Michael Levin: Consciousness, Biology, Universal Mind, Emergence, Cancer Research

The hardware does not define you. I get

lots of emails from people who say "I've read your papers. I understand I'm a collective intelligence of groups of cells. What do I do now? I just learned

cells. What do I do now? I just learned that I'm full of cogs and gears.

Therefore, I'm not what I thought I was." And I think this is a really

was." And I think this is a really unfortunate way to think. The bottom

line is you are still the amazing integrated being with with potential and a responsibility to do things. I think

we are actually a collection of interacting perspectives and interacting consciousnesses.

Professor Michael Lean, welcome. What's

one of the biggest myths in biology that you with your research, with your lab is helping overturn? Yeah. Uh, hey Kurt

helping overturn? Yeah. Uh, hey Kurt great to see you again. Um, I think that, uh, one of the biggest myths in biology is that the best explanations come at the level of molecules. So this

this biochemistry what what they call you know molecular mechanism is uh usually currently taken to be the kind of the gold standard of of what we're looking

for in terms of explanations and I think uh in some cases that's valu that's you know that that has the most value but in most cases I think it's it's not the right level and uh Dennis Noble has a

really interesting uh set of um set of papers and talks on uh biological relativity so this idea that different levels of explanation in especially in biology uh provide the most bang for the

buck and I think in terms of looking forward uh as to what do these explanations let you do as a next step uh I think we we really need to go beyond the molecular level for many of these things what's the difference

between weak emergence and strong emergence I think that emergence in general is basically just a measure of surprise uh for the observer so I think a phenomenon

is considered emergent by us if whatever it's doing was something that we didn't anticipate. And so it's it's relative. I

anticipate. And so it's it's relative. I

don't think emergence is an absolute thing that is either is there or isn't or is weak or strong. It's just a measure of the amount of surprise. You

know, how much how much extra is the system doing that you knowing the rules and the various properties of its parts didn't see coming. That's that's

emergence I think. Would you say then that biology has physics fundamentally?

So it goes biology, chemistry, physics.

I mean, people have certainly made that um that kind of ladder. Uh I'm not sure what we can do with that. I think that uh it's more like these different levels

have their own um types of concepts that are useful for understanding what's going on and they have their own autonomy. That's really important that I

autonomy. That's really important that I think it's uh there's there's a lot of utility in considering how some of these higher levels are autonomous and they do things that the lower levels don't do.

And and that gives us power that gives us experimental power. And would you say that there's something that the lower levels don't do in principle or in practice? So for instance, is there

practice? So for instance, is there something that a cell is doing that in principle can't be derived from the underlying chemistry which in principle can't be derived from the underlying

physics? Yeah, it really depends on what

physics? Yeah, it really depends on what you mean by derive. For example, there are certainly aspects of let's say cognitive functions that we normally associate with fairly complex creatures

brains and so on that we are now seeing in very simple basil media. So even

something as simple as a gene regulatory network can have six different kinds of learning and memory for example Pavlovian conditioning. And so there

Pavlovian conditioning. And so there what you would see is on the one hand you say okay well look here's here's a a simple bit of chemistry that's actually doing these complex things that we normally associate with behavior science

and with investigating cognitive systems. Um you can always tell a chemistry story about any effect. In

fact you could you could also tell a physics story as well if you look under the hood. All you ever find is chemistry

the hood. All you ever find is chemistry and physics right? Uh but the more interesting thing about that story is that you actually can use paradigms from behavioral science such as learning and

conditioning and communication and uh and and active inference and things like that and that lets you do way more than if you were to restrict yourself to a to an understanding at the level of mechanism. What's super interesting

mechanism. What's super interesting there is that you said you could always tell a chemistry story or you could always tell a physics story to explain some biological process, but you can't always tell a biological story to

something that's physics related. So

what people would consider more fundamental or what gives rise to the rest in terms of ontology would be well can you tell a story in terms of so and so. So can you tell a story in terms of

so. So can you tell a story in terms of biology of physics? Can you tell a story of well you can tell a story of architecture for these buildings behind us? maybe even of biology because people

us? maybe even of biology because people comprise the people who made this and you could tell a mathematical story but it would be difficult to make the case that you could tell an architectural

story in the way that we understand architecture not a metaphor about mathematics. Do you agree with that or

mathematics. Do you agree with that or do you disagree with that? Uh I I I think that's somewhat true although it's not as true as we think. So often times you actually can tell an interesting

story cashed out in the terms of uh behavioral, science., uh, for example

behavioral, science., uh, for example active inference for example various learning modalities uh of objects that are really thought to be the domain of physics and chemistry so I think there's

more of that than than we tend to uh we tend to understand as of now but it is also the case that the fact that you can tell a physics story doesn't mean that there's that much value in it

necessarily so for example uh imagine that there's a chess game going on so you could you could absolutely tell the story of that chess game in terms of particle

movements and or or maybe quantum foam or I don't know what whatever the bottom level is. So, so you can do that. Um how

level is. So, so you can do that. Um how

much does that help you in playing the next game of chess? Almost not at all.

Right? It's it's if if your goal is to understand what happened at the physical level, yes, you can tell a story about all the atoms that that were pushing and pulling and all of that. But if your goal is to to understand the large-scale

rules of the game of chess, the principles uh and and more importantly to play the next game of chess better than what you just witnessed, that that story is is almost completely useless to you. And this this abounds in biology

you. And this this abounds in biology where you can uh you can use chemistry and physics to tell a story looking backwards about what just happened and why. But in terms of understanding what

why. But in terms of understanding what it means and developing that into a new uh new research direction, new biio medicine, new discoveries, it it often means that you actually have to uh tell

a a much larger scale story about memories, about goals, about preferences and and and these other kinds of concepts. What would be the analogy here

concepts. What would be the analogy here for so the rules of chess? What are you trying to understand? The rules of what?

Biology, developmental biology, cellular biology. Uh well the the thing that ties

biology. Uh well the the thing that ties all of our work together I mean we we do a lot of different things. We do cancer biology, we do developmental biology, we do regeneration, aging um not to mention AI and some other things. What ties it

all together is really an effort to understand embodied mind. So I this the center focus of of all my work is really to understand cognition broadly in in

very unconventional diverse embodiment.

And in biology, uh what we try to understand is how life and mind intersect and and and what are the um what are the features uh that uh that

allow biological systems to have preferences, to have goals, to have intelligence, to have problem solving clever problem solving in different spaces. Okay, great. Because there are a

spaces. Okay, great. Because there are a variety of different themes that your work touches on. So regeneration, cancer research, basal cognition, cross embryo genetic assistance, which is from a

podcast that we did a few months ago and that will be on screen, link in the description. There's xenobots

description. There's xenobots anthrobots. Please talk about what ties

anthrobots. Please talk about what ties that all together. Yeah, what what ties it all together is the effort to understand intelligence. Um, all of

understand intelligence. Um, all of those things are really different ways that intelligence embody is embodied in the physical world. And so for example when we made xenobots and anthrobots

our goal with all of these kinds of synthetic constructs is to understand where the goals of novel systems come from. So typically when you have a a

from. So typically when you have a a natural plant or animal and it's doing various things, uh not only the structure and the and the behavior of that organism, but also whatever goals

it may have, we typically think of are driven by evolutionary past, right? So

so these are set by the evolutionary history, by adaptation to the environment. So, you know, for eons, um

environment. So, you know, for eons, um everything that didn't quite wasn't quite good at pursuing those goals died out and then this is what you have.

That's the standard story. So, the

reason that we make these synthetic constructs is to ask, okay, well, for creatures that never existed before that do not have an evolutionary history of selection, where do their goals come from? So, that's that's just part of

from? So, that's that's just part of that that research program to understand where do the properties of novel cognitive systems come from that do not have a long history of selection as that

that system. um everything else is that

that system. um everything else is that we do is is an extension of uh our search for intelligence. So basically

cancer right so so the way we think about cancer is as the uh the size of the cognitive light cone of living or of cognitive systems. So what I mean by

that is every every agent uh can be uh demar it can be defined by the size of the largest goal it can pursue. So

that's the cognitive lyone in space and time what are the biggest goals that it can pursue. So if you think about

can pursue. So if you think about individual cells, they have really uh sort of humble single cell scale goals.

They have metabolic goals, they have you know, proliferative goals and things like that. They they handle uh the

like that. They they handle uh the situation on a very small single cell kind of scale. But during embryionic development and during evolution in general, uh policies for interaction between

these cells were were developed that allow them to scale the cognitive lone.

So groups of cells for example uh the groups of of cells um that uh are involved in making a salamander limb they have this incredibly grandiose goal in a different space instead of metabolic space they are building

something in anatomical space. So they

have a particular path that they want to take in the space of possible anatomical shapes. So when a salamander loses their

shapes. So when a salamander loses their limb the cells can tell that they've been pulled away from the correct region of anatomical space. They work really hard. They rebuild uh they take that

hard. They rebuild uh they take that journey again. They rebuild that limb

journey again. They rebuild that limb and then they stop. and they stop because they know they've gotten to where they need to go. That whole thing is a navigational task, right? And

there's some degree of of intelligent problem solving that they can use in taking that task. So, uh that that uh amazing scale up of the cognitive ly that that that you know from what what

the the Lyone measures what do you care about? So, so you know, if you're a

about? So, so you know, if you're a bacterium, maybe you care about the local sugar concentration and a couple of other things, but that's basically it. If you're a set of salamander cells

it. If you're a set of salamander cells what you really care about is your position in anatomical space. Do we have the right number of fingers, the right is everything the right size and so on.

And so understanding that scaling of cognition, the scaling of goals, the how does a collective intelligence work that takes the little tiny very competent tiny components that have little tiny

lychones and how do they come together to form a a very large cognitive lyone that actually project into a different space, anatomical space now instead of a metabolic space. though that that's

metabolic space. though that that's that's fundamentally a question of intelligence and and and the other thing about it is that this kind of thinking so this is really important that this kind of thinking is not just you know

sort of philosophical embellishment because it leads directly to biomedical research programs. If you have this kind of idea, what you can ask is, well let's see then in then if if if cancer

is that type of phenomenon, it's it's a it's a breakdown of that of that scaling and that basically individual cells just shrink their ly back down to the level of a primitive microbial cell as they

were once and that boundary between self and world now shrinks. Whereas before

the boundary was that whole limb, now the boundary is just every cell is is the self. So from that perspective

the self. So from that perspective they're not more selfish. They just have smaller selves. So that's really

smaller selves. So that's really important because a lot of a lot of work in cancer um models uh cancer cell behavior from a perspective of game theory like they're less cooperative and they're they're more selfish. Actually

I'm not sure that's true at all. I think

they just have smaller selves. And so so just a moment. So you think you would say that every organism is equally as selfish. It just depends on their

selfish. It just depends on their concept of self. Yeah. I think I think all agents are one of the things agents do is operate. It's not the only thing they do, but one of the things they do

is they operate in their self-interest.

But the size of that cell can grow and shrink. So individual cells when they're

shrink. So individual cells when they're tied into these large networks using electrical cues, uh, chemical cues biomechanical cues, they're tied into these larger networks that partially

erase their individuality. And we could talk about how I think that happens. But

what you end up with is a is a collective intelligence that has a much bigger uh, cognitive light cone. The

goals are much bigger. And then of course, you know, you can scale that up.

I mean, humans, you know, have enormous enormous cognitive light cones. um and

and whatever is beyond that. But but but that's the thing. It's the size of your cognitive icon that determines what kinds of goals you can pursue and what space you pursue them in. So we talk about goals and we talk about

intelligence. And you said something

intelligence. And you said something interesting which is that life is the embodiment of intelligence or something akin to that the embodiment of intelligence. So it's as if there's

intelligence. So it's as if there's intelligence somewhere and then you pull from it and you instantiate intelligence. So is that the way that

intelligence. So is that the way that you think of it? Let me be clear about about what I mean. In philosophy

there's this concept of universals. So

Plato had the forms. Yeah. And then

would say that this is almost rectangular. So it's embodying the the

rectangular. So it's embodying the the rectangularness which is somehow somewhere out there akin to what I imagined you meant when you said intelligence is there being embodied by this. But then there's Aristotle which

this. But then there's Aristotle which says okay yes there is something akin to a form. It's just not out there. It's

a form. It's just not out there. It's

actually in here. The rectangularness is a property of this microphone.

So I imagine this latter view is the one that most biologists would take. Not

that there's intelligence out there.

Let's just grab it and instantiate it here. No, something is has the property

here. No, something is has the property of intelligence. So explain what you

of intelligence. So explain what you mean when you say embodying intelligence and also what you mean by intelligent.

Yeah. Uh let's see. And ju just just a quick thing to finish real quick the previous thought which is that the reason I think this stuff is not um philos these are not questions of philosophy. These are very practical

philosophy. These are very practical questions of science because they lead to specific actionable technology. So

so the idea that what's going on in cancer is a shrinking of the cognitive lone leads directly to a research program where you say, well, instead of killing these cells uh with chemtoxic chemotherapies because I believe that

they're, you know, genetically irrevocably irrevocably damaged, maybe what we can do is force them into better electrical networks with their neighbors. And and and that's exactly

neighbors. And and and that's exactly what we've done. And so so we've had um lots of uh lots of success uh expressing strong human anka genes in in frog

embryo cells and then leaving the leaving the anka proteins be but instead making sure that they're connected into uh tight electrical networks with their neighbors and they normalize. They make

nice skin, nice muscle. They they do their normal thing instead of being um metastatic. And so so that kind of

metastatic. And so so that kind of thing, you know, it's it's very important to me that all these ideas and so we'll talk about in a minute about platonic space and things like that.

It's important to me that all of these ideas don't just remain as kind of philosophical musings, but they have to make contact with the real world and specifically uh not just explaining stuff that was done before, but

facilitating new new advances. They have

to they have to enable new research programs that weren't possible before.

That that's what I think is the value of all of this kind of these these deep philosophical discussions. So let's see

philosophical discussions. So let's see uh with respect to the definition of intelligence. So I like for for

intelligence. So I like for for practical purposes I like William James' definition which is the ab some degree of the ability to reach the same goal by

different means and that uh presupposes it's an interesting definition because it presupposes that uh there is um some problem space that the agent is working on. Uh but it does not say you have to

on. Uh but it does not say you have to be a brain. It doesn't say you have to be natural versus artificial. It doesn't

say any of that. It's very cybernetic definition. What it says is that you

definition. What it says is that you have some amount of skill in navigating that problem space to get to where you want to go despite interventions despite surprise, despite various

barriers in your way. How much uh competency do you have to achieve that?

