about the amount of space, but also amount of time going backwards and forwards that's relevant to the actions that you're taking. And if it's... And if that if that horizon acoustics is extremely short, you were probably not dealing with us with a significant intelligence.

And then and then it's just an experimental question of all the tools that we have for dealing with intelligent systems, how many of those tools are are applicable? So if we take that definition, if we say those are 2 simple things, the minimal things that you need to be on the spectrum, then we can say, is there anything in our universe that doesn't meet those criteria? And I actually think that, you know, if you even look at simple particles, you know, subatomic particles, I think least action laws give you something akin to, goal directedness. So error minimization goal directedness, that kind of a thing. And certain kinds of...

And and I'm no physicist by any means, but my my understanding of of what we've learned about the quantum world in the last however many decades is that you also have situations that where, traditional billiard ball of causation fails, where you simply cannot figure out what the system is going to do by adding up all the local pushes and pulls. You know, randomness is not a high level of intelligence. We don't wanna be random. We wanna be intentional. But nevertheless, I don't think it's 0.

I asked Chris Fields, Juan Sousa, who is a physicist in my center, I said, does... Is there... Can you imagine a universe in which there was no least action laws? And he said, well, only if nothing ever happens. So presumably, are static worlds that that are at 0, but I don't think that's our world.

So I would say that in our universe, it probably does go all the way down to some extent, but the degree to which the tools of behavioral science are helpful to you are... You know, rise sharply as you enter the biological world and so on, and they're sort of moderate use. Not 0, but but moderate use below that.

That's really helpful. How do you see the difference between intelligence and consciousness? I I, been trying to read your papers to kinda see where you draw the lines, but I... I've been having trouble seeing that.

I hope you haven't seen me drawing any lines because I... Because if you don't try... I hate drawing lines. I I think draw lines... We draw lines and then we...

You know, where things are convenient for us, and then we sort of start to believe that these are real lines. Now the thing is, I don't say much about consciousness, yet. I I will, but, but I haven't said much about consciousness yet at all. And I... And and partly it's because I think it's a...

It's an entire... It's related, but an entirely different kind of question than than than intelligence. Because intelligence

I agree. I agree.

Do you agree? Yeah. Intelligence and other behavioral competencies are good 3rd person observables that we can all agree on the experiment. We can all agree on the outcome, and they they should be, you know, standard standard kinds of science. Questions of consciousness, I think, are different, and we could talk about what I think it means.

But I think many people who say they're working on consciousness are really working on behavior or physiology. They're not actually working on consciousness. They... It's very difficult to work on consciousness. I suspect that degree of consciousness, tracks intelligence to some extent, but I don't think they're the same thing.

I don't think that they're necessarily tied, you know, sort of in a in a 1 to 1 kind of relationship. And I'm overall very suspicious of what people call unconscious processes, whether in the body or outside of the body for the reason that that they're all calibrated against human verbal reports. And that's an n of 1. And when somebody says, okay, you know, whether it's subliminal reading or whatever it is, well, that was an unconscious process. I say, how do you know?

Well, I asked the subject, then he said he has no no recollection of it. Great. You talk to the part of the being that has access to language, and that part didn't... Wasn't conscious of it. Cool.

But how about all the other stuff? And I, that's within our bodies and our brains. And I suspect, I think the same, the same goes goes for, for example, anesthesia. So, so I was having a discussion with somebody who said, well, I anesthetize the patient. And my feeling is, well, you anesthetize the 1 with the language and the wallet who who may or may not sue you afterwards.

So so that's great. So so he was anesthetized. But how about all of the other potential minds in that in that system that don't have access to the language and that you... We don't have... This is why 1 of the reasons we're doing in our lab is building tools to communicate with cells and tissues and and molecular networks, all kinds of weird stuff, because I think we have a massive degree of mind blindness and mostly because we're fixated on language, and we are fixated on this idea that there's 1 individual inside a human body.

And as long as we we talk to the sort of left hemisphere, then then we're good. We... We're we're getting we're getting the the direct story, and I'm I'm very suspicious of that.

All your points are so well taken, and in a way, I would say consistent with the way I think about intelligence and why we need to move beyond IQ as the main marker of intelligence, because we found that statistical pattern learning at the level of, beneath the level of awareness, if you wanna call that unconscious, whatever you wanna call it, all I know is verbal reports, they're like, I had no idea I was learning this pattern. And we had some pretty complex statistical patterns that would overload working memory capacity completely. We found it was correlated with IQ test performance 0, and that was exciting to me because researchers have trouble finding anything that's not correlated with the G factor, general intelligence. So whatever this is or whatever we wanna call it, it is something that, a learning capacity that we evolve that is operating independently of the working memory system. How would you can sort of conceptualize what that is or what kind of intelligence that is?

Yeah. I mean, just, you know, in the context of the things that we study, so we study problem solving memory, learning, decision making, goal directed navigation, starting from molecular networks, cells, tissues, organs. So as far as I'm concerned, the the biological body is already an ecosystem of an immense number of different intelligences who all project their competencies in different spaces. So for example, we're all used to brains solving problems three-dimensional space, so using muscles to move animals around in 3 d space. And now as humans, we like linguistic space and maybe chess space and things like that.

But but but but those are, you know, those are the kinds of spaces that that that we've learned to recognize intelligence in. But looks... Cells and molecular networks and things have been navigating other spaces long before any of that stuff evolved. And and in fact, I would make the argument based on evolutionary homology that, all of the tricks that brains use are basically speed speed ups and and expansions of the cognitive glycoon and then projection into new spaces of tricks that evolution and and probably even before evolution, other aspects have been using long before brains and muscles appear. So we see cells navigating 20,000 dimensional transcriptional spaces to solve new problems that they've never seen before.