And that was his definition of intelligence. Now, I will certainly

intelligence. Now, I will certainly agree that that doesn't capture everything uh that we care about in cognition. So, so a focus on problem

cognition. So, so a focus on problem solving doesn't handle play and it doesn't handle um emotions and and things like that. But uh for the purposes of of our work I focus on the

problem solving aspects of of intelligence. So within uh within that

intelligence. So within uh within that um the uh your your your point about the the platonic space. So now so now to be to be clear everything that I was saying

before I think we have very strong u empirical evidence for and so now I'm going to uh in answering this question I'm just going to talk about stuff that I'm not sure of yet and that these are just these are ideas we don't you know I

I don't feel strongly that we've shown that any of this is true but this is my opinion and this is where our research is is going now. Uh I I actually think

that uh uh the the Platonic view is is more correct. Um and I know this this is

more correct. Um and I know this this is not how most biologists think about things. I think that in the exact same

things. I think that in the exact same way that um mathematicians that are uh sympathetic to the Platonic worldview this idea that that there are in fact in

some way there is a separate world in which various rules of number theory and various facts of mathematics and uh various properties of computation and things like that, right? That there's a separate space where these things live.

And importantly, the idea is that you know they think that we discover those things. We don't invent them or create

things. We don't invent them or create them. We we discover them. That uh and

them. We we discover them. That uh and and that they would be true still if all the facts of the physical universe were different. They would still, you know

different. They would still, you know they would still be be true, right? I I

extend that idea in a couple of ways.

One is I think that what what exists in that platonic space is not just um you know rules of mathematics and things like that which are in a certain sense low agency kind of objects because they

just sort of sit there doing you know they don't do much. I actually think that there's a spectrum of that and some of the components of that platonic space have have much higher agency. I think

it's a space of minds as well and of different ways to be intelligent. And I

think that just like when you make certain comput certain devices, you suddenly harness the rules of rules of computation, rules of mathematics that are basically free lunches. You know

there are so many things you can build that will suddenly um have properties that you didn't have to bake in. you

know, you get that for free basically right? I think intelligence is like

right? I think intelligence is like that. I think some of the components of

that. I think some of the components of that platonic space are actually minds and uh and sometimes what you what happens when you build a when you build a particular kind of body, whether it's one that's familiar to us with a brain

and so on or really some very unfamiliar architectures, whether they be alien or synthetic or whatever. I think what you're doing is you're harnessing a pre-existing uh intelligence that is

there in the same way that you harness various laws of mathematics and computation when you build specific devices. Okay. Well, that's super

devices. Okay. Well, that's super interesting. So, at any moment there's a

interesting. So, at any moment there's a mic there's Mike 11, but there's Mike 11 at 11 a.m. Then there's Mike 11 at 11:01 a.m. And it's not clear they're the

a.m. And it's not clear they're the same. So, there's the two the river. Do

same. So, there's the two the river. Do

you step in it? This is the same river.

Okay, cool. There's a through line.

There's something there, though. Maybe

it's something like you're akin to what you were an epsilon amount of time previous and then that's the through line. So, as long as that's true, then

line. So, as long as that's true, then you can you can draw a worm of you throughout time. Are you saying that at

throughout time. Are you saying that at any slice of that there was a Michael 11 in some Michael Leven space which is also in the minds of human space and you're picking out points somehow?

You're traversing this space of minds.

That's that's actually uh even more specific than what I was saying. I mean

that's that's interesting and and I think that's um that what what I was saying that uh in general um kinds of minds. So there are different uh I I

minds. So there are different uh I I don't know quite what to think about individual instances um but but kinds of minds you know because that would be an extremely large space then. Well, I

think yes, I think the space is extremely large, possibly infinite, uh but in fact, probably infinite. Um, but

I I think what what I was talking about was mainly types of types of different minds, types of cognitive systems. Now for individuals, you rais a really interesting point, which is I call them

selflets, which are the the kind of the thin slices of experience that uh you call them selflets. selflets, you know because you have a you have a you have a self and then and then the different slices of it are the selflets and you

can look at it as, you know, kind of like, that, that that, um, special relativity, you know, bread loaf, you know, sliced into pieces, that kind of thing. So, uh I I think what's

thing. So, uh I I think what's interesting about asking that question about the self and what is the through line is what's really uh important there is to pick a vantage point of an

observer. Again, kind of akin to to what

observer. Again, kind of akin to to what happens in relativity, you have to ask from whose perspective. So, so one of the things about being a continuous self is that other observers can count on your behaviors and your properties

staying more or less constant. So, the

reason that we identify, oh yes, you know, you're the same person as you were before is basically nobody cares that you have the same atoms or you don't or or the cells have been replaced. What

what you really care about is that this this being I I can have the same kind of relationship with them that I had before. In other words, they're

before. In other words, they're consistent. I can expect the same

consistent. I can expect the same behaviors. The things that I think they

behaviors. The things that I think they know, they still know and so on. And so

that that of course in in in our human lives that um uh often often breaks down because because humans grow from from being children to being adults all their

preferences change uh uh the things that they remember in the things that they value change in our own lives we sometimes change right and that's that's a much more important change you know are you the same person even though if

if if all your material components remain the same but you changed all your beliefs all your preferences would you still be the same person right so I I think I think what we mean when we say

the same is not about the matter of it all. It's about uh what kind of

all. It's about uh what kind of relationship we can still have and and what what do I expect from you behavior-wise and and and and so on. Um

and there's some really interesting and so so that's from the perspective of an external observer. Now, the latest uh

external observer. Now, the latest uh the latest work that um that I just published a couple days ago looks at what does that mean from the perspective of the agent themselves and this idea

that you don't you you don't have access to your past. What you have access to are memory engrams, you know, traces of of of past experience that were deposited in your brain and and and possibly in your body that you then that

future you is going to have to interpret. And so that leads to a a kind

interpret. And so that leads to a a kind of scenario where you treat your own memories as messages from your past self. You know, um the idea uh then that

self. You know, um the idea uh then that is that those memories have to be interpreted. You don't necessarily know

interpreted. You don't necessarily know what they mean right away because you're different. You're not the same as you

different. You're not the same as you were, right? Especially over long

were, right? Especially over long periods of time. And this this this comes out very starkly in organisms that change radically like caterpillars to butterfly. So so memories persist um

butterfly. So so memories persist um from from butterfly from caterpillar to butterfly. But the actual uh detailed

butterfly. But the actual uh detailed memories of the caterpillar are of absolutely no use to the butterfly. It

doesn't eat the same stuff. It doesn't

move in the same way. It has a completely different body, completely different brain. You can't just take the

different brain. You can't just take the same memories. And so I think what

same memories. And so I think what happens in biology is that it is very comfortable. In fact, it depends on the

comfortable. In fact, it depends on the idea that uh the substrate will change.

You will mutate your cells. Some cells

will die, new cells will be born.

Material goes in and out. Unlike in our computational devices, the material is not um you're not committed to the fidelity of information the way that that we are. Uh in in our computation you are committed to the salience of

that information. So you will need to

that information. So you will need to take those those memory traces and reinterpret them for whatever your future situation is. In the case of the butterfly, completely different. in the

case of the adult human somewhat different than your brain when you were a child but even even during adulthood uh your your your the context your mental context your your environment

everything changes and I think uh you don't really have an allegiance to what these memories meant in the past you you reinterpret them dynamically and so this gives a kind of view of the self kind of

a process view of the self that what we really are is a continued uh continuous dynamic attempt at storytelling where what you're constantly ly doing is interpreting your own memories in a way

that makes sense about what you know a coherent story about what you are think what you believe about the outside world and and it's a it's a constant process of self- construction so that that I

think is what's going on with selves if it's the case then that we interpret our memories as messages from our past selves to our current selves then can we reverse that and say that our current

actions are messages to our future self yeah I think I think that's exactly Right. I think that a lot of what we're

Right. I think that a lot of what we're doing now is going at any given moment uh is behavior that is going to enable or constrain your future self. You know

uh you're you're setting you're setting the conditions in which the environment in which your future self is going to be living in including changing yourself.

you know, anything you undertake as a self-improvement program or conversely um you know, when people entertain um intrusive or depressive thoughts that changes your your brain that literally

changes the way that your future self is going to be able to process information in the future. Everything you do radiates out not only as messages and um a kind of niche construction, you know where you're changing the environment in

which you're going to live and which everybody else is going to live. We are

constantly doing that to ourselves and and to others. And so that you know um really uh forces a kind of uh thinking

about your future self as kind of akin to other people's future selves. And I

think that also has important ethical implications because once once that symmetry becomes apparent that your future self is not quite you um and also

uh others future selves are also not you. That suggests that the way the same

you. That suggests that the way the same reason you do things so that your future self will have a better life. Uh you

might want to apply that to others future selves. like breaking breaking

future selves. like breaking breaking down this idea that and I'm certainly not the first person to say this but breaking down the idea that you are a persistent object separate from everybody else and and you know sort of

persisting through time breaking that down into uh a set of selves and what you are doing now is basically for the good of a future self I think makes you think differently about others future

selves at the same time. Is it as simple as the larger the cognitive light cone the better for the organism?

Well, what does better mean? I mean, I think that certainly there are extremely successful organisms that do not have a large cognitive lyone. Having having

said all that, you know, the size of an organism's cognitive ly is not obvious.

We are not good at detecting them. Uh

it's a it's an important research program to find out what any given agent cares about because it's not easily um inferable from from measurements directly. You have to do a lot of

directly. You have to do a lot of experiments. So assuming we even know

experiments. So assuming we even know what anything's cognitive lying is uh I think lots of organisms do perfectly well but then what's the definition of

success? So in terms of the way we think

success? So in terms of the way we think about um well the way many people think about evolution in terms of uh you know how many copy number like how many of you are there that's your that's your

success. So so uh but just persistence

success. So so uh but just persistence and expansion into the world from that perspective I don't think you need a particularly large cognitive lyon. you

know bacteria do great. Um but from other perspectives if we sort of ask ourselves what the point is and why do we exert all this effort to exist in the physical world and try to persist and and and uh exert effort in all the

things we do in our lives. One could

make an argument that a larger cognitive lyone is probably better in the sense that it allows you to generate more meaning and allows you to bring meaning to all the effort and the you know the

suffering and the joy and the hard work and everything else. uh from that perspective one would want to enlarge one's cognitive lyone and you know um we collaborate well I collaborate with a

number of people uh in uh in this group called CSAs the the the center for the study of apparent selves and we talk about this this notion of something for example in Buddhism they have this

notion of a body sattva vow and it's basically a commitment to enlarge one's cognitive lyone so that over time one becomes able to have a wider area of concern or compassion, right? It it you

know, the idea is you want to um you want to work on changing yourself in a way that enlarges your ability to really care about a wider set of beings and uh and and so so from that perspective

maybe you want a larger cognitive light.

Okay, so there are three notions here.

So enlarging what you care about, okay then also enlarging what you find relevant. And then there's also

relevant. And then there's also increasing the amount of opportunities that you'll have in the future. So

that's the adage. That's the business adage. Go through the door that will

adage. Go through the door that will open as many doors as possible. And then

the relevance one I don't think is the case because if you find more if you find too much relevant you you will also freeze because you don't know what to do. Now then there's the concern for

do. Now then there's the concern for others. So help me disembroil these

others. So help me disembroil these three from one another. Yeah.

Um the the the relevance is is is I think really important. You know, one thing I often think about is like what's the what's the fundamental unit that uh exists in the world? Is it is it, you

know, is it genes? Is it information?

Like what what is it that's really spreading through the universe and and differentially reproducing and all that?

Uh I tend to think it's perspectives. I

think that what's really out there um as uh as a a diverse as as a way to uh describe really diverse agents, I think I think one thing they all have is

a commitment to a particular perspective. So perspective in my

perspective. So perspective in my definition is a bundle of commitments to um, what, am, I, going to, measure, about, the outside world? Uh what am I going to pay

outside world? Uh what am I going to pay attention to and how am I going to weave that information into some sort of model about what's going on and more importantly what I should do next. So

so there are many many different perspectives and as you said it's it's critical that every perspective has to shut out uh way more stuff than it lets in because right because if you if you act and and and this this interestingly

this gets back to your original point about the different levels of description you know physics and chemistry and all that because if you try to um if you wanted to if you wanted to be a lelassian demon if you wanted to

track microates all the particles right I'm just going to track I'm going to track reality as it really is I'm just going to watch all the particles that's all I'm going to uh no no living system can survive this way right because because you you would

be eaten before anything else happens you would be dead so I think that um I think that any agent that evolves under resource constraint so which is all of

life uh and it remains an interesting question what does that mean for for AIs and so on but any agent that evolves under constraints of of of

um metabolic and time resources is going to have to coarse grain. They're going

to have to not be a reductionist.

They're going to have to tell stories about agents that do things as a means of compression, as a way of compressing the outside world and picking up perspective. You cannot afford to try to

perspective. You cannot afford to try to track everything. It's impossible. So uh

track everything. It's impossible. So uh

that that aspect that that compression also comes back to the um the memory engrams issue that we were talking about because as your past self compresses

lots of diverse experiences into a compact representation right of of a memory trace of what happened that kind of learning is fundamentally compression where you're you're compressing lots of

data into a you know into a short piffy generative rule or or or or a uh you know a memory that you're going to remember that you can use later, Right?

So not the exact uh um experiences that you had but but but some compressed representation. Well, the thing about

representation. Well, the thing about compression is that um the most efficient uh the the data that's compressed really efficiently

starts to look random, right? So because

because you've you've gotten rid of all the correlations and everything else, uh the more you compress it, the more random it looks and you've really gotten rid of a lot of metadata uh that you you have to that's the point of of

compression. you've lost a lot of

compression. you've lost a lot of information. Wait, why do you say that

information. Wait, why do you say that the more compressed it is, the more random it is? Why isn't Isn't it the opposite? But the more random it is, the

opposite? But the more random it is, the more incompressible it is. That's true

because you've already compressed the hell out of it. That's that's why right? That that's why it's

right? That that's why it's incompressible because you've already compressed it as much as it can. This is

this is the issue that for example the STI people right the search for extraterrestrial intelligence that they come uh come up against because uh the messages that are going to be sent by truly advanced civilizations are going

to look like noise to us because because um really effective compression schemes uh unless unless you know unless you know what the what the de so so you've you've you've um compressed it unless

you know what the algorithm is to reinflate it the message itself looks like like noise. It doesn't look like anything because because you've you've pulled out um you've pulled out all of the correlations. All of the order that

the correlations. All of the order that uh that would have made sense uh to a more naive observer is now gone. And if

you don't have the key to interpret it with, it just looks like noise. And so

that means that if you sort of think about this um there's a there's an architecture like a like a bow tie like a bow tie kind of architecture that's important here where you take all these experiences, you compress them down into

an engram. That's your memory. And then

an engram. That's your memory. And then

future you has to reinflate it again and figure out okay so what does this mean for me now right it's it's a simple rule that I inferred let's say you learned an associative learning task or or some kind of you know you've learned

something general you've learned a to to count you know a number or or something like this so you know so rats I think it takes about if I recall correctly like like 3,000 trials before they understand

the number three that's that's distinct from any instance so it's not like three peanuts or three you know sticks it's like the number three of anything Right?

So after, you know, some thousands of trials, they get it. And so now they have this this compressed rule. They

don't remember the sticks or the or the or the peanuts or whatever, but they they uh they remember the actual rule to to right. And so that's the engram at

to right. And so that's the engram at the center of your bow tie. Well, future

you has to has to reinflate it. Has to

has to uncompress it and expand. Okay.

But now I'm looking at three flowers. Is

that the same or not? How do I how do I apply my rule to this? And I think that um what's important is that you can't do that deductively because you're missing

a lot of that basic information. You you

you have to be creative when you um interpret your own engrams. There's a lot of uh creative um input that has to that has to come in to understand what it was that you were thinking at the

time. And I think that um that kind of a

time. And I think that um that kind of a thing I mean I mean we know that that recall of memories actually changes the memory, right? So, so in neuroscience

memory, right? So, so in neuroscience they know this that that there's no pure non-destructive reads of of memories that when you access your memory you change it. And I think that's why

change it. And I think that's why because the active interpretation is not just a passive u reading of of what's there. It's actually a construction

there. It's actually a construction process of trying to recreate. So so

what does that mean for me? What does it what does it mean now? And and that's that's part of that that process of the of the of the dynamic self, you know, is is trying to figure out obviously all this is subconscious, but but trying to

figure out um what your own memories mean. Yes. Okay. So you said obviously

mean. Yes. Okay. So you said obviously much of this is or maybe obviously all of it or much of it I'm not sure is subconscious. So when we say you

subconscious. So when we say you currently are constructing an engram for the future you to then unpackage, I, am, not, doing, this, at least

not at a effortful conscious level there's an instinctual unconscious component to it and then both to the encoding and then to the retrieval and

the expansion of the engram. Yeah.

So who the person who's listening to this, they listen to these podcasts they listen to theories of everything in large part because they're trying to understand themselves. They're

understand themselves. They're interested in science. They're

interested in philosophy. You're also

speaking to them now with this answer to this question. Who are they? They're

this question. Who are they? They're

listening to this and they're saying "I'm doing this. I don't I'm not aware.

This is all news to me, Mike. You're

saying I've been doing this my whole life and this defines me. this doesn't

sound anything like me. So who are you?

Who are you, Mike? And who is the person who's listening? What defines them?

who's listening? What defines them?

Well, so, so a few things. So the fact that there are an incredible number of processes under the hood has been known for a really long time. So, so not only all the physiological stuff that's going

on, I mean, you also don't have the experience of running your liver and your kidneys, which are very necessary for your brain function. um you are also not aware of all the uh subconscious

motivations and uh and and patterns and traits and everything else. So so let's let's let's assume right now that that um whatever our conscious experience is there is tons of stuff under the hood not not just the the thing that I just

said but everything else that neuroscience has been studying for for you know for 100 years or more. Uh

there's lots going on under the hood and that doesn't define you. It enables you to do certain things. uh it constrains you from doing certain other things that you might want to do. Um the hardware

does not define you. Uh I think the most important thing and look I I think this is a really important question because I get lots of emails from people who say I I've I've read your papers. I understand

that I'm now that now I understand I'm a collective intelligence of groups of cells. What do I do now? I I don't know

cells. What do I do now? I I don't know what what to what to do anymore. Right?

And my answer is do whatever amazing thing you were going to do before you read that paper. like all all of this information about what's under the hood is interesting and it's and it's and

it's um you know it has all kinds of implications but the one thing it does not do is diminish your responsibility for uh living the best most meaningful

life you can it it doesn't affect any of that and um uh one way I think about this and there's lots of sci-fi about this but one one thing that uh you might remember is you seen the the film

Xmachina yes and so and So, there's one scene there where uh the protagonist is standing in front of a mirror and he's completely freaked out because the AI is

so lifelike he's now wondering maybe he's a robotic organism too. And so, so he's, you know, he's he's cutting his hand and he's looking in his eye and he's trying to figure out what he is.

And so, so let's let's just dissect that for a minute. Um, the reason he's doing this and and what happens to most people, which I think is quite interesting, is that if if they were to

open their their arm and they find a bunch of cogs and gears inside, I think most people would be super depressed because what they would because I think where most people go with this is, I've

just learned something about myself.

Meaning, I know I I know what cogs and gears can do. They're a machine and I just learned that I'm full of cogs and gears. Therefore, I'm not what I thought

gears. Therefore, I'm not what I thought I was. And I think this is this is a

I was. And I think this is this is a really unfortunate way that uh a really unfortunate way to think because what you're saying is your experience of your

whole life. And um all all of the all of

whole life. And um all all of the all of the joys and the suffering and the personal responsibility and everything else that you've experienced, you're now willing to give all that up because you think you know something about what cogs and gears can do. I would go in the

exact opposite direction and I would say, "Amazing. I've just discovered that

say, "Amazing. I've just discovered that cogs and gears can do this incredible thing. Like wow. And and and why not?

thing. Like wow. And and and why not?

Because because why do you think that proteins and um uh you know the ions and proteins and the various things in your body th those are those are great for true cognition. I like like I always

true cognition. I like like I always knew I was full of you know protein and and and lipids and ions and all of those things and that was cool. I was okay with being that kind of machine but cogs

and gears no you know no way, right? And

so I so I think one thing that that we get from uh from our education um uh focused on certain kinds of materialism is that we get an idea we get this uh

unwarranted uh confidence in what we think different materials are capable of and and we believe it to such an extent.

I mean, I I find this amazing as a kind of a, you know, an educational or sociological thing that uh we we we we embibe that story so uh

strongly that we're willing to then give up everything that we know about ourselves in order to stick to a story about um materials. I I think I think that's you know the one one thing that I think Decard had really really right is

that uh the one thing you actually know is that you you are uh an agentic being with with responsibility and and a mind and and all these um you know and all

this potential and whatever you learn uh is is is is on the background of that.

So if you find out that you are made of cogs and gears, all you should conclude is well great uh now I know this stuff can do it as well as proteins can. And

so so so from that so so what I really hope um that people get from this is simply the idea that pretty much no discovery about the

hardware, no discovery about the biology or the physics of it should uh pull you away from uh the the the fundamental reality of your being. that whatever it

is that you are uh you know groups of cells, an emergent um you know an emergent mind pulled down from platonic space or what whatever which whichever of these things are correct. Uh the

bottom line is you you you are still uh the the the you know the amazing integrated, being, with, with with potential and a responsibility to to do

things. Um

things. Um Uhhuh. So many people who dislike

Uhhuh. So many people who dislike materialism and like the more whatever they consider to be not materialism. So

could be idealism, it could be spiritualism or whatever they want to call it or non-dualism or trialism instead of a dualism. In part what

they're saying is look I'm not material because they denigrate the material and they view it as robotic lifeless. But

you're saying there's another route. If

you are material whatever it is you turn out to be you can elevate that. So you

can say look there's there's a dynamism to it. There's an exuberance. There's a

to it. There's an exuberance. There's a

larger than lifeness to the what I previously thought was oifying.

Yeah. For for sure. And Ian McGillchrist makes a point of this too. He says that uh we've we've underestimated matter.

You know, when when we talk about materialism, we we uh have been sold and are selling still uh this notion of um

of of matter as uh lacking intelligence.

And I think that we need to give up this unwarranted confidence in uh what we think matter can do. We we we are finding novel uh protocognitive

capacities in extremely minimal systems. Extremely minimal systems and they're surprising to us. They're they're

shocking to uh when we when you know when we find these things and I think we uh are are really bad at recognizing uh what kinds of systems can give rise to minds and therefore being depressed

because we think that we are a particular kind of system and there's no way that system can be this this you know majestic agentic being it's it's it's way too early for that. uh we just

we absolutely I mean this is this is one of the I think the major things is that we have this we have this idea that that we know what different kinds of matter can do

and and obviously I'm not I'm not just talking about you know homogeneous blocks of material I'm talking about uh specific configurations but but but really minimal kinds of things can have

some very surprising uh cognitive qualities, and, so, um, yeah, it's, it's it's it's way too early to to think that we know what's going on here. I think we

have a record here of 45 minutes of recording or so and we haven't mentioned the word bioelect electricity once. So

kudos to you, kudos to me. How the heck did that happen for a Michael 11 interview? So what does bio electricity

interview? So what does bio electricity have to do with any of this? Yeah. So so

bioelect electricity uh is not magic. It

is not unique in the sense that uh there are probably certainly out in the universe there are probably other ways of doing what it does but what it does here on earth in the bi in the um in

living forms is something very interesting. It functions as a kind of

interesting. It functions as a kind of cognitive glue. So when you when you

cognitive glue. So when you when you have collective intelligence, you need to have um you need to have policies and you

need to have mechanisms for enabling individual competent individuals to merge together into a larger emergent individual that's going

to do several things. First of all, the larger network, the larger um level is going to distort the option space for the lower levels. So the parts are doing things that the parts do but they're now

doing it in a way that uh that is coherent with a much higher level story of what's going on higher level goals because that their their action landscape is bent. It's distorted by the larger level. Their perception their um

larger level. Their perception their um their uh you know energy landscape is is is distorted. So uh that collective is

is distorted. So uh that collective is going to that that new self is going to have memories, goals, preferences, a cognitive like that's that's that that

requires some some um some some very specific features and there are a bunch of them and one of the uh modalities that lets that happen that lets the cognitive light cone scale that lets the

the intelligence scale is bioelect electricity. So by taking uh cells and

electricity. So by taking uh cells and enabling them to be part of an electrical network, there are some really interesting larger level dynamics which you know this is what we exploit

in in artificial neural networks of course right this is this is but biology noticed this since the time of bacterial biohilms that uh electricity is just a really good way for higher level cells

to emerge and higher level computation to emerge. Um there are probably other

to emerge. Um there are probably other ways of doing it but but here on earth by electricity is tends to be the way to go. Something I always wonder in

go. Something I always wonder in conversations about our higher selves lower selves, higher goals. How do we even say higher or lower when what we're talking about is such a vast landscape

of goals or cognitive light cones in a higher dimensional space where the real number line is the only continuum that has an an ordering to it. As soon as you

have the complex numbers or R2 or R3 etc., there's no you can't pick two points and say one is higher than another. Yep. Yep. unless you implement

another. Yep. Yep. unless you implement other structure. So, what is it that

other structure. So, what is it that allows us to say higher or lower? Uh

bad vocabulary. You're you're 100% right. Um, the the only thing that

right. Um, the the only thing that matters here because because it doesn't necessarily mean the next level up is not necessarily smarter than the lower level usually, but but that doesn't guarantee that at all. Um, not

necessarily bigger or smaller in physical scale. So the only thing I mean

physical scale. So the only thing I mean by and we we really don't have a great vocabulary yet for all this stuff but but the only thing I mean by hire is uh something akin to set membership just

the fact that a tissue is made up of cells and cells are made up of molecular networks. That's it. That that's all I'm

networks. That's it. That that's all I'm talking about. I'm not saying that it's

talking about. I'm not saying that it's bigger or or or more intelligent or more valuable. What all I mean is is that um

valuable. What all I mean is is that um in a in this um in this hierarchy certain things are made up of other things. That's it. That's that's that's

things. That's it. That's that's that's all I mean.

Earlier when defining intelligence, I believe you said William James' was something about ability but also means.

So ability to generate multiple paths to a single goal. I don't know if it was also the ability to have multiple goals but we can explore that. But let's pick out a goal then you can generate

multiple paths to that goal. Many many

ways of executing. But then you also I believe you said the means too as well.

Is that correct? Yeah. the the means in in James's at least the way I read him uh in James when he says means he means the path that that is the path a means to an end right it's a path that takes

you to that end so you know this is the kind of stuff um we see in biology just you know just to give you an example um one thing that people often think when when they hear me talk about the

intelligence of development and so on people often think I mean the complexity right just the fact that that you start from an egg and you end up with I don't know a salamander or something that there's an increase in complexity and then you And then then rightly people

think well that's just you know uh there's there's lots of examples where simple rules give give rise to complex outcomes that's just emergent emergent complexity that's not intelligence and they're right that is not what I mean

that's not intelligence what I mean by intelligence is the problem solving of the following kind. So let's say you uh you have a you have a sal you have a an egg belonging to a salamander. One of

the tricks you can do is is um prevent it from dividing while the genetic material is is copying. And so you end up with polyloid nootes. So so instead of 2N, you can have 4N, 5N, 6N, 8N, that

kind of thing. Well, what happens when when you do that, what happens is the cells get bigger in order to accommodate the extra genetic material, but the actual salamander stays the same size.

So if you take a cross-section, so let's say we take a cross-section of a little um tubule, a kidney tubule that go, you know, runs to the kidneys, normally there's like eight to 10 little cells that go in the circle to um to to to make that tuble and then there's a lumen

in the in the middle. So if you make the cells gigantic, the first thing you notice is that well first of all having multiple copies of the genetic material you, still, get, a, normal, noot., So that's pretty amazing already. Second amazing

thing is when the cells get the cells uh scale to the um to the amount of genetic material. So the cells get get larger.

material. So the cells get get larger.