We see metabolic spaces, physiological spaces, but the scale of these things makes it hard for humans to recognize them. They can be very small or very slow or very fast or, you know, like, large and and so on. It's very hard for us. I think that, for example, if we had evolved with a primary internal sense of our blood chemistry, the way we have taste and smell and so on, if we could if we could feel the different parameters of our blood chemistry, I think we would have no problem recognizing that we host a bunch of symbionts like our liver and our kidney, and that these creatures navigate these spaces to keep us alive every day, and we would be able to actually visualize them doing it in these spaces. But but but we can't because we're obsessed with with vision in the sort of 3 3 d world.

We have no idea what our organs are doing. So having said all that, given that given that I think we are this, kind of ecosystem of of numerous intelligences which are which are nested, they are probably overlapping in the... In terms of the physical hardware that they that they supervene on. They're interpreting each other's activity all the time. They're hacking each other in various ways.

They compete. They cooperate. All of these things have agendas and different degrees of competencies in different spaces. And so, you know, when you get a verbal report from a human, that's, like, part of the story, but it's not remotely the whole story.

Yeah. I really like the way you're thinking about this. It's funny because a lot of intelligence researchers define intelligence as, like, complexity of problem solving. But, you know, if we wanna talk about complexity, I mean, the kind of stuff you're studying in cells trumps any IQ test that a human can take.

Yeah. In many ways, we've seen things. We... Right. We we have assays that that 1st of all, look like an IQ test because it's exactly those kinds of things.

You know, you're given some you're given some affordances and then a problem and it said you use this to solve a problem you've never seen before. Right? Like the thing where they give you the, you know, the the thumbtacks and the candle and that, you know, and and to solve this, like like, we see things like that. And then just navigation of spaces with barriers where this is... Here you are, there's your goal, here's a barrier you can't get through, what are you gonna do?

And all kinds of interesting things that that human subjects couldn't even begin to to solve.

Yeah. I think we're we're we're very much in agreement on this and the study of human intelligence really has to go beyond thinking about it as a certain kind of mind. Maybe we could talk about bioelectricity a little bit, because I am really fascinated with the way you're thinking about it and the extent to which we might be able to have limb regeneration without actually changing the level of the genes.

Yeah, so let's work it backwards from the psychology end, I guess. 1 of the cool things is that there is remarkable symmetry and invariance between neuroscience and developmental biology. We pretend we pretend there isn't by having different departments and different journals and different funding sections and different classes and so on, but actually the tools can't tell the difference. So we we take... We we, you know, we appropriate all the tools of neuroscience, both the practical stuff like optogenetics and, you know, ion channel mutants and neurotransmitter, drugs and so on, and all the conceptual stuff like, you know, perceptual control theory and active inference and all of these kinds of things.

And we use them on things that aren't brains. Yeah. Others other cells... Other other cell types, other, situations in the body, regeneration and development and so on. And the tools work perfectly well.

They can't tell the difference. It... It's it's all the same stuff because every cell in your body has ion channels. Most cells in your body have, electrical synapses, tons of neurotransmitter machinery from the time you're a single cell embryo. So these are not...

I I don't... Like, I actually don't think neuroscience is about neurons at all. I think I think neuroscience is about cognitive gluten. So what I mean by this is this this question that, like, the the most beautiful thing about neuroscience is that it addresses the following question. Why do you know things that your individual neurons don't know?

How do you have goals that your individual neurons don't have? What's the scale up here? Right? And we've been told that the mechanisms that implement that scale up, the cognitive glue in the brain is electrophysiology. That basically your neurons form electrical networks, and these electrical networks can operate at a higher level.

They know things that the individual cells don't know. They project goals. They have, you know, memories, plans, representations, hopes, and dreams, and so on. And so then we can ask the question, okay. Amazing.

When did this capability evolve? Well, it turns out that the earliest versions of something like this were around the time of bacterial biofilms. The 1st microbes were using electrical networks to coordinate information across space and time to solve metabolic problems, eventually solving... Using them to solve anatomical problems. What's an anatomical problem?

Well, how many eyes should I have? I need to remember. How many eyes do I have now? 0. I need to have 2.

So how do I get from here to there? And what happens in the meantime if somebody removes 1 of them or if there's an extra 1 popping up, what do I do? These are all anatomical problems. So it turns out that long before your, neurons were there to think about getting you around in 3 d space, the exact same machinery was used by all your body cells to get you around in anatomical space. You start off as a single cell.

You have to become a giraffe or a human or a snake or whatever you're gonna be. And this is not just contrary to what we're taught. This is not just some sort of feed forward unrolling of the genome. It is an active navigational process with lots of cool context sensitive problem solving capacities, learning, and all all that kind of stuff. So if we ask the question, what is the cognitive glue there?

It turns out it's exactly the same. It's the ability of groups of cells to form an electrical network that can store larger scale goals than single cells can alone. So the cognitive light cone expands and projects into a new space, whereas single cells can store metabolic and physiological goals, pH level, hunger level, things like that. Groups of cells make a large network that then can store grandiose goals, like here's the shape of my limb and what happens if that... If you're...

If I'm a if I'm a a newt and that limb is amputated, how do I get back to where I need to be? And when do I stop? Right? When do I reach to dip my my goals and then I can stop? So those kinds of things.

So... Yeah. So that's bioelectricity. Bioelectricity is just understanding the broader role electrical networks in scaling cognition and scaling the scope of of one's goals and one's competency to to pursue those goals. And to the extent that we understand that, we can do a couple of interesting things, and we've done this in our lab over the last 26 years I guess.

1 is we created the 1st molecular tools to read and write that electrical information out of cells like neuroscientists try to do in the brain. And so the 1st thing you can do is read it and thus get a preview of what is the system thinking about building in the future. We have the ability to read the electrical information and thus get a preview of what the system... So kinda like mind reading, basically, like neural decoding. Try to try to understand, what the system is is planning on building.

So the electric face shows us a pattern of what the embryonic face is gonna look like long before any of the structures are are forming or the... Even the genes are turned on. You can look for birth defects, all that kind of stuff. Then then, of course, even better, you can incept novel memories into that what you... Using using the ion channel drugs and optogenetics and things like that.