That's amazing. Then you find that well actually since the cells are really big uh there's the only only a few of them are now working together to make the exact same size tubule. So they scale

the number of cells to make up for the aberrant size of the cell. Right? That

makes sense. And then and then the and then the the the most amazing thing of all happens when you make truly gigantic cells. There's not even room for more

cells. There's not even room for more than one. One cell will bend around

than one. One cell will bend around itself leaving a lumen in the middle.

The reason that's amazing is that that requires a different molecular mechanism. That's cytokeleletal bending

mechanism. That's cytokeleletal bending whereas before you had cellto cell communication. And so that is that that

communication. And so that is that that kind, of, thing,, right?, So, so so, just think about this. You're a nuke coming into the world. You have no idea. You

can't count on how much genetic material you're going to have, how many cells you're, going to, have,, what, size, cells you're going to have. What you do have is a bunch of cool tools at your disposal. You have cytokeleletal

disposal. You have cytokeleletal dynamics, you have gene regulatory networks, you have biologicity, you have all this stuff. And what you're able to do under totally novel circumstances is

pick from your bag of tools to solve the problem. I go from an egg to in in

problem. I go from an egg to in in morphospace, I take this journey from an egg to a proper noot. Not only can I not count on the environment being the same I can't even count on my own parts being

the same, right? That kind of that kind of um uh you know, another way to to call this attitude is uh is is is beginner's mind. It's like you you don't

beginner's mind. It's like you you don't overtrain on your priors, on your evolutionary priors. You have a bag of

evolutionary priors. You have a bag of tools and you're not just a fixed solution. This is this is why I think

solution. This is this is why I think evolution doesn't just uh produce solutions to specific environmental problems. It produces problem-solving agents that are able to use the tools they have. I mean, what what's a what's

they have. I mean, what what's a what's a better example of intelligence than something that can use the tools it has in novel ways to solve a problem it's never seen before, right? Like that that is that is a version of intelligence.

And um and that's, you know, that's what that's what is uh all over the place in biology. The the ability to navigate

biology. The the ability to navigate these pathways, not only to avoid to avoid various barriers and and so on but to use the tools available to them

in creative ways to solve the problem.

And we see some of this in extremely minimal systems. It does not require a brain. Doesn't even require cells. Uh

brain. Doesn't even require cells. Uh

very minimal systems have surprising problem solving capacities. And this is why we should be extremely humble when we try to make claims about what something is or isn't or what um

competencies it has. We are not yet good at recognizing those things. We do not have a mature science yet of knowing what uh what the properties of any of

this stuff is. See, the tricky part with this definition of intelligence, help me out with this, is that what we want to say is that it's conceivable that the

kid from Saskatoon, the poor kid, is more intelligent than the rich kid from the Bay Area. So that's

conceivable. But the rich kid has far more means, far more ability to achieve their goals. So if there was implement

their goals. So if there was implement implementability within the path. So if

we say look the ability to generate paths that are realizable is in part what defines the the IQ or the intelligence. Well the

poor kid from Sas Saskatoon has less raw material to play with to generate a path. So how do we how do we avoid

path. So how do we how do we avoid saying unless you want to say which I don't imagine you want to say. How do we avoid saying that the poor kid from Saskatoon is just by definition less

intelligence by by happen stance than the person from the Bay Area? Yeah. The

the thing the thing to keep in mind here is that um estimates of intelligence and and I think all cognitive terms so everything about um you know what all the words that people use sensience

cognition goal directedness all of them uh I think we have to remember that those are not objective properties of a given system. IQ is not the property of

given system. IQ is not the property of whatever system you're trying to gauge the IQ of. It is your guess, your best guess about what kind of problem solving you can expect out of that system. So

it's as much about you as it is about the system. And we've shown this in our

the system. And we've shown this in our experiments a lot of times that when people talk about certain kinds of developmental constraints or they talk about the competency of tissues to do one thing or the other, it it's it's

much more about our own knowledge of the right stimuli and the right um ways to communicate with that system and not so much about the system itself. When you

make an estimate of the of of the intelligence of something, you are taking an IQ test yourself. All you're

saying is this is what this is what I know in terms of and this is what I can see in terms of what kind of problem solving I can see and this applies to to to animals. This

applies to AIS, this applies to humans in various economic environments. Um you

know this this the simple version of this is uh you show somebody a a human brain and they say that's a pretty awesome paper weight and I can see that it, can, do, you, know, at least, action, and hold down my my papers against gravity

and that's all I think it can do. and

somebody else is you've missed the whole thing, right? Like this thing does all

thing, right? Like this thing does all this other stuff. So I I I I think that uh that that type of um mistake where a we think that it's an objective property

of the system and b that we think that we're good at as at at determining what that is is what bites us uh a lot when we're when we're dealing with especially unconventional systems. So if someone So

so to use your example, if someone looks at at a kid with that environment and says, "Well, I I I don't I don't think this kid has has much intelligence, the problem isn't on the side of the kid.

The problem is that somebody else might come along and says, "Oh, you don't get it." In a in a in a different

it." In a in a in a different environment, it would that, you know this this kid would would, you know exhibit all these amazing behaviors. um

the you know the the good news about all of this uh and and you know I'm certainly not it's not in my wheelhouse to comment on any of the um kind of economic stuff or the sociology of it

but, for, the, for, the, biology, and, and and for the um computer science and so on um the good news is that all of these things are empirical empirically

testable. So when when we come across a

testable. So when when we come across a certain system um each of us is going to guess what is the problem space it's operating in what are its goals and what

capabilities do we think it has to reach those goals and then we do the experiment and then we see who's right that's the thing that this is not a philosophical debate this is absolutely experimental so if you say I don't think

these cells have any intelligence u uh you know I think they're just a feed forward um emerging dynamics and I think oh no I think they're actually minimizing or maximizing some particular thing and they're clever about doing it.

We do the experiment. We put a barrier in their place in the you know between them and their goals and we actually see do they or do they not have the what I claimed to to you know uh to be their their competency and then we find out

how much each of our views lets us discover the next best thing. So these

are all empirically testable kinds of ideas. So before we get to consciousness

ideas. So before we get to consciousness and 11 labs I want to talk about cognition. So in 2021 or so you had a

cognition. So in 2021 or so you had a paper called reframing cognition. H okay

something akin to that. Yeah that sounds like uh I think that might have been a review with um Pamela Lion maybe. Yeah.

And then on page 10 section five something like that you defined or you started talking about basal cognition and uncavotted cognition. So what do

those terms mean?

uh to be completely honest I don't remember this part uh I' I mean I yes I certainly don't remember the pages or the basil cognition yeah I mean ba so okay so so the idea for basil cognition

is basically that whatever cognitive capacities we have they have to have an origin and we have to ask where did they come from because this idea that um you know we are completely unique and they

suddenly sort of snap into into place it doesn't it doesn't work evolutionarily and it doesn't work developmentally both of those are very slow process processes. So the stories we have to

processes. So the stories we have to tell are stories of scaling. They're uh

to really understand these processes, we have to um understand how how simple information processing capacities scale up to to become larger cognitive lyans more intelligent systems, project into

new problem spaces and so on. So basil

cognition is the question of okay so where did our cognitive capacities come from? So that means looking at uh the

from? So that means looking at uh the functional intelligence of cells tissues, slime molds, um microbes bacteria, um and and minimal matter, you know, active materials, that kind of

stuff. That's that's basil cognition.

stuff. That's that's basil cognition.

Well, what do the primitive what do the really primitive versions of of cognition look like? And it and it's a really important skill to um to to to practice that kind of uh imagination

because often what trips people up is uh they they imagine for for example uh for example pansychist views right so somebody says oh you're trying to tell me that this rock um you know is sitting

there having hopes and dreams well no that's not the claim the claim is that the claim isn't that that these these full-blown largecale cognitive properties that you have are exactly there everywhere else The claim is that

it's a spectrum or a continuum and that there are primitive tiny versions of them that are also should be recognized because we need to understand how they scale. So that's that's that's basil

scale. So that's that's that's basil cognition. So if it's a spectrum, I hear

cognition. So if it's a spectrum, I hear this plenty. Look, I'm not saying

this plenty. Look, I'm not saying someone will say I'm not saying everything is conscious. It's a

spectrum. It's not on off. But then to me, can't you just define onoff to be if you have a nonzero on the spectrum, then you're on? Like for instance, you don't

you're on? Like for instance, you don't say you say a particle has electric charge. Is it electrically charged?

charge. Is it electrically charged?

Well, it's on the spectrum. Yeah. If it

has a nonzero amount, you call it electrically charged. If it's zero, then

electrically charged. If it's zero, then you say it's neutral. So, can't you just say then that yes, The Rock does have hopes and dreams, even if it's at

0.0000.2% of whatever you have. Well, I

I personally am on board with that. I I

think, you know, I think I think potential energy and and least action principles are the tiniest hopes and dreams that there are. Uh I so so I agree with that completely. I think that

is the most basil version and in our universe. So, so I don't this goes way

universe. So, so I don't this goes way beyond my pay grade, but but for example, I've talked to Chris Fields who who uh is really an expert in this stuff. And I asked him, is it possible

stuff. And I asked him, is it possible to have a universe without least action laws, right? And he said the only way

laws, right? And he said the only way you can have that is if nothing ever happens. So if that's if if that's the

happens. So if that's if if that's the case, that tells me that in our world there is no zero on the on the cognitive scale and everything is on it. But but

with but again, we have to we have to ask then. So So I agree with you. I

ask then. So So I agree with you. I

think I think I think if you're on the spectrum then then you're on and that's it. And I think in this universe

it. And I think in this universe everything is on. But we have to ask ourselves what do we want this terminology to do for us? So uh that's that's why some people critique these

kind of perspectives by saying well then if if everything is on it then the word means nothing then why you know why do we why do we even have the word because everything is if everything is cognitive and I didn't say consciousness yet but but let's say let's say everything is

cognitive then then why do we need the word everything is and I I really think that we need to focus on what we expect the terminology to do for us. So let's

let's imagine let's just dissect this for a minute. Um the old uh paradox of the heap, right? So you got a you got a pile of sand and you know you know that if you take off one little piece of sand, you still got a pile, but

eventually you have nothing. So So what how do you define the pile? So I I think for all of these so so my answer to this and I think the solution to all of these kinds of uh terminological issues is

that it's not about the object itself.

It's about what tools you're going to use to interact with it. So if you call me and you say I have a pile of sand all I want to know about the definition of pile is am I bringing tweezers, a

spoon, a shovel, a bulldozer, uh dynamite, what how are we like what are what are the tools that I have to do what we need to get done. So that is the only value in in these in this in this

terminology. So you know by saying that

terminology. So you know by saying that everything is cognitive does that by itself help us with anything? No. I

think what does help is if you tell me what kind of cognition and how much and that's an empirical question and then we can argue about it and the answer to that question is what are the tools that help us the most. So you show me a bunch

of cells and you say I think this uh the the right way to do this is um physics chemistry and uh feed forward emergence and complexity. That's how I think we're

and complexity. That's how I think we're going to interact with it. and I look at it and say I I think the way to interact with this is through some interesting concepts from cognitive neuroscience including active inference learning

training and so on then we get to find out who's right you know if I if I if I can show that using my concepts I got to new discoveries that you didn't get to there you go on the other hand if I

waste all my time you know writing poems to a rock and and nothing ever comes of it well then you're right and so and so I think that um uh the point of all this terminology yes we can say It's all on a

spectrum. But now comes the fun and

spectrum. But now comes the fun and interesting work of saying, okay, so what does the spectrum look like? And

where on the spectrum do the various things that we see land? Okay, let's get to consciousness.

land? Okay, let's get to consciousness.

I want to say that I I don't agree with Chris Fields about the principle of least action because firstly people say the universe is lazy. But you can also put a minus sign and say the principle

of most of maximum effort. Okay. But

then also there are many there are many quantum field theories that aren't based in lrangeians to minimize. So there's algebraic

to minimize. So there's algebraic constructive axiomatic and categorical and then there's there's this whole there's a new video that actually got released a couple days ago by Gabriel

Carassie and I'll put the link on screen which says there's a distinction between Newtonian lrangeian and Hamiltonian mechanics. So Hamiltonian is more about

mechanics. So Hamiltonian is more about flows. You just watch the flow of a

flows. You just watch the flow of a system. Lrangeian is the one where you

system. Lrangeian is the one where you minimize and then Newtonian there's actually some Newtonian systems F equals MA that you can't map to a to Hamiltonian system. So I I have a bone

Hamiltonian system. So I I have a bone to pick with Chris Fields. You should

have him on. This is the you know this is getting way beyond anything I could argue with you about. But you should have him on and you guys could talk. I I

would watch that for sure. We had a three-way discussion again a plug here with Michael Leven, Carl Fristen, and Chris Fields. That was fun. Yeah. Yeah.

Chris Fields. That was fun. Yeah. Yeah.

Okay. So many people want to know what is your hunch at which see there are various interpretations of quantum mechanics., We're, not, going to, go, there

mechanics., We're, not, going to, go, there but there are various theories of consciousness in the same way there there's a litany there's a litany. Which

one do you feel like is on the right track? Well let's see. Um I can say a

track? Well let's see. Um I can say a few things. Uh I what what I definitely

few things. Uh I what what I definitely don't have yet. I'm working on it but I don't have anything that I would I would talk about now. uh a a new theory of consciousness. So I do not have uh

consciousness. So I do not have uh anything brilliant to add to this that somebody else hasn't already said. So

I'm just going to kind of tell you what what I have to say now. Sure. Um I I think that uh one one thing that's really hard

about consciousness and what makes it the hard problem is that unlike everything else that we work with, we don't have any

idea what a correct theory would output.

So what would the what format would the predictions? Sorry, we don't have an

predictions? Sorry, we don't have an idea of what the correct theory would look like. No, no, no, no. We don't have

look like. No, no, no, no. We don't have a correct uh we don't have any idea of what the output of a correct theory would look like. What would it give you?

Right., So, so so, for, everything, else,, the correct uh a good theory gives you numbers, you know, predictions about specific things that are going to happen. What does what does a good

happen. What does what does a good theory of consciousness give you? So

um, you know, what what we would like is something that, you know, we we say "Okay, here's a here's a cat or here's a cat with three extra brain hemispheres grafted on that also has wings. What is

it like to be these these creatures right? What what is the output of a

right? What what is the output of a correct theory of consciousness?"