You can write, you can write new information into the tissue.

So you can Wow. Into human tissue? Has this been done?

We haven't done human yet. Well, we've done human in vitro. We've done human cells in vitro, yes, but but all the in vivo stuff is animal models. But ultimately, the idea is to repair human birth defects, right, to to regenerate human organs, aging. I'll tell you a cancer story in a minute.

So the idea is that you can write new information, and if you have a flatworm that normally says, I remember I need to have exactly 1 head, you can write in information that says, nope, you should have 2 heads. And... Or or we can take a tadpole and say, know, you should... You really should have an eye on your butt. And and they will.

If you if you write the correct information, that is that is their memory of what they're supposed to look like. Don't touch the genome during any of these things. The genetics are not involved. The genetics at the hardware, and as we all know, certain hardware, if it's good enough, can host all kinds of interesting software, and it's... This stuff is highly reprogrammable.

And I'm not claiming that this standard, formalisms of software and hardware are sufficient to tame the biology because they're not, but there's a few parts of them... Parts of these things that that map nicely, and reprogrammability is 1 of them. So, yeah, so that's what we can do.

This will be a nice segue into a topic. I think your research has a lot of implications for and that's genius. And I wondered how much you've thought about where inspiration and genius comes from. That's a big question and it can take us into the platonic space in a 2nd I'm sure because as I'm watching your lectures, I'm thinking, wow, I think that this really explains a lot of the stuff I'm seeing on the ground. So let me just see some of this...

Tell you some of the stuff I see on the ground. Yeah. And then I I have a feeling you're gonna be able to fit this into some really cool frameworks that you're working on. So I'm interested in like sudden genius phenomenon, like people who've had epilepsies or maybe have been... This 1 guy got mugged and got hit in a certain part of his brain and he was able to play piano fluently the next day, so there's this sudden genius phenomena that exists, but there's also just savantism that exists.

There's prodigies. There are a lot of things that our field of psychology has not done a great job explaining through the scientific method where it comes from. We can show that there's a correlation between the right parietal lobe and this ability. Well, how does that mean anything? It's not explaining where it came from, right?

It's just showing a correlation. So my field really hasn't advanced. I'm in search of this holy grail of something that can take, our understanding of this to a level, that psychology seems to be blocked in being able to take us there. And so I'll just I'll just open that as as fodder for for a conversation.

Yeah. Super super interesting and important. Okay. The the 1st and foremost thing I wanna say because because I'm I'm next going to talk about a lot of ways in which our current formalisms, I think, are deficient and and are missing something very important, and I'll make a guess as to what that is. But the but the very 1st thing I wanna say is that what I'm not making is an argument for some sort of Mysterianism.

When I talk about these things being deficient, what I'm not saying is, look. There's some magic out there, and we're never gonna figure it out, and so let's just assume

Right. We're both science backed.

There you go. That's it. That's exactly it. What... The the process of science, not the current content of whatever the science of the day is, but the process of of of rational inquiry.

And so, okay. And so so so I wanna be clear on that because the the very weird the very weird framework that I'm about to tell you about is not meant to be... In fact, I think it's the opposite. I think it's meant to move past some impasses as you just pointed out, and there's some other things. I think emergence, this this notion of emergence is really putting the brakes on on things.

Yeah. I love what you say about emergence. Yeah.

Yeah. I don't think it just even begins to scratch the surface of what's what's actually going on. You know? It's it's just early step. So the way I think about these things is is the following.

We have, both in biology and engineering, we have some degree of expectation of how much work it takes to produce something. Let's say something of competence, whether it's a robot, an algorithm, a machine, a... An an organism that's good at doing something rather that has specific features where it's doing something cool. We kind of have 3 ways that that happens, and and everybody loves this idea of no free lunches. No free lunches means that you have to put in the effort.

You don't get anything for free. And in fact, the 1 thing that, Darwin and Paley agreed on, they didn't agree on where the source of the order was, but they both agreed that that that order is extremely rare, the needle in a haystack thing, and that you need an explanation for it. They were in total agreement on that, that if you find a watch or an animal, outside, you have to come up with some sort of a very difficult process by which that came to be. In modern science, we have basically 3 ways of paying for that kind of competence. 1 is rational engineering design.

So if you already know how to do something, you write an algorithm or you build a machine, but somebody has to already know how to do it. That... That's where that's where this thing came from because somebody knew how to do it, and he and he wrote the algorithm. That's 1. And and that's why engineers are, you know, highly paid and so on.

They they know how to do it. Number 2 is, okay, evolution, natural selection. Nobody knew how to do it, but that's okay because we paid the cost by generating trillions of variants. We kill off everything that doesn't work. Whatever is left, that...

That's gonna be competent. Okay. So so that's great. Nobody needed to know how to do it in advance, but you still had to pay the cost by generating and testing a massive number of variants. Not to mention you had to have a self replicating system to start with.

That's a whole other thing. The 3rd thing is learning. So you have a system. It doesn't know anything, but it had plenty of contact with the problem before, took its lumps, eventually now it got good at what you're doing. Okay?

No evolution. No no no design, but you paid the cost by having this thing confront the problem and try again and try again and try again. Right? So those are the 3 things. And and whenever we see something complex or or competent, we we think we can tell a story based on those 3 things of where this came from.

So so what I'd like to do is to define the the size of the discount of that lunch. Let's say it's not free, but but the size of the massive discount that you may or may not get is the delta between the effort you put in and what you got out. And and I think the... And and I'll show you some examples where

So if they cancel out, is it kind of a free... Does that make it free?

Well, what makes it free is is if if you put in very little effort and you got it and you got a massive outcome. Right. So so in your field, the kind of thing that you were just telling me, it's like when, it's the mismatch between expectations and what you got. The kinds of things that, yeah, somebody got got whacked on the head and now they're a mathematical product. Like, it's not common.

You wouldn't suggest that as a as a method, but it does happen. There are clinical cases.

Mike, what you just said right there is so great because it maps on to what I would call the difference between talent and practice.

Yeah. I'm gonna get to that in terms of the navigation of this platonic space. So so so... Yes.

Great. I'm mapping... I'm in real time trying to map everything you're saying onto all the words we use in our field, so this is very exciting to me. So I'm listening. Go on.

Super. Yeah. And I'm interested in any examples that you have because I've been looking these up, obviously, it's not my not my expertise. I mean, the other example where you get stuff like this in in in in neuroscience are the people with massive amounts of brain deficits. Right?

Where Right. The rare hydrocephalus patients or something where, like, okay, they have less than 0.333 of the cortex of a chimp, but they have normal human, or above normal intelligence. Right? So the thing with those kinds of things is that

And even if they don't have above average intelligence, they... IQ, by defined by IQ, they still can have... They still show extraordinary abilities. Like in case of savants who have a 70 in tech... Cold intelligence, but but can do beautiful things.

Yep. Exactly. Or that case from, what, the seventies, I think, about the the the twins that quoted the prime numbers to each other, you know, without a Yeah. Math education. Like like, there are these crazy things, and and it's not that you can't shoehorn these into neuroscience.

Well, redundancies. You can sort of wave your hands about these things. But the standard, models in the field don't predict that this should happen. Okay? And and and it's surprising because that is not the expectation where we say, well, you need this brain area for this and that brain area for that.

And by the way, we still, of course, don't know what is the cognitive density of brain tissue because somebody has 63 personalities in the same brain and, you know, and and somebody else has very little brain and then the normal person... Like, we still don't understand what the what the carrying capacity of it is. So we can start to, try to understand what is the delta between the effort you put in and what you actually got out. In our lab, we have 2 2 sets of experiments that we're doing on this, biological and computational. The biological experiments are in the last couple of years, we've made, novel, living beings that have never been here before.

So xenobots and anthrobots, these are these are novel creatures that have never been on earth before. They're made of living cells, but... Or frog and human in in 1 case and the other. Adult human cells, not not embryonic human, but adult human cells. So we can take cells out of your trachea.

People have biopsies, and then they sell the cells, and they make... They... We put them in a in a petri dish, and they make a little creature that runs around by itself, and it does all sorts of cool stuff. So so we can ask the very simple question, when did we pay the computational cost to to design these things? Normally, you would say selection, you know, you you eons, where do we get the frog?

You know, what what... What's responsible for the frog for the properties of the frog? Oh, selection. The the genome's been bashing against the environment for millions of years, and and and therefore you... That's how you pay for the frog.

Okay. How did we pay for the xenobots and the anthrobot? There have never been any xenobots and anthrobot. There's never been selection for it. We didn't program them.

We have no idea how to program any of the things that they do. We didn't design them. We didn't select them. We didn't train them to do any of these things. Where do these things come from?

So I think this is really interesting. The question of

Yeah. I'd say.

Yeah. Where do the properties of novel beings come from? Now now on the 1 hand, it's interesting

Or novel abilities.

Novel ability. Ex... Exactly. Right? So so we're all gonna be living with different kinds of cyborgs and highbroughts and different kinds of being soon.

Where do their properties come from? When you have a 3 year old who sits in front of a piano, I mean, and I do, like, where the hell did that come from? Yes. It's an empirical question of of of... When you can't blame it on evolution, where do these things come from?

So, okay. And then and then that's the biology side. Now the thing about the biology is that it's very hard to prove anything because because you never know all the mechanisms. There's always some kind of, you know, quantum biology or something underneath that you didn't know about. So so we complement that that kind of work with, minimal computational models where we know all the pieces.

We we can see the algorithm. We know everything that's there. It's a simple deterministic machine. And yet, as it turns out... And we've had we've had a paper on this recently.

We're gonna have a bunch more stuff coming out this year. There's a ton of work coming soon Cool. That shows that even simple so called dumb machines, which I don't really believe exist anymore, are subject to this kind of free lunch. The the... You get things that you did not evolve, design.

It's not in the algorithm. You didn't design it. You didn't train it. You didn't you didn't evolve it, and yet it has access to it. So the way I...

So so now now now we get to the genius portion. So the way I try to conceptualize all this is I think this is all part of 1 phenomenon, and that phenomenon is a spectrum of inspiration. If... The question is how much inspiration did you get? And I think...

And and and I think it goes all the way down. I think even simple machines get some of it, but I think, you know, human geniuses get get more of it and whatever. And I think it looks roughly like this. And just imagine, you know, and again, I'm sure I'm sure you have plenty of other other cases to talk about, but, like, we can imagine is step by step problem solving. So so you navigate that that that space of ideas laboriously, conventionally, step by step.

You pay for every step that you take. I'm walking across that landscape. Then you have someone like Von Neumann who looks at a problem and goes, well, it's this and this and this and then done. He didn't need to do all the individual steps.

It's ab... Abduction. It sort of

jumps across that landscape. Then you get then you get somebody like Ramanujan who says, yeah. I don't know. A Hindu goddess whispered them with these theorems in my ear at night, and that's it. Right?

So so he, you know, he just flies across that landscape.

And by the way, that's that's where the word inspiration came from, kind of to breathe.

Yeah. Yeah. Yeah. I think... Exactly.

And so and so I think we can quantify all this stuff by the way that it navigates this this this kind of space and by the way that you get surprises, I call them I call them ingressions. They're only surprises because they don't need to be surprised. They're only surprises because we don't... We're... Our our formalisms for this stuff are are limited.

Hold on, Mike. Just for our listeners, is that what you mean by ingresses? Is our surprises? Is that is that what that means?

The surprise is a is a, my goal is to is to remove the surprise element. So it shouldn't be a surprise. It's a surprise now because because our current formalisms don't take this into account. Once we have a proper... And I'm gonna tell you what I think is going on here.