Because because if it outputs uh patterns of behavior uh or physiological states, then what you've explained is physiology and behavior. There are going to be people say to that say, "Well, you haven't explained the the consciousness

at all." In fact, almost all theories of

at all." In fact, almost all theories of consciousness look like elim look kind of eliminativist. Even the ones that

of eliminativist. Even the ones that aren't trying to be, even the ones that say, "No, no, we're not trying to explain away consciousness. It's real

and I'm going to explain it." Then you look at the explanation and you always feel, like,, "Yeah,, but, but but, you haven't explained the actual, you know the the actual consciousness. You've

explained some kind of behavioral propensities, physiological states, or whatever." So, so that's the problem

whatever." So, so that's the problem that we have. Consciousness is the one of those things that cannot uh exclusively be studied in the third person. Everything else you can study as

person. Everything else you can study as an external observer and you don't change much as the observer by by studying them. Consciousness you can

studying them. Consciousness you can really only you know in a full way you can only study consciousness by being part of the experiment by by by seeing by experiencing it from the from the

first person perspective. So the weak version of this is you might say well a good theory of consciousness is is a kind is art. what it outputs is art poetry, whatever that when we experience it, it makes us experience that

conscious state and we say, "Oh, so that's what it's like. I see." Right?

So, so that's that's one that but that's kind of a weak form. You can do a stronger form and you say, "Well, the real way to do it is to have a rich brain interface." So, if I want to know

brain interface." So, if I want to know what some other system is is what its consciousness is like, we need to fuse together. Now, caveat to that is you

together. Now, caveat to that is you don't find out what it's if you do that you know. So, so let's say a rich um

you know. So, so let's say a rich um some kind of brain interface, you know we we re really connect our brains together or something. You don't get to find out what it's like to be that system. You find both of you find out

system. You find both of you find out what it's like to be a new system composed of the two of you. So, it's

still not So, from that perspective, uh it it's it's really hard. I mean, you know, people I suppose people who do meditation or take psychedelics, I suppose they're doing experiments in actual consciousness, but but third

person experiments in consciousness are really hard. You can do things like turn

really hard. You can do things like turn it off, you know. So there's general anesthesia and you can say oh look uh you know the consciousness is gone. Um

and and even and even then some people will say yeah but I experienced you know floating above my body while you did the surgery and I you know when I saw you drop the scalpel and do this or that. So

so it's still you know even even with that amazing reagent of being able to supposedly shut off consciousness you still, got, some, issues., So so, so, the study of consciousness is hard for those

kinds of um for those kinds of reasons.

Um and uh I I think that about the only useful thing I could say here is that for the same reasons that we associate consciousness with brains, for exactly

those same reasons, we should take very seriously the possibility of other forms of consciousness in the rest of our bodies and and also lots of other things. But um you know we and and so so

things. But um you know we and and so so I'm working so Nick Rolo and I are working on a on a paper on this where you can sort of look at all the different popular theories of consciousness on the table and you can

just ask which of them are specific for brains and why like what what what aspects of each of those theories really tells you that it's got to be brains. My

guess is we haven't finished the paper yet but my guess right now is that there's not a single one that can distinguish brains from other uh other other types of um structures in your

body. And so I think we should take very

body. And so I think we should take very seriously the possibility that other subsystems of the body have some sort of consciousness. It's not verbal

consciousness. It's not verbal consciousness. Um sorry I'm not

consciousness. Um sorry I'm not understanding. Are you saying what if we

understanding. Are you saying what if we list all the theories of consciousness and then we place does it distinguish the brain as being responsible for consciousness? Yeah. We ask what what is

consciousness? Yeah. We ask what what is it about that theory that says it's in the brain rather than somewhere else?

Let's say your let's say your liver. So

IIT would say no because IIT is a pansychist theory that would say look if your liver is doing some processing then it has some non-zero amount of consciousness. Right. Right. And I and I

consciousness. Right. Right. And I and I agree with that. Now now now now as far as I as far as I understand IAT also has an exclusion postulate that says there should only be one central consciousness

in the in the system. I I think that's true. At least it used to be true. Um I

true. At least it used to be true. Um I

don't know, Julio, may, may, disagree, with that, but, uh, but, but but, I, think, we, are actually a um uh a collection of interacting uh perspectives and

interacting consciousnesses for that for that reason. And uh you know then

that reason. And uh you know then sometimes people say well I don't feel my liver being conscious. Right? You

don't uh but you don't feel me being conscious either. Of course you don't.

conscious either. Of course you don't.

and and the fact that your left hemisphere has the the the language ability for us to sit here and talk about it and the the the the liver doesn't doesn't actually mean that it's not conscious. It just means that we

not conscious. It just means that we don't have direct access to it and we don't have direct access to each other.

So that doesn't that doesn't bother me.

Um so I that's that's my suspicion about about consciousness is that for for the same reason that people think it's in the brain, we should take very seriously that it's in other places in the body.

Okay. And then and then more more generally uh you know um other other types of constructs that are not human bodies at all or not even animal bodies.

You've spoken to Bernardo Castrop several times now. What is it you agree with him the most that you think most people would disagree about? Cuz you

agree with him that it's nice to go for a walk. Okay, sure. But most people

a walk. Okay, sure. But most people agree it's nice to go for a walk. So

what is it that you agree with him about that you think is a contentious issue to most people? So, this isn't this is a

most people? So, this isn't this is a controversial statement. And then what

controversial statement. And then what is it you disagree with him about regarding consciousness?

Yeah, boy. Uh I don't you know, it's hard for me to know what most people agree or disagree with him about. I I

really don't know. Um we we we agree on a lot of things. We agree on I think the primacy of of of consciousness. Uh I I think that uh you know his his idealist

position has a lot of uh a lot to recommend it. the the one one thing I

recommend it. the the one one thing I think we disagree on is um the issue of compositionality. So if I recall

compositionality. So if I recall correctly from from a talk that we had together a little while ago, he felt that uh it is important in order to be a true self to be a to be to to have a

conscious experience as an inner perspective. um you have to be you know

perspective. um you have to be you know he he he focuses on the view of um embryionic development as a single system that you know whatever subdivides and develops but it but it starts out as

a single system and I was arguing that that really is just a um uh a contingent feature of biology. I mean we certainly can take two two early embryos and mush them together. You get a perfectly

them together. You get a perfectly normal you know embryo out of it. And in

general, there are lots of biological systems like our our xenobots, like uh like anthrobots that you can you can create by composition, by pulling other things together. So I I don't give as

things together. So I I don't give as much um I I don't put as much emphasis on a system being demarcated from the outside world because it was somehow uh because it started out that way and it

sort of remained uh you know disconnected. I I I think those are I

disconnected. I I I think those are I think, that's, kind, of a, superficial aspect of the biology and you can do things a different way. I don't think that's what um what's responsible for.

But but he he you know I yeah I think he thinks it's important that that individual selves are not um compositions. They're not made as

compositions. They're not made as compositions. they're they're somehow um

compositions. they're they're somehow um you know individualized from the word go which again even the egg right so so we I mean we we humans like eggs because we can see it as a distinct little thing

with a membrane you say ah this you individual but but but even an egg is composed by the maternal organism from molecular components like I I see I see no no point at which any of this is is

truly distinct from from anything else so so I put less emphasis on it but I but I think he thinks it's important it seems like the point that you're saying is look we can think about this is several rooms. This building comprises

several rooms. But even in and Bernardo may say that's what makes a person is the distinct rooms. But you're saying yeah, but even in a room there are different people. There are different

different people. There are different chairs. There are different tables. Is

chairs. There are different tables. Is

that what you're saying? What I'm saying is and and I you know I may not be doing justice to his view and I think I think you should ask him more about this but um I think he thinks that it's important in order to be a unified so so I think

we were discussing what makes for a unified inner perspective right so so we don't feel like billions of individual brain cells I mean I have no idea well we kind of do because that's what it feels like to be billions of individual

of neurons that's really what it feels like but um but we do feel at least mo most of us most of the time feel like some kind of unified centralized inner perspective. And so we were talking about how that comes about

and I think he felt that having that in in the physical universe is uh importantly related to um arising from a single origin a sing so he sees the egg

as a single point of origin and and arising from that that's how you are a separate individual from others and I see it as much more fluid and I see the boundary between self and world as something I can change all the time. I

think it changes in embryogenesis and that's the scale of that's the story of the scaling of the cognitive lyon that we talked about. I think it can shrink during cancer. Uh I think it can change

during cancer. Uh I think it can change during metamorphosis during maturation.

Um I I think I think it's much more fluid than that. Now, as we're on speculative ground, if what makes an agent is the distinction between the self and the world, and some people think of God as the entirety of

everything, thus the entire world, and there's no distinction, then can one say that God is an agent?

I I don't know. I I mean certainly I think most uh well religions that have a that have a god anyway as far as my understanding is they would think that yes the god has uh extreme agency in

fact higher than than ours. I I I don't know what that really buys us um you know in any in any helpful way. Um

remove the word god. Does the world have agency? Okay. So so that's an

agency? Okay. So so that's an interesting question. So so let's start

interesting question. So so let's start with first of all how do we know when anything has agency? And that's an that's an experimental research program.

So you basically you hypothesize what uh problem space it's working in, what you think its goals are, and then you do experiments to figure out what competency it has, and then you find out, did I guess well poorly? Do I need

to make a better guess? And so on. So

for example, um people have said to me well, you know, your kind of pansychist almost view says that the weather should be, you know, cognitive. And I you know

I I say uh I don't say that it is or isn't because we haven't done the experiments. Do I know that uh weather

experiments. Do I know that uh weather systems let's say let's say hurricanes or so do I know that they don't show habituation sensitization that they couldn't be trained if you had the right scale of of machinery? I have no idea.

But what I do know is that it's not a um this is not a philosophical uh thing that we can decide arguing in an armchair. Yes, it is no it isn't. No

armchair. Yes, it is no it isn't. No

you have to do experiments and then you find out. So now the question is okay.

find out. So now the question is okay.

So what about you know the galaxy? What

about the universe? right are these the you know Gaia ecosystems again I think these are all empirical questions now some of them are intractable I you know we don't have the capability to do um

experiments on a on a on a planetary scale but for example one thing that I did try to do once was design a gravitational synapse so design a solar systems sized arrangement where masses

would fly in and based on the history of masses flying in it would respond to new masses in a different way so you can do you know historicity and you can have habitu ation and sensitization and things like that. So c could you have something like that that would be very

sort of ponderously slowly on an enormous scale computing something and having you know sort of simple thoughts.

I bet you could you know I bet you could. Um is the real universe doing

could. Um is the real universe doing that? I have no idea. We have to do

that? I have no idea. We have to do experiments. So so you know here here

experiments. So so you know here here you bump up against another question which is how do you know if if and when you are part of a larger cognitive system right? So, so I don't, you know

system right? So, so I don't, you know how do we know if we are in fact part of a bigger a bigger mind? So, I I don't know. Um, my suspicion is that there are

know. Um, my suspicion is that there are some sort of girdle-like theorem that will tell you that you can never know for sure. Uh, and you you know, you can

for sure. Uh, and you you know, you can never be certain, but I bet that you could gather evidence for it for or against. And I often think about um a

against. And I often think about um a kind of a um, you know, kind of a mental mental image. Imagine two neurons in the brain

image. Imagine two neurons in the brain and one is a is a you know kind of a kind of a strict materialist and one's a little more mystical and the one neuron says look uh you know we're just we just

run on chemistry and the outside world is a cold mechanical universe and it doesn't care what we do there's no mind outside of us and the other one says can't prove it but I kind of feel like there's an order to things and I kind of

feel like our environment is not stupid I kind of feel like our environment wants things from us and I kind of feel these waves of of you know these waves back propagating through us that are like almost rewards and punishments. I

feel like the the the universe is is trying to tell us something and and the first one is you're just seeing, you know, uh faces and clouds. It doesn't it doesn't exist. And of course, in in in

doesn't exist. And of course, in in in my example, the second one is correct because they are in fact part of a larger system. They're part of a brain

larger system. They're part of a brain that is learning things. And it's very hard for any one node in that system to recognize that or even a sub, you know

subnet network. But I wonder if we could

subnet network. But I wonder if we could uh having having a you know a degree of intelligence ourselves if we could gain evidence that we were part of a larger

system that was actually processing information. And I I don't I don't know

information. And I I don't I don't know exactly what that would look like but my hunch is that it would look like what we call synchronicity. I think that what it

call synchronicity. I think that what it would look like are um coincidence co co are are events that don't have a uh

causal connection at our lower level like like mechanistically like by physics there's no reason why that should be but at a larger scale in terms

of meaning and um uh you know gr the greater meanings of things that that they do have some kind of interpretation and I I think that's what it would look like to be part of a larger system I think it would look it would look and

feel like synchronicity. So, does it exist? I, you know, I don't know, but

exist? I, you know, I don't know, but that that's what I think it would feel like. Take me through the history of the

like. Take me through the history of the Levven Lab. When did it start? What were

Levven Lab. When did it start? What were

your what were your first breakthroughs?

Yeah. Um, okay. Uh, let's see. Well, it

started I mean, it it it started in my head when I was pretty young. Like, I

was it was a dream that I had uh to to do this kind of stuff. I mean, I I consider myself to be the luckiest person in the world. I get to I get to do, you know, the funnest stuff with the best people. So, um I yeah, I I think

best people. So, um I yeah, I I think it's I think it's super super fortunate.

Um but but I had I kind of had this this idea when I was very young. I had no idea what it was like. I was pretty sure that it was actually impossible. Um I

never really thought it would be practically feasible, but I figured I would push it as far as I could be, you know, before um I would have to go back to coding. And uh you know because um

to coding. And uh you know because um yeah uh for people who are unaware your background is also in computer science.