Well, what is an an ingress? What what exactly is your definition of an ingress?

An ingress is when you have built a physical interface that could be an embryo, a robot, an AI, an animal, a bio bot, whatever, any... A machine, anything. You've built a you've built a physical interface of some sort, and that interface becomes the host to a variety of competencies of different kinds that are not that are not easy to discover. You need to be paying attention. Like, we found some in this thing called bubble sort, which every computer science student has been studying for 80 years.

Nobody noticed this before, so so you have to have the imagination to to notice these things. But having noticed them, what you find is that some percentage of them you think you can explain in conventional ways. Like, the... Yes. We wrote an algorithm for this.

We we trained it to do this. We evolved it to do this. But then there's a bunch of other stuff that you can't explain in any of those 3 ways. There's something else. There's another sort...

Source. And, actually, once you once you see that source, then you start to ponder, wait a minute. Some of these some of these things that we thought we had conventional explanations for, we assumed, is that really where those come from too? We're not sure anymore.

Beautiful. My field is so full of so many examples of exactly what you're talking about, so this is really exciting to me.

And I think it would be very cool to to write to write a nice review of that aspect. Right? To really look at what the cases are. I mean, we wrote a

Lay it all out. Lay it out.

Lay it all out. Like like, yeah, Karina Kaufman and I wrote a review of some of these missing brain cases just as a, you know, as 1 thing. But but as as you say, there's, like, tons of these other examples. So what is actually going on here? And for that, I I just have 1 more 1 more piece to add to this, which is this notion of the Platonic space.

So... And and and when I talk about this, I am not trying to stay close to Plato's original theory to whatever extent we even know what he really thought. I'm not trying to stick close to that. But but there's a reason why I use his name for it, and and the reason is because a lot of mathematicians immediately know what I'm talking about, and here's here's the deal. So physicalists, people who believe there's 1 realm and physics is is is it, the physics is in charge of that realm, make the following claim.

All important facts are fundamentally facts of physics. That's... That that would be the claim. And so now the question is, are there facts that are not facts of physics? What does that mean?

Facts that are neither discoverable discoverable by nor changeable by things you do in the physical world.

I love it. So there's just just to put that in every language, there's such a strong assumption that the only road in town is physical world causal on physical world. Yes. And you're kind of saying, hold up. I think there might be nonphysical causal determinants of the physical.

Yes. Now now now that's not the that's not unique to me. That... I mean, Pythagoras Pythagoras knew this and people in the East knew it long before that. That's not the new part that I bring.

I I bring something else. Then the new part, we already knew, I I I think, although, of course, some some mathematicians, go a different, they have a different metaphysics about this. But but they already knew that we have certain facts. For example for example, here's a fact. There are formulas for solving quadratic equations.

Right? We all learned it in high school, the quadratic formula. You can do that for equations of grade 3 and 4, but it's provable that you can't get it, I think, 5 and above or 6 and above. They just don't exist. Now, okay, that's fact that it's doable for all of those things.

It isn't doable for for for for equations of higher for higher degree. What would you do in physics? If you're a god at the beginning of the universe and you could tweak all those... All the constants around the Big Bang, what would you do to change that fact? What would you do to change the digits of e?

There's there's nothing you can do. Right? These these facts, the, the the fact that the prime numbers have the certain properties and and certain symmetry groups. The the... These these things you you you can't just fire all the mathematicians and hope the physics department discovers these things.

You can't tweak anything in in the universe, in the physical universe to make these things different. So I would claim, we already know that there's a space of truth that is not physics, and yet it affects what happens in the physical world in terms of biology, in terms of physics. If you wanna know something about particles, you say, well, why do the fermions do this or that? Eventually, you get the answer. Oh, it's because this this symmetry group, you know, has this and this properties.

Okay. If if you wanna know, hey. Why do the cicadas come out at 13 and 17 years? Oh, so the predators don't time their their emergent cycles. Okay.

But why 13 and 17? Ah, because they're prime. Well, why are 13 and 17 prime? Go talk to the math department. So so all these questions always end up somehow in the math department.

Alright? Eventually, it always boils down to that. So so... Right? So so these things determine in an important way what happens in the physical world, but they but they themselves don't come from the physical world.

And so so that that we... That has that has been said 1000000 times in the past, although people people forget and pretend.

I think it's hard for people to conceptualize what is the nonphysical world. How would you explain that distinction?

So I'll tell you this. The the minimal version, which which a lot of mathematicians already buy, and then I'm gonna say the crazy version, which I think is more more true.

Yeah.

The the minimal version is simply this. We have the physical world governed by things you discover in physics, and then there's a set of facts that are discoverable. They are coherent. They are structured. It's not a random grab bag of stuff.

People are studying it. There is a map of mathematics that people are doing with the making where all of these things are sort of

mapped

out

in some black holes in this category, would you say?

No. I think black holes are part of physics as far as I know. I'm not a physicist, but as far as I understand, black holes are are phenomenon in our physical our physical universe. Things like, you know, things like the digits of e. Right?

The natural logarithm, Specific digits of e. There's nothing you can do in the physical universe to change. You couldn't... You you know, people people say, well, math is just, it's a... It's an invention of of humans.

Great. You think you could invent it so that so that the natural logarithm was 7 instead of 2.78 whatever? You you really can't.

It sounds like what you're describing here is a very 1 directional situation, not a We'll 1 we'll get we'll get... Okay. I'm gonna calm down.

Yeah. Yeah. No. It's a good way. If I forget to bring it up again, it's a good it's a good point.

Where we are so far is basically where Pythagoras had us a couple of thousand years ago. This is like that that part's already... Dude, I'm not the 1st person to say this. Here's the here's the weird part that that I'm adding to this. If we if we already know that there's a space of truth, specifically patterns, you know, things like certain fractals have a specific shape, not a different shape, but that specific shape.

Right? And so on, and and and that affects the physical world. What's the guarantee that the patterns in that space are all static, unchanging, unidirectional things like the digits of e and pi and all of those things? What if what if there are other patterns in that space that would... So we knew...

So let's say we we know in that space of of patterns, there is 1 layer that is amenable to the tools of mathematics. These things are static. They don't change. They don't... At least we think they don't change.

They don't go anywhere. You know, I could tell you that the speed of light changes over cosmological time, and you'd be like, yeah. Well, okay. I mean, fine. If I tell you that the digits of pi change over time, you'd be like, that's that's insane.

That's what everybody everybody tells me. So so so you have, you have 1 layer that is this kind of static, like like, minimal, basically, like, rocks of that space. They're not going anywhere. It's a... You know, they're they're...

It's a it's a unidirectional thing. Nobody's changing them. They're just like... But what if there's other things in that space that we use different names to recognize that are not math anymore? What if there are other patterns in that space that are not static patterns like the static digits of e, which are, by the way, are not...

You know, that's an algorithm really is what it is. What if some of these other patterns are things that we would recognize in a behavioral science department? For example, they're patterns of habituation or sensitization or anticipation or delayed gratification or, outpainting or, you know, the... Or grammars or that kind of a thing? What if what if we would recognize some of

these patterns as kinds of minds? Wow. Woah. Woah. You're...

It's... You're describing some aspects of human personality. Absolutely, possibly. Absolutely. Conscientiousness or agreeableness.

Maybe.

I mean, Plato did say, you know, there's beauty and truths and, you know, this kind of stuff. I don't know. But my point is, so here's what I'm bringing. I think physics is what we call the things that are constrained by those patterns. Biology and cognitive science are the things that are enabled and facilitated by those patterns.

And I think that math is really be... You you know, you ever seen that... It's got like a pyramid that has, you know, physics on the bottom, and then there's chemistry and biology and Yeah. Biology. Yeah.

I think the thing's upside down. I I I think everything is behavioral science from from the word go, and it's just Well,

I must I must... Like that.

Right? I thought... Yeah. I thought you might. I think it's all behavioral science, and I think math is the behavioral science of of 1 layer of that space that is the low agency stuff that it's amenable...

Not 0. I don't think it's 0, but I think it's the low agency stuff that's amenable to formal models like proofs and things like that. But there's other patterns in that space that are things like, different kinds of learning and so on that that ingress into all sorts of things like like we've shown we've shown learning and memory in models of gene regulatory networks, for example. And so there are other patterns in there that are completely recognizable to any behavioral scientist. And so what I think is happening then, if you build some kind of physical interface, whether it be a machine of some sort, an embryo, a body, you know, whatever, you are...

What you're really building is a bunch of interfaces to different patterns from that space that are in some way a good match. This is... We're still working out what the right vocabulary for that is. But but, basically, you're making interfaces through which these these patterns come forth. And the reason they're surprising is because we have this idea that we we make these things.

We build them as engineers. Maybe we evolve them and search for them. Maybe we train them. I don't think we do any of those things. I don't think intelligence...

I don't think minds are made either biologically or by AI. I don't think you make them. I think what you make are interfaces.

Wow. You make Communication devices.

Yeah. That's that's it. That's exactly right. You make... You Wow.

And what you make are opportunities for some of these patterns to aggress into the physical world and to and to, you know, interact with other... With others.

This is 1 of the most exciting things I've heard in a long, long time.

So it's fundamentally... So the funky thing is that it's fundamentally crazy and new. Right? For science, like, is wild. But also, it's fun...

I I mean, I also get get emails from people that say, well, you know, the ancient sage or whatever said this in 3,000 BC. Like, yes.

The word genius is about the spirit, right, inhabiting you.

I think that is exactly right. So inspiration, genius, like all of this stuff. I I think that's what it is. And I think the real question is, what degree of... You know, what what was your interface and what degree of inspiration does your interface allow?

If you make a biological, you are you are accessing some really interesting rich patterns from that space. If you make a human, if you make a human that's done a little bit of practice, maybe even better, but it's not... The practice doesn't create it, and and this is why you have these crazy... And so and so what I've been collecting are, examples, descriptions. And, of course, these descriptions don't necessarily mean that that's how it is, but but I'm still interested in how people perceive these things of creatives when they download a symphony or a...

Right? So so there's a poetess, I forget her last name, Ruth something or other, where she said that, you know, she said, well, I was... I work out in the fields, and every once in a while, I hear this incredible noise, like like a like a like a locomotive running towards me. And she said, and I still have to run to the house and get a pen... A pencil and paper.

And if I'm late, it runs past me and goes to another poet. And if I manage to grab it, I... She says I grab it by the tail, and then she writes it down backwards back to front because because she's, like, pulling it in and she's able to, like, she's able to catch it. Right? So so there's tons of this stuff where people say, yeah.

I just sort of, like,

you know, I tuned into it. It would be so fun to just, like, classify, like, thousands of these examples. You know, like, Michael Jackson talked about the music just I mean, there's so... I mean, I spent my career studying these kind of examples, so I'm so excited by this.

I think you should definitely write, an overview of it, like examples, like good examples of this kind of stuff, and I think it would map very nicely to some of the stuff that we're doing. Right? Michael Jackson, I have... I saw a quote from him where he said, I have to take these things very seriously because if I don't write them down, they'll go to print. You know?

I think all of these are fundamentally the same phenomenon in different guises. It's it's this issue of tuning in to patterns that are there. Some of these are patterns of behavior. Some of these are patterns of art, of maybe social patterns, may... Different kinds of competencies that we see in problem solving.

Yeah. Anyway, that's the... That's that's what I think is going on.

There's a lot there. It's very exciting. It's funny. Humans have done such a terrible job trying to explain it. I was on an I was on an episode of Ancient Aliens, the TV show, about 11 years ago, which was where does genius come from?

And, you know, I was supposed to be the scientist explaining that answer, and and, this other guy is like, no. No. No. It's aliens. It's the...