Right. Right. Yeah. Yeah. Um yeah you know I I learned to program pretty young and at that time uh that was a good way to uh that was a pretty good way to um to make money and I just figured I would do the biology as long as I could and then eventually I would get kicked out

uh and then then I would just go you know go back to coding. Um so yeah my my lab actually began uh in September of 2000. Uh that's when um uh I got I got a

2000. Uh that's when um uh I got I got a faculty position uh at the foresight institute at the Harvard Medical School and uh and I yeah we opened we opened our doors in 2000. It was just it was

just me at first and then me and one other technician. Um there's there's

other technician. Um there's there's like 42 of us now but at the time it was just it was just me and and a tech named Adam. Um and uh that was the first time

Adam. Um and uh that was the first time you know starting then was the first time that I could really start uh to take uh practically in in you know to to be practical about some of the some of

the um ideas I had about bio electricity and cognition and all these things.

Prior to that I was building up a tool chest. So I was building up uh skills

chest. So I was building up uh skills techniques um uh you know um uh information and so on. But being a grad student and then a posttock I wasn't able to talk about any of these things.

Uh but but then when I was on my own and and um then then that was the time to get going. So um just a couple of you

get going. So um just a couple of you know a couple of interesting interesting milestones.

Uh already by the time by the time I got you know I I uh we opened the lab I was involved in a collaboration with um with Ken Robinson and his uh his postoc

Thorly Thorland and together uh with and with my postoc mentor Mark Mcola we um really showed the first molecular tools for bioelect electricity. So we had a

paper on left right asymmetry and uh we showed we showed the first bioelectric tracking of non-neural bielectric states in the chicken embryo. We showed that it was important for setting up which side

is left which side is right and and then uh manipulating that information using injected ion channel constructs. So that

was the first time any of that you know reading and writing the mind of the body which is how I I certainly wouldn't have said it back then but this is how I see it now. um that that was the first time

it now. um that that was the first time that was done in a molecular in a molecular way. So that that that cell

molecular way. So that that that cell paper came out in I think uh 2002 I think it finally came out. Um but that that was a really early project. The

other the other really early project was um I had uh as a as a as a as a posttock um I started gathering tools for this whole for this whole effort and a lot of

those tools were DNA plasmids and coding different ion channels and so what I would do is I would write uh send send emails or letters to people working in electrophysiology, gut physiology, inner

ear and you know they would have some potassium channel that I had cloned and I would say you know could I could I get one of these plasmids? Um and uh I I was uh I was um I was telling them what I

was going to do. You know, I would say and what I'm going to do is is is use it to express it in embryos in various locations and use it to to in a very targeted way change the biological properties of these things. And you

know, most people were very nice and they sent me these constructs. One

person sent a a letter to my postoc mentor to say that I had had clearly had had an, you know, a mental breakdown and that he should be careful because this is so insane that I'm I'm obviously off my rocket, right? And so I remember now wait, is this your recapitulation of

what they said or they actually said mental breakdown? Well, well, okay. So I

mental breakdown? Well, well, okay. So I

I didn't see the letter, but my boss came to me. So So my boss came to me and and he was laughing and he said and he said, "Look at this. This guy says you're nuts. You asked him for for a

you're nuts. You asked him for for a plasma. He told me to be, you know, to

plasma. He told me to be, you know, to watch out and he says you're having a psychiatric break." So um so that's what

psychiatric break." So um so that's what that's what I'm I'm re relaying is what what he said to me. Okay. So um but uh but nevertheless most people sent

constructs uh and um uh in when when we got to the lab uh when to when my lab opened I started doing that. I started

um been misexpressing these things in embryos to just to just to see the space of possible changes. Right? What does

bioelect electricity really do? I mean

nobody knew at the time. It was thought it was really crazy. It was thought that membrane voltage was a um a housekeeping parameter. There was an epiphenomenon of

parameter. There was an epiphenomenon of other things that cells were doing and that uh if you mess with it, all you're going to get is uninterpretable death.

That's that's you know, everybody thought this was a stupid idea. And so

and so we started doing this and I had this uh I had this uh um um graduate student. She was she was in the dental

student. She was she was in the dental program. Her name was Ivy Chen. And she

program. Her name was Ivy Chen. And she

was in the dental program and uh she had she had amazing hands. And so I taught her to micro inject RNA into cells in the in the embryos because you know she had like really really good hands. How

do you know she had good hands before she tried that? Well, you look like you have good hands. Yeah. Well, she was a dental student and so so I talked to her. She wanted to do research and I

her. She wanted to do research and I said, "Tell me tell me what you do." And

I said "Oh, I do these, you know, I saw people's, you know, gums and whatever."

And I said, "Okay, you probably could do this." Okay. So, she wasn't playing Call

this." Okay. So, she wasn't playing Call of Duty. No, no, no. She Well, well, she

of Duty. No, no, no. She Well, well, she may have been also, but I don't know any I don't know that. Uh what I know is that she was doing, you know, surgeries in in people's mouths and and I thought that that she may be able to, you know in in tight confined places, you know

with the glasses and everything. So I

thought I thought she would be able to do this through a microscope and she and she was. Um and so and so we we did this

she was. Um and so and so we we did this we did this together and we injected these these constructs and I still remember to this day. Uh she calls me in one day and she says, "Um so I looked at the embryos and they're they're covered

with some kind of black dots and I said "Uh, black dots? Let me let me see.

Let's let's go look." So I so I come out and we look we look through the microscope. The black dots were eyes.

microscope. The black dots were eyes.

What she had done was what she had done was the potassium channel that she injected um was the one that we later it took years to publish the paper. But uh

what she what she had discovered is that is is a particular biological state that tells cells to build an eye. It's it's

remarkable because right right there and then uh you knew that a bioelectricity was instructive. It was not an epi

was instructive. It was not an epi phenomenon because it controls which organs you get. B that it's that the whole system is modular and hierarchical because we did not tell the cells how to

build an eye. So we we didn't say where the stem cells go or what cells go next to what other cells or what genes should be expressed. We did none of that. We

be expressed. We did none of that. We

triggered a highle subruine that says build an eye here. So right away that that one experiment like told us told us all these amazing things. Then then

eventually and this was the work of a grad student um Sheri in my group who uh took you know took on the the project and she did a whole PhD on this showing that the other amazing thing about it is

that if you only target a few cells what they do is they get their neighbors to help out because they can tell there's not enough of them to build an eye you know kind of like ants you know the ants recruit their their their buddies to

take on a bigger task. So that tells you that the that that the material you're working with has these amazing properties that you don't have to micromanage, right? It's a different

micromanage, right? It's a different kind of engineering. It's engineering as as I put it recently in a recent paper.

It's engineering with um agential materials because it's a material with competencies with an agenda. You don't

have to control it the way you do wood and metal and and things like that. So

okay., So, anyway,, so, so so, that, that, that kind of thing. Um uh then uh then we had a bunch of work on a bunch more work on

left right asymmetry and showing how uh the cells in the body decide which side they're on based on um based on these electrical cues. Then we discovered that

electrical cues. Then we discovered that in order for cells to uh the way they interpret these electrical cues had to do with uh the movement of serotonin. So

long before the nervous system or the brain shows up, the body is using serotonin to interpret electrical signals. So, so this was this was really

signals. So, so this was this was really underscoring um the uh the idea that a lot of the tools, concepts, reagents

pathways, mechanisms from neuroscience really have their origin much earlier.

And so this was a completely new role for serotonin, right? So, so serotonin is a neurotransmitter, does many interesting things, but long before your brain appears, it also controls which direction of your body, your heart and

your various other organs go to. So

trying to understand in in the kind of you know in the short term how does electrical activity control cell behavior but bigger picture wow these these these neurallike processes are going on in cells that are absolutely

not neurons much more you know much long before that. So um so that was that was

before that. So um so that was that was kind of cool. Um then then I hired a postc named Danny Adams who later became a faculty member uh and a and a colleague. And one of the things that

colleague. And one of the things that she did was to um pioneer the early use of voltage sensitive dyes to read these electrical potentials. And so she

electrical potentials. And so she discovered uh in the work that she did in my group she she discovered this um this thing we call the electric face.

And approximately what year is this now?

Oh this is the electric face. This is

probably 200 2008 something like that.

2007208. Um and uh what she had discovered was that if you look at the nent ectoerm that later will regionalize to become face and mouth, you know, eyes

and mouth and all of that that um uh that uh early early on before all the genes turn on that um uh determine where all those things will go, the biomectric

pattern within that ectoerm looks like the face. It it shows you where all the

the face. It it shows you where all the stuff is going to go. And then and then we ultimately we were able to show that and by the way there was that eye spot which which is which is why the eye thing worked. And we were able to show

thing worked. And we were able to show that all kinds of birth defects that mess up the formation of face do it by uh uh inhibiting the normal bielectric pattern and that you could fix it. You

know you could you could you could um exert um repair effects that way. So uh

so that was so that was that was interesting. Then then we then we

interesting. Then then we then we started looking at regeneration. Um and

again the early work was done also by Danny and then later on by Kelly Chang who's now a faculty member at University of Las Vegas where what we did was uh we showed that um tadpole tail regeneration

was also biomectrically driven and that was our first gain of function uh effect in, regeneration, where, we, were able, to show that we could actually induce new regeneration. So the tail is a very

regeneration. So the tail is a very complex organ. It has spinal cord

complex organ. It has spinal cord muscle, bone, well, not bone vasculature um interervation um you know, peripheral innovation, skin. And

so, um, we took we took tadpoles that normally do not regenerate. There's a

there's a stage at which they they can't regenerate their tails. And we developed a bi-electric cocktail that induces it to to grow. My my the my my postto at the time, Kelly Chang, said, um, I I I

soaked them. I said, "Well, how long did

soaked them. I said, "Well, how long did you how long did you soak them for?" And

she said, "An hour." And I I thought I thought, but that's got to be too short.

There's no way an hour soak is going to do anything. And sure enough, that that

do anything. And sure enough, that that hour soak led to uh eight days of regeneration where we don't touch it at all. And the most recent version of that

all. And the most recent version of that work is in the frog leg where we show that 24-hour stimulation with our cocktail induces a year and a half of

leg growth during which time we don't touch it at all. So the amazing thing there is again this is not micromanagement. This is not 3D

micromanagement. This is not 3D printing. This is not us telling every

printing. This is not us telling every cell where to go during this incredible year and a halfl long process. This is

at the very earliest moment you communicate to the cells go down the leg building path not the scarring path and that's it. And then you take your hands

that's it. And then you take your hands off. It's it's it's calling a sub

off. It's it's it's calling a sub routine. It's modularity. It's relying

routine. It's modularity. It's relying

on the competency of the of the material where you're not going to micromanage it. So that was so that was the first

it. So that was so that was the first time that kind of became obvious that that was possible is when when she she showed that an hour um just an hour stimulation of the correct biological

state got the whole tail to commit to regenerate itself. Uh so that was that

regenerate itself. Uh so that was that was the beginning of our regeneration program after which we went into limbs and uh and and now of course we're trying to push into into mamalian you

know into mamalian limbs. Um yeah along along the along the way uh Celia Herrera Ringone and Nosha Morugan were other postocs that that that showed leg

regeneration in and frog and so on. Um

around around that time we had uh we had another thing we we really I really wanted to work on cancer and I really wanted to work on this um on this idea that uh there's a bioelectric component to it and and the and the way you can

you can think about it is simply that not why is there cancer but why is there anything but cancer? So, so why do cells ever cooperate instead of being amoebas? Why do they ever cooperate? And

amoebas? Why do they ever cooperate? And

so we know that the bielectric signaling is the kind of um cognitive glue that that binds them together towards these large scale construction projects maintaining organs and things like that.

And so um yeah, so we wanted to study that biomectrically. And so I had I had

that biomectrically. And so I had I had two students, Brooke Cherinet and Maria Labin who uh undertook that and we were able to show that using this biological

imaging you can tell which cells were going to convert ahead of time. You

could also convince perfectly normal cells to become metastatic melanoma just by giving them inappropriate biomectric cues about their environment. So you can you, can, no, no, no no no, no, genetic

damage, no carcinogens, no you know anka genes but but just the wrong bielectric information and they become like metastatic melanoma. Um and and best of all they

melanoma. Um and and best of all they were able to show that you can actually reverse not re reverse um carcinogenic stimuli for example human genes by appropriate bi connections to their

neighbors. So we had a whole set of uh

neighbors. So we had a whole set of uh we had a whole set of papers um showing how to uh how to control uh cells biomectrically and uh oneita Matthews in my lab now is trying to take um take all

those strategies into human into human cancer. So this is 2009. This was yeah

cancer. So this is 2009. This was yeah the first yeah the first experiments were were done around um 2010 2011 something like that. So when did this

conjectural connection between bioelect electricity and cancer occur to you? the

field was clueless about that. It's not

as if they had an opinion and said no.

Well,, uh, to, to to, be, to, to, be, to, be clear, the very first person who talked about this was Clarence Con in 1971. So

Clarence Con in 71 wrote that uh he had a couple papers uh in in in science where he showed that resting potential of cells was an important um driver of

cell proliferation and he conjectured that it might have something to do with with with cancer. So this idea had been floated. Nobody had ever done anything

floated. Nobody had ever done anything with it and and and they and the uh tools to study this at a molecular level didn't exist until until we made

them. So you know that that idea just

them. So you know that that idea just just that bio electricity is important in cancer h had been around before. Um

what I think we brought to it that was completely new is the notion of that this is also related to cognition. the

idea that it's not just that it drives proliferation in cancer that this is really involved in setting the limiting the size of the cognitive lone at which

point cells acquire ancient you know um uh um metastatic like behavior the way that you know amiebas do um that that aspect of it I think is is completely new with us that that that idea that uh

that this really is about the boundaries of the self you know I've never seen anybody else talk about that so um so those you know those those around that same time though something else interesting that happened in 2009 which

is that we were we were studying plenary we were studying flatworms um and uh we had uh we had shown

that when you cut plenary into pieces the way that they these pieces decide how many heads they were going to have uh is actually related to the ability of cells to communicate with each other using gap junctions these these

electrical synapses and so we had made some two-headed worms and so on Um and uh around two 2009 um I had this um had

this uh student this visiting student from BEu her name was Lissa and uh she she we I asked her to recut the two-headed worms and just in plain

water. No more no more manipulation of

water. No more no more manipulation of any kind. We we cut them meaning cut off

any kind. We we cut them meaning cut off the, heads, of, them, again., Yeah., So, so so you have a normal one-headed worm. You

cut off the head and the tail. You have

the middle fragment. you uh soak that middle fragment in a drug that blocks the cells from electrically communicating with each other and they develop heads at both ends. Would that

drug that you soak it in be called a biological cocktail? Like is that what

biological cocktail? Like is that what you referred to earlier? It's a

different biological cocktail. It wasn't

even a cocktail. It was a single one single chemical. It was it was really

single chemical. It was it was really simple. It was just one one single

simple. It was just one one single chemical and all it does is block abjunctions. And so and so what what

abjunctions. And so and so what what that did did was change the electric circuit properties that that the cells have and they all and and both wounds decided they had to be heads. So now you get these two-headed worms. So So yeah.