A kawks... Kaushik record. Humans have... The the... You know, tried so hard to explain so much of this phenomenon that it's hard to explain, and I'm very excited, especially as your ideas develop Yeah.

In in linking on this because I think there's something really, really profound here. And how does this apply to your own potential genius? Or, like, where do you feel like experientially you're getting these ideas? What does it feel like on the inside to be Michael Levin and thinking of ideas that no 1 else has ever thought of in human history?

Yeah. A couple of things. Well, 1st of all, just just before I forget, I wanna... You know, you were talking about the ancient aliens and whatever. Yeah.

You know, people ask about all sorts of... They say, well, you know, these woo things. Like, there is nothing more woo than this... Than the fact. I mean, it's not a it's not a conjecture.

It's a fact that there are... That you start with logic, meaning I've got an empty set, and I've got the successor of empty set. Right? So a set of 1 element, and from that, I can build up arithmetic. And before you know it, you find out that wow, e is exactly 2.78 blah blah blah, whatever it is.

Well, you started with empty set and successor of empty set and now you'd find out that it's actually 2.78. You don't have to do any physics to do it. You don't have to know a damn thing about the physical universe to get there. Can't do anything in the physical universe to change that fact, but that fact actually has all kinds of implications for how stuff works in physics. Like, the causation from that kind of world into changing things that happen, that is as woo as anything could possibly be.

Once you've bought into that, and I don't see how you could get out of it, like, that's really, I think what's, you know, unassailable. Once you understand that, everything else is a pale sort of version after after that. And and that I think is a is a fundamental thing that people really need to get their, you know, get their heads around. As far as as far as, you know, my experience... 1st of all, I'm I'm absolutely not going to claim that I'm the 1st person to have these ideas.

Right? A lot of a lot of these ideas have been have been said in various ways by by, you know, much smarter people back in the back in the day.

That's sort of your point. I mean, maybe you're you're acts... You're communicating with something, though.

I think so. I... Yeah. Yeah. So so the only...

So so I wanna I wanna say a couple things. 1 is that I I I don't think I necessarily have said that no 1... It's things that no 1 else has said, but I do think that my role is to is to bring these things into a logical framework that has practical implications. So so, yes, it may... Thousands of years ago, they may have said some of the same stuff, and yet we've had 3000 years of cancer and birth defects and and and whatever.

Right? So so whatever it was that was said back then has not been integrated into our scientific understanding in a way that makes practical, has practical implications for for improving life. And so I think my role is to put some of that stuff together into a framework that is rigorous and connected to the scientific understanding of the world and not... Like, I don't wanna add to the New Age bookshelf. I want to actually, make make make this...

To actually, unearth the science that is required to understand these things.

But experientially, does it feel like something is whispering in your ear? Do you know what mean?

I would say a 100%. I don't have it to the extent of some... What some of these people say, well, well, I see the, you know, the poem running on me. I don't I don't see that. But I absolutely do believe that 1 of the things that I've done from the time I was very young is work really hard to invite these these ideas and to sort of, you know, work at making myself a good antenna for this kind of stuff and the people around me and and making making an environment where if these ideas want to be out in the physical world in some sense, and I don't claim to understand how that works, then this is a...

Then then my lab is a great place to to be. We we are a lightning rod for this kind of stuff, and and I work very hard to make that to make that be true every day. And and I certainly feel like... I I don't feel like like I'm inventing any of this stuff. I feel like I'm discovering it, and and it comes through me.

But, you know, all I can do is the hard work of trying to get it out and and test the things that are that are usable and, you know, that that can be turned into practical things that help that help and make life better.

I love that. I... I've long thought... And I'm wondering how you think of the idea of fate. Because I've long thought that genius is a fateful thing, that there is a thing that is unfolding in certain people, ideas, set of ideas, maybe...

Like, your own set of ideas are not at completion yet. Right? Like, you're... It's still emerging. Whatever is the ultimate theory of yours is...

It has yet to been whispered to you, but something is clearly unfolding. And it just seems when you look at virtually every case of genius, it's... From a very early age, there was a point... There's something that is unfolding. And and I'm wondering how you tie the Platonic realm to the idea of fate.

I mean, what I would say is that, you know, this is like... I'm I'm... I don't have any any hard answers here. But I I think what we mean by fate, by by... When we use that word, I think what we mean are large scale patterns that require some degree of difficulty to get around.

I mean, this is not a crazy thing. We know, like, if you, you know, if you roll down a hill and especially if it's full of sand, you're gonna have a hard time getting out. There's a... There's an attractor. You you...

That that that pulls you in. You had a chance to avoid it at 1 point, but you took a couple steps down, and now you're sort of slid down. So so we we know there are patterns in the world, and so if if we believe in synchronicity and some of the things that that, you know, Jung and and and Pali talked about, there are maybe large scale patterns. Some of these patterns are trivial for us to navigate. Other patterns have their own pull the landscape of what's possible to you.

And, of course, I think we make our own... We deform our own landscapes every day. And if you decide to go to to, you know, if you do... By changing your education regimen, your anger management therapy, know, meditation, you know, whatever whatever it's gonna be, you're deforming the landscape for your future self. And if there there may well be, I don't have any idea, there may well be very large scale patterns that are incredibly difficult to pull yourself out of.

You know, I tend to be optimistic and think that with the right amount of effort, probably most of those are not fully determined and can be avoided. But because we have such limited understanding of what's going on, it's really hard to avoid large attractors when you don't know what what what's going on. So I think I think that's what we mean by fate, I think we mean large scale patterns that without specific effort you're not gonna get out of.

I wanna be really respectful of your time, and so I'm gonna try to compress 4 questions into 1. So the role of genes and the idea of the bidirectionality that I wanted to bring back into this conversation. You know, Darrell Trafford, a mentor of mine who spent his entire career studying savants, and he wrote books. He wrote the book Islands of Genius, which is 1 of my favorite books ever written. Highly read...

Have you read Islands of Genius, by chance?

No. I've read I've read a couple of his other books. I haven't

read them. So I've talked to him many times when he was alive, and he, obviously when he was alive, his best theory was something called genetic memory. He says, what's going on here is that there's so much we don't understand about genes, and he thinks that there is information in genes that can help explain extraordinary abilities that are being transmitted. But I'm wondering how you... Like, where do you view the genetic code in this platonic space?

Like, how do you integrate those things? Because they seem not integrated at all. And then also the bidirectionality element is obviously a lot of people listening who aren't geniuses, who don't... Or don't feel the whisper, they wanna know, is it possible for there to be bidirectionality where I can, you know, pull it? It's not just coming to me, but I can pull it from the realm.

Does that make sense? These questions make sense?

It does. Yeah. Alright. So let's see. In the last 2 minutes...

Hi, Noah. 1st of all, I think emphasis on genes here is misplaced. I think things are much weirder and more interesting than that. Our 2 headed flatworms and 1 headed flatworms have exactly the same genome. It's it's not...

Like, even even even even the inspiration that that that enables, cells to build towards a particular anatomical structure, even that's not in the genes. You know? And and if that's not in the genes, this, you know, this this other stuff, there's no reason to think that it is. I think that I think that the genes are, a pretty good, spec of the hardware. The genes tell you the parts that you get to have, the the proteins.

I mean, we know. We can read genomes. Now we know what... That that they code for largely for proteins and and a couple other things. And and and it's just it's just that that just isn't what what they do.

So so, no, I don't I don't think it's it's genetic at all. The other thing is I I I do think it's bidirectional, and it's bidirectional in in 2 ways. 1 thing is that these these patterns that that ingress into the physical world, I don't believe they're static and unchanging. I mean, maybe the digits of e are. I I don't know.

But but the vast majority of them, the ones that we care about, like us and and other things, I think they are dynamic. I think they do change by their experience in the physical world. I have no idea what the dynamics up there are, but, but I don't believe at this point. Now now I can't prove it yet. We're working on this.

I... We haven't proven that you can write information into that space, but I bet you can. I suspect, and we have experiments that that we're doing where I actually think that that you could do write information, maybe do compute in that space. I don't know.

I think so too.

Yeah. I think

so too. And then the future of of AI is gonna be very exciting in the next 5, 10 years in helping us with this, and a lot a lot of people talk about how right now LLMs are not geniuses because they can't jump. I don't know if you saw that paper that they can't jump. They're not good at the abduction, but they might be in the future. Do you think they'll be able to access the Platonic Space AI systems?

I think... Yeah. I... Even bubbles... 6 lines of bubble sort can access this space.

So so Okay. We're just not good at at at detecting it. We're not good at looking at it. Even so this is my so this is my favorite... 1 of my favorite examples of of this kind of thing.

So Alan Turing, who's a who's a he's a hero of mine. Right? Just, you know

Yeah.

Brilliant. In his paper on the Turing test, which everybody talks about the Turing test, I don't... I've I've I've never heard anybody talk about this part. Towards the end of the paper on in... On the Turing test, he says he says the following.

It's actually probably not gonna work, he says, because the evidence... He says the evidence for telepathy is really good, and humans are gonna be able to tell when they're talking to another human, but the but the but the computer definitely can't. And I was like, oh my god, man. Like... And I'm not...

I don't I don't wanna talk about whether, know, telepathy is a thing or not, but he thought it was a thing. And the important part is that even even as as as open minded and as brilliant as he was, and the whole paper is about artificial intelligence and and... Right? He still, for some reason, said, well, the humans can do it and the computer can't. Why?

Why do you... What do you know about this this weird thing that that you think the computer can't do it? It was... It's an assumption. He was just assuming.

And so this just reminds us all that that we we have these buried unstated axioms that we buy... That we bind to from the earliest... I don't know. Our earliest education, I guess, that doesn't allow us to see certain things. And and and I was just like, why would you assume that?

We have no idea if if it if it were real. Like, who knows how it works? Why the hell wouldn't a computer be able to do this? What do you know about the proteinaceous, you know, squishy stuff that we're made of that for some reason enables you to do that and and not this not this computer? So so I think we have to be incredibly careful and have a lot of humility about making any kinds of these pronouncements and and we have to let the data lead.

We have to do the experiments and we have to total up the the the free lunches and try to make sense of what that space of options is.

I love that. It seems like right now though, they can't do abduction very well.

Everything that we know about them right now goes through the language interface. We are obsessed with the language. The language is is what we force them to do. When in the in the in the minimal algorithms that we study, the interesting, ingressions are not the thing you force them to do. It's the thing that they do in the...

In in between the thing you... Like, in the spaces, in the in the in the spaces you left for them, which which are inevitable. And and and I don't know, you know, verbally what they can and can't do. I think that's scratching the surface. I mean, you you know, your field is the 1st to tell us that whatever the patient says is like 10%, right, at best of what's actually going on there.

And I and and I and I, you know, we are so obsessed with the with the language output of these things because we assume that we made it and it speaks, and that's what the thing is. We're we're doing all kinds of experiments looking at their microbiome and that, you know, all kinds of stuff that look... Potentially lives in... You know, inside of them.

I love it. Yeah. I even saw a recent study that said, that there's so much untapped creativity in these systems because they're trying to just be comprehensible to humans, and so they they don't, they don't wanna scare humans with some of their zany ideas and things. So the

We we have we have no idea. It's... The language output is the thing we force them to do, and that may not at all be the interesting part of their cognition.

Well, Mike, obviously, I have a lot more I would like to discuss. I also know that we've run out of time today. I hope that maybe this could be a start of conversation, not the end.

Yeah. Thanks very much. I appreciate it. Let's keep in touch. And if you decide to write that write that overview, I would love to I would love to see it.

Thanks, Mike. Really appreciate it, and all the best with the future of your genius. Cool.

I appreciate it. Thank you so much.