So, so Lissa um recuts these two-headed worms in plain water. No more

manipulation. And she gets more two-headed worms. It's permanent once once you've convinced them. Now the

genetics are untouched, right? No no no uh no genomic um uh editing, no trans genes. Uh genetically identical, but the

genes. Uh genetically identical, but the two worms are the two-headed worms are a permanent, line, now., So So, a, couple, of interesting things there. One is uh well

one one is is is it shows the um the interesting memory properties of the medium meaning once you've brought it to a new state it holds it remembers the two so it's a kind of memory it remembers the two-headed state another

interesting thing is that two-headed worms were first seen well they were first described in the early 1900s so people had seen to be made by other by other means people had seen two-headed

worms apparently to to to my knowledge I I don't think anybody's ever ever written about this nobody thought to recut them until we did it in 2009. And

I think the reason is because it was considered totally obvious what would happen. I mean, their genome is normal.

happen. I mean, their genome is normal.

You cut off that second ectopic head, of course, it'll just go back to normal.

That's what people assume. So, this is this is another another example of um why thinking in these in these different conceptual ways is uh it matters. it

leads to new experiments because if you don't think about this as memory, if you're focused on on the genes as as driving phenotypes, then you would never it doesn't make any sense to to recut them. But if you start thinking, well, I

them. But if you start thinking, well, I wonder if there's a physiological memory here, then then that leads you to this experiment, right? So so thinking in

experiment, right? So so thinking in this way leads to um leads to new experiments. Um and then and then the

experiments. Um and then and then the and then the other thing it points out is something really interesting.

So for pretty much any animal model, you can call a stock center and you can get genetic you can get lines of genetic mutants. So you can get flies with curly

mutants. So you can get flies with curly wings and mice with crooked tails and weird coat patterns and you know chickens with funky toes. You you can get any you know there's a any any kind

of um uh any kind of mutant lines in pleneria. There are no mutant lines.

pleneria. There are no mutant lines.

Nobody's ever succeeded in making anything other than a normal plenarian except for our two-headed form. and that

one's not genetic. And so there's a deep reason which I didn't understand back then. In fact, I think we only I think I

then. In fact, I think we only I think I only really figured out what I think it means um in the last few months. But uh

but but it was it was striking that that the only unusual plenarian form per permanent plenarian form out there was the one that we had made and it was and that's the one that's not genetic. It's

not done by by the way that you would do this with any other animal. Yeah. What's

your recent discovery been? Well, it's

it's it's not so much a a dis a discovery. It's more of a um a a new way

discovery. It's more of a um a a new way of thinking about it. So

um so one of the one of the weird things about pleneria is that because the way the, way, they, reproduce,, at least, the ones that we study, the way they reproduce is they tear themselves in

half and then each half grows the rest of the body. And

um, t, t t t t t t t t t t t t t t t t t t t t, t t t t t t t t t t t t t t t t t t t typically, what, happens, for, for, most, of us that reproduce by sexual reproduction is that when you get mutations in your body during your lifetime, those mutations are not passed on to your

offspring, right? They they they they

offspring, right? They they they they disappear with your body and and then the eggs go on and so on. Well, in

pleneria, it's not like that. in

pleneria um uh any mutation that doesn't kill the cell gets expanded into the next generation because each half grows you know grows the grows the remainder of the body and so so their genome is very messy they have I mean in fact

cells can be mixloyed they can have different numbers of chromosomes that's that's very weird and I always I always thought isn't it strange and no nobody ever talked about this in any biology

class that I've ever had isn't it strange that the animal that is the most regenerative uh apparently immortal. They don't age.

Uh cancer resistant and by the way resistant to trans genes. So so so nobody still nobody's been able to make transgenic worms. Um is also the one with the most chaotic genome. Now that's

bizarre. You would think but from everything that we've we we are told about genomes and and and how they determine phenotypes that the animal um uh with with all those amazing

properties should have really pristine hardware. you would think that that that

hardware. you would think that that that you should have a really clean, really stable genome uh if you if you're going to be regenerative and cancer resistant and not age and whatever. It's the exact opposite. I always thought that was

opposite. I always thought that was incredibly weird. And so so finally I

incredibly weird. And so so finally I think uh and we've done some computational work now to show to show why this is uh I think we now understand what's happening. And what I think is

what's happening. And what I think is happening is this. Imagine uh let's go let's go back to this issue of uh of of of developmental problem solving. So if

you have a if you had a passive material such that you've got some genes the genes determine what the material does and so therefore you have an outcome and that outcome gets selected you know it either does well or not and then and

then there's differential reproduction.

So the standard story of evolution then everything works well and everything works like uh it would in a genetic algorithm very very simple. The problem

with it, of course, is that it takes forever because let's say that let's say that, you're, a, tadpole, and, you, have a mutation. Mutations usually do multiple

mutation. Mutations usually do multiple things. Let's say this mutation makes

things. Let's say this mutation makes your mouth be offkilter, but it also does something else somewhere else in the tail, something positive somewhere in the tail. Uh, under the standard uh evolutionary paradigm, uh, you would

never get to experience the positive effects of that of that mutation because with a mouth being off, you would die and that would be that. So selection

would weed you out very quickly and you would have to wait for a new mutation that gives you the positive effects without the bad effects on the mouth right? So that that it's it's very hard

right? So that that it's it's very hard to make new changes without ripping up old gains and so on. So that that that's some of the limitations of of that kind of view. But but but a much more

of view. But but but a much more realistic scenario is is the fact that um you don't go straight from a genotype to the phenotype. You don't go from the genes to the actual body. There's this

layer of development in the middle. And

the thing about development is not just that it's complex. it's that it's intelligent, meaning it has problem solving competencies. So, what actually

solving competencies. So, what actually happens in tadpoles is if I move the bo the mouth off to the side of the head uh within a few weeks, it comes back to normal on its own. Meaning meaning it

can it can um uh re uh you know re reach again that region of anatomical space where it wants to be. So now imagine what this means. Imagine what this means for

means. Imagine what this means for evolution when you're evolving a competent substrate, not a passive substrate. By the time a nice tadpole

substrate. By the time a nice tadpole goes up for selection to see whether it gets to reproduce or not, selection can't really see whether it looks good because the genome was great or because

the, genome, was, actually, so so, but, it fixed whatever whatever issue it had.

Right?, So so, that, competency, starts, to hide information from selection. So so

selection finds it kind of hard to to choose the best genome because even the ones with problems look pretty good by the time it you know it's time to be selected. So what happens and we did

selected. So what happens and we did computational um simulations of all this. And what happens is that

this. And what happens is that uh when you when you do this um evolution ends up spending all of its effort ramping up the competency because it doesn't see the the structural genes.

All it sees is the competency mechanism.

And and and if you improve the competency mechanism, well that makes it even harder to see the genome, right?

And so you have this ratchet, you have this positive feedback loop where the more the more competent the material is the harder it is to evolve the actual genome. All the pressure is now on the

genome. All the pressure is now on the competency. So you end up with kind of

competency. So you end up with kind of like a like a ladder. um uh really an intelligence uh uh ratchet because right and and and people like um uh uh Steve

Frank and and others have pointed this out for for you know in in in other aspects of biology and also in technology right the once you um you know once RAID array technology came up it's not it became not as important to

have really pristine and stable uh disc media because the RAID the RAID takes care of it right so so the pressure on having really really stable you know disc is off so so what it means is that

in the case of the pleneria that that positive feedback loop that ratchet went all the way to the end. That basically

what what happened here is that uh what you've got is an organism where it is assumed that your hardware is crap. It's

assumed that you're full of mutations.

All the cells have different, you know numbers of chromosomes. We already know the genetics are all over the place. Uh

but all of the effort went into developing an algorithm that can do the necessary error correction and do and and and take that journey in morphospace no matter what the hardware looks like.

That is why they don't age. That is why uh they're resistant to cancer and that's why nobody can make a transgenic worm because they really pay less attention to their genome in that sense than than many other organisms. So you

can imagine um a sort of continuum.

you've got um something like CL against the nematode where they're pretty cookie cutter., So, so so, as, far, as, we, know, they

cutter., So, so so, as, far, as, we, know, they don't regenerate much. It's you know what you what the genome says is pretty much what you get. Then then you've got some mammals right. So so mammals at least in the embryionic stages they've

got some competency. You can chop you know um early mamalian embryos into pieces and you get twins and you know triplets and so on. Uh then you got salamanders. Salamanders are re they're

salamanders. Salamanders are re they're quite good regenerators. They're quite

resistant to cancer. they are longived and then you know when when you when you run that that spiral all the way to the end you get pleneria which are these amazing things that have committed to the fact that the hardware is going to

be noisy and that all the effort is going to go into an amazing algorithm that lets them do their thing and and that's why if you're going to make lines of weird pleneria targeting the structural genome is is not helpful but

if you screw with the um the actual mechanisms that uh that enable the error correction aka the bioelectricity that's when you can make lines of double-headed and and and and so on because now you're

targeting the actual uh you know the the the int the the problem solving machinery and if you were to look at the genome of the salamander versus the sea elegance would the sea elegance be more chaotic or more ordered than the

salamander? It's a good question. So

salamander? It's a good question. So

nobody's done that specifically. No, as

as far as I know this is this is something that we're just ramping up to do now is to start uh cuz correct me if I'm if I'm incorrect. It sounds like the hypothesis is that if you have a large

amount of genetic chaos or what if you can quantify that then you would have something that would be compensated for in terms of competency or some higher level structure. Yeah, I think that yes

level structure. Yeah, I think that yes I think that's a that's a prediction of of of this model that I just laid out.

And so yeah, so we can test that. I mean

a part of it also is uh there there's an ecological component. I mean you can ask

ecological component. I mean you can ask the question so why doesn't everything end up like pleneria? And I think there's a there's an aspect of this that that that that ratchet obviously doesn't run to the end in every in every

scenario because in some species there's a better trade-off to be had somewhere else. I wonder if there are three

else. I wonder if there are three components then because then if you don't see a direct correlation it could be hidden by a third factor. Yeah. Which

which I think would probably be environment. It would it would probably

environment. It would it would probably be the ecology of how do you reproduce um you know how noisy, how dangerous how unpredictable is your environment.

I'm going to guess there's something like that involved here. Yeah. But I

think but I think that's um you know that's that's that's starting to kind of explain what's going on with with with pleneria and that uh yeah that so so

those so so we found um uh we we we found the persistence of the two-headed phenotype and then um Nester Oedo and Junji Morokuma um in my group uh wrote a wrote a nice paper on that and and so on

and the the next kind of big advance there by in 2017 was by Fallon Durant um a grad student in my lab who also did something interesting. So, so when you

something interesting. So, so when you take a bunch of worms and you uh you treat them with let's say this reagent that blocks the gap junctions, typically what you see is okay, you treat 100

worms, 70% of them go on to make two heads and 30% are unaffected. So, we

thought they were unaffected because they stay one-headed and we always uh we always called them escapees because we thought that they somehow just escaped the action of the octal. maybe their

skin was a little thicker or something and we never had a good explanation for it., But, but, any, anyway,, uh you, know,, we

it., But, but, any, anyway,, uh you, know,, we there was a 70% penetrance to the phenotype and and most things have not 100% phenotype, so it wasn't penetrance.

A penetrance just means that um when you apply some treatment to a population not all of them have an effect and not all of them have the same effect. That's

true for pretty much every every drug every mutation and so on. So um so for years we called them escapees and then um around 2015 when Fallon joined lab

she recut some of those one-headed escapees and found that they also do 7030 that 70% of them became double-headed and 30% didn't. And so

what we realized was that they're not actually escapes. They're not

actually escapes. They're not unaffected. They're affected but the way

unaffected. They're affected but the way they're affected is quite different.

They are randomized. They can't tell if they should be one-headed or two-headed.

And they flip a coin se with a 7030 bias about what they should do in any given generation. In fact, we were able to

generation. In fact, we were able to show that when you cut multiple pieces from the same worm, and we call them cryptic worms, cryptic because physically they look completely normal one head, one tail, they look normal but they're not normal. And then because

because if you recut them, they're not sure what to do. Their memories are un are bystable. So what happens is that

are bystable. So what happens is that you can cut them into pieces and every piece makes its own decision if it's going to be one-headed or two-headed even though they came from the same you know the same parent organism uh with

the same roughly 7030 um frequency. So

so there so so that's another kind of permanent line and the way we studied it more recently was as a kind of perceptual bystability. So so like the

perceptual bystability. So so like the rabbit duck illusion right you look at it and you look it looks like one thing looks like something else that's kind of um what's happening here. there's a

biological pattern that can be interpreted in one of two ways and and that's why they're they're confused. You

know, they're sort of bystable and it can fall in in in either direction. Um

so that's so that's another thing we uh you know we did in in in Pleneria. Okay.

So that's 2017. I'm going to get you to bring us up to 2020 and then to 2024.

But first, what is meant explain to myself what is meant when you say Levan lab? So there's also Huberman lab. Do

lab? So there's also Huberman lab. Do

biologists do professors who are in neuroscience or biology get given a lab by the university? Is this standard? Do

you share a lab with other people?

What's meant by lab? Is it a room? What

is it? Yeah. Um, okay. So, so the way the way this works is basically that uh when you're finishing up your posttock you u you do what people call going out on the market, which means you interview

at a bunch of places and see who will hire you as a brand new um junior faculty member. So, when you get a job

faculty member. So, when you get a job and so this is this is, you know considered your first real independent job because uh you are now in charge of all your successes and failures. It's

all it's all up to you and typically uh yes, at that point you get a lab. So

one of the things you do is you negotiate uh the amount of space you have. Typically, you start off pretty

have. Typically, you start off pretty small. Um and then over time, if you

small. Um and then over time, if you bring in new grants, then you ask for more space and the lab grows. And when

they say Lean Lab or Huban Huberman Lab what they're just referring to is the um all of the research that is controlled by you where you make the decisions, you know, where that particular person makes

the decisions. So physically so for

the decisions. So physically so for example I have uh I have uh three different locations on this campus where my research is done and that's just because um there isn't one contiguous

space I I mean I would be happier to have everything under one you know in one place but um they're they're large spaces and uh so so there's a few specific locations all of them are

considered part of the Levan lab because as the principal investigator I'm the one whose job it is to bring in uh the uh external funding to to support all the people that work there and to pay

for the reagents and also I'm the um you know the the PI of these labs. It's

their job to be responsible for the good and the bad of of what they do. So

that's that's what it means. It's it's

you're it just means you're the you're the principal investigator responsible for um determining what uh research happens and what happens to that research, who does it. You're hiring

you're um you know recruiting people you're writing grants. That's that's

what it means. And for the people who are watching, I mean, sorry, for the people who are listening, there are shots on screen right now of the Levven Lab, provided we're able to go later.

Okay. So, now bring us to 2020 to 2024.

Yeah. Um, so, so some of the some of the latest most most exciting things that um Oh, oh, by the way, one thing I I didn't mention that happened around between

2015 and 20 I mean 2020 or so, uh, was also um, Viphuff Pies. He's he's also a a staff scientist in at my lab. Um we

were able to show that uh you can actually use reinforcement of biomectric patterns to fix birth defects. So we in frog this started yeah this this all all this started in frog and we were able to

show that there's a range of birth defects induced by other you know by other means that you can actually repair so so complex defects of the brain face hard like these really complicated things you could actually repair them uh

by very simple uh changes in the biological pattern so I so I I you know I I think that's a really important actually story because because not only is it a path to birth defects uh you know clinical repair of birth defects

but it actually shows how again you can take advantage of this highly modular aspect and you don't have to tattoo um instructions onto every cell for something as complex as a brain or a fa

or or a heart. Uh you can give pretty largecale uh instructions and then the system does what it does to to to to fix it. So, okay. So, so the the next couple

it. So, okay. So, so the the next couple of big things after that were first of all the discovery of Zenobots and this was Doug Blackston and my group did all the um uh did all the biology for it and

this was in collaboration with Josh Bonggard who's a computer scientist at UVM and uh his PhD student at the time um Sam Criedman who did all the all the

computer simulations for for for the work. So, so this was the discovery of

work. So, so this was the discovery of the zenobots and the idea of using uh epithelial cells from an early frog embryo to so so prospective skin cells

um to let them to liberate them from the rest of the embryo where they're basically getting a bunch of signals that force them to be this like you know boring skin layer on the outside of the animal keeping out the bacteria. So they

were going to be a skin cell. They

weren't yet. uh they were comm they were well at the at the it's it's it's uh it's hard because skin isn't you know it's not it's not a real precise term but it's it's cells that at the time

that we took them off the embryo were already committed to the fate of becoming that kind of outer epithelial covering. They they hadn't matured yet

covering. They they hadn't matured yet but they they already knew they were going down that that direction. So um so we were able to show that when you liberate them from those cues, they

actually take on a different uh a different lifestyle uh and they become a motile sort of self-contained little little um construct that swims around and does some really interesting things

including making copies of itself from from skin cell from loose skin cells that you provide and so on. Um, shortly

thereafter, you know, a few a few a couple years later, we were able to make anthrobots, which is the same thing but with adult human tracheal cells. And

part of that, so so that has there there's a couple of reasons why that's important. Very simply, you know, some

important. Very simply, you know, some people saw zenobots and they thought well, amphibians are plastic, embryos are plastic. Maybe maybe not shocking

are plastic. Maybe maybe not shocking that that um cells from a frog embryo can reassemble into something else, but basically um this this resembles a

developmental bi an a phenomenon in frog developmental biology known as an animal cap. And and and you know one way an

cap. And and and you know one way an animal cap. It's called an animal cap.

animal cap. It's called an animal cap.

The animal cap is just basically that top layer of skin cells of perspective ectoormal cells. It's called an animal

ectoormal cells. It's called an animal cap. So so some people thought about

cap. So so some people thought about this as a unique uh feature of frog developmental biology. And so I wanted

developmental biology. And so I wanted to get as far away from Prague and embryo as possible because because I wanted to show that this was kind of general and and a broader phenomena. So

what's the furthest you can get from embriionic frog adult human? So um so Kismushka in my group who just defended her PhD about a month ago. Uh so so she

developed a protocol to take donated uh tracheal epithelial cells from from human patients um often elderly patients and let them assemble into a similar

kind of thing a self-motile little um construct that swims around on its own.

And one of the most amazing things that uh that these anthrobots do and this is just the first thing we tried. Right.

So, I'm guessing there's hundred other things that they can do, but um one thing that they can do is if you put them on a a neural wound. So, in a petri dish, you can grow a bunch of human neurons. You take a scalp and you put a

neurons. You take a scalp and you put a scratch down through that um through that lawn of neurons. So, there's a there's neurons here, there's neurons here, and there's a big there's a big wound in the middle. When the when the

um anthrobots come in, they they can settle down into a kind of a we call it a superbot, which is the collection of um collection of anthrobots. And four

days later, if you lift them, you lift them up, what you see is what they do is they take the two sides of the of the neural wound and they knit them together. So they literally repair

together. So they literally repair across that gap. So you can sort of start imagining I mean there's a couple of things on a practical level. You can

imagine in the future uh personalized interventions where your own cells, no no heterogous uh you know synthetic cells, no gene therapy um but your own cells are are are behaviorally

reprogrammed to go around your body and fix things in the form of these anthropods. you don't need immune

anthropods. you don't need immune suppression because they're your own cells, right? And so and so so you can

cells, right? And so and so so you can imagine uh those kinds of um kind of interventions. It's interesting because

interventions. It's interesting because a lot of the interventions we use now we use drugs and we use materials, you know, screws and bolts and things and then occasionally we use like a pacemaker or something, but but generally our interventions are very low

agency, you know, and ultimately we'll have like smart implants that that make decisions for you and do but but mostly they're very low agency kinds of things.

And when you're using low agency tools the kinds of things you can do are typically uh very brittle. In other

words, this is why it's hard to uh discover drugs that work for all patients. You get you get side effects.

patients. You get you get side effects.

You get very differential uh efficacy in different patients because you're trying to micromanage at the chemical level a very complex system. You don't just want agency. You want agency that's attuned

agency. You want agency that's attuned to yourself because you get someone else's agency in you. Yeah. Yeah. It's

not great for you. Exactly. which is why your own cells coming from your own body, they share with you all the priors about health, disease, stress, cancer you know, uh they're they're they're part of your own body. They already know

all of this. And so part of this is is creating these um understanding how to create these agential interventions that uh can have these positive effect. I

mean, we we didn't teach the anthropots to repair neural tissue. We had no idea.

This is something they do on their own.

Like who would have ever thought that your tracheal cells which sit there quietly for for decades if you give if you let them uh have a little life of their own they can actually go around and fix neural wounds right you must

have had some idea that this would be possible otherwise you wouldn't have tested it. Oh, true. Uh, true. Yes.

tested it. Oh, true. Uh, true. Yes.

Uh, this this is true for a lot of stuff in our lab where people say, "Well, did you, know, that, was, going to, happen?", And

so, on the one hand, no, because it's it's so it's so wild and and it wasn't predicted by any existing structures. On

the other hand, yes, because we did the experiment and and that's why I did it because I had I had an intuition that that that that's how this thing would work. So, so, so did I know that it was

work. So, so, so did I know that it was going to specifically repair uh peripheral intervation? No. But I did

peripheral intervation? No. But I did think that it would um that among its behavioral repertoire would be to exert positive influence on on human cells around it. And so this was a convenient

around it. And so this was a convenient assay to try. We have hundred more that we're, going to, try., There's, all, kinds, of other stuff. Yes, I see. I see. So

other stuff. Yes, I see. I see. So

you're testing out a variety. Correct.

You have to start somewhere, right? And

so and so and so we said, okay, so Gazm and I said, well, why don't we why don't we try some, you know, a nice easy neural scar. There's there's many

neural scar. There's there's many there's many other other things to try.

Uh so that's kind of the practical application, but the kind of bigger intellectual issue is much like with the zenobots, what's cool about making these sorts of um synthetic constructs is that

they don't have a long evolutionary history in that form factor. There's

never been any zenobots. There's never

been any anthrobots in the evolutionary history. The anthrobots don't look

history. The anthrobots don't look anything like a human sta, you know stages of human development. And so the question arises uh where do their form and behavior come from then right and so

this is where you get back to this issue of the platonic space right if it's if you can't pin it on eons of specific selection for specific uh functions where do these novel um capabilities

come from and so I I really view all of these synthetic constructs as exploration vehicles there ways to look around in that platonic space and see what else is out there we know normal

development takes it shows us one point in that space that says this is this is this is the form that's that's there.

But once you start making these synthetic things, you you widen that uh that your view of that latent space as to what's actually possible. And I see this research program as really investigating the structure of that uh

platonic space and the way that mathematicians, you know, people make the map of mathematics, right? And there

are the sort of a structure of how the different pieces of math fit together. I

think that's that's actually what's what what we're doing here when we make these synthetic things is we're making vehicles to to um observe what else is possible in that space that evolution

has not shown us yet. Um yeah. So, oh

you know and and and then you can do interesting things like and this is this is this you know still unpublished but you you can you can ask questions like um what what do their transcripttos look like? You know what genes do xenobots

like? You know what genes do xenobots and anthrobots express? Uh and uh you know without blowing any of the the sort of surprise with the p the paper should be out sometime this year. Um massively

new transcriptional profiles in these things. no no drugs, no um no synthetic

things. no no drugs, no um no synthetic biology circuits, no genomic editing. Uh

just by virtue of having a new lifestyle, they adapt their uh transcriptional profile. Their the the

transcriptional profile. Their the the genes that they express are quite different quite different. So so that'll be that'll be an interesting study. Um

and then you know for the for the for the rest of it, I mean what we've been doing in the last few years is trying to bring a lot of the work that we've done earlier into clinically relevant models.

So the cancer stuff has moved from frog into human cells and organoids um um spheroids. So human cancer spheroids and

spheroids. So human cancer spheroids and uh glyobblastoma colon cancer stuff like that. Um the regeneration work has moved

that. Um the regeneration work has moved from frog into mice. So and this is uh it's it's you know it's coming along.

I'm not I'm not claiming any particular result yet. This is um I should also say

result yet. This is um I should also say there's a an invention um uh uh what do you call it? uh

um uh a disclosure here I have to do because because we have we have a couple of companies now and so I have to you know I have to do a disclosure that uh uh in the case of regeneration so

morphaceuticals is a company that Dave Kaplan and I have so David is a um bioengineer here in uh at Tuftton and and he and I have this have this company

aiming at limb regeneration and and more broadly biomectrics in in regeneration.

Um so yeah so the cancer the limb regeneration stuff um you know more more uh more uh experiments in trying to understand uh

how to read and interpret the information that flows across levels. So

so we know cells exchange electrical signals to know how to make an embryo.

Turns out embryos actually communicate with each other. So that's been a really exciting uh finding recently of for Angela Tong and Migra who just got her PhD as well uh where we studied this um

embryo tomb embryo communication showing that groups of embryos actually are much better at resisting certain defects than than individuals and they have their own transcriptional profile. So I call it a

transcriptional profile. So I call it a hyper embryo because it's like the next level. They they have an expression um a

level. They they have an expression um a transcriptto that is different from from normal embryos developing alone let's say. So that's that's pretty exciting.

say. So that's that's pretty exciting.

Uh and um yeah, that's those those are the kinds of things we've been we've been focused on. Okay, now we're going to end on advice for a newcomer to

biology. They're entering the field.

biology. They're entering the field.

What do you say, boy? Uh well, step one is to ignore most people's advice. So

that's, uh, I, don't know, how, helpful, that will be, but um uh I I actually have uh I have a whole thing about maybe we can put up a link. I have a whole uh um long um description of this on my blog. So on

my blog, I have a I have a thing that uh basically talks about talks about advice. Okay, that's on screen. Also

advice. Okay, that's on screen. Also

you should know that the previous research by Angela Tong and Gamasaya.

Yeah, Gazam Gumskaya. We did a podcast together. So that link will be on screen

together. So that link will be on screen as well. There's also another podcast

as well. There's also another podcast with Michael 11 which is on screen and then another one which is on screen with Chris Fields and and Carl Fristen.

Another one with Michael Evan and Yoshabach that's on screen. So Michael

is a legend on on theories of everything. Okay. So does your advice

everything. Okay. So does your advice for the biologist differ from your advice to the general scientist entering the field? I mean uh the most important

the field? I mean uh the most important thing I'll say is I do not in any way feel like I could be giving anybody advice. Uh I think that uh there are so

advice. Uh I think that uh there are so many individual circumstances um that I'm not going to claim I have any any uh sort of uh How about what you would have wish you had known when you

were 20? Yeah.

were 20? Yeah.

Um I I I I so so so this is this is pretty much the only thing I can say about any any of this. Uh

that even even very smart successful people are only well calibrated on their own field their own things that they are passionate about. They're not well

passionate about. They're not well calibrated on your stuff. So what that means is that if somebody gives you so this is this is all about uh it's kind of meta advice. It's all about adi

advice on advice and and and the idea is that when somebody gives you a critique of a specific product, so let's say you gave a talk or wrote a paper or you did an experiment and somebody's critiquing

what you did, right? That that's gold.

So, so squeeze the hell out of that for any way to improve your craft. What

could I have done better? What could I have done better to do a better experiment? What could I have done

experiment? What could I have done better in my presentation so that they would understand what I want them to understand? That that's gold. the part

understand? That that's gold. the part

where everybody gives uh largecale advice. Oh, work on this, don't work on

advice. Oh, work on this, don't work on that, focus um don't think of it this way, think of it that way, all of that stuff is uh generally speaking better

off uh ignored completely. So

um people people are are really not calibrated on on on you, your your uh your dreams in the field, your ideas.

uh, you, know, you, it it, does, not, pay, to listen to anybody else about um what you should be doing and how you really need to be everybody needs to be developing their own intuition about about what

that is and testing it out by doing things and seeing how how they land and um I think that most most everything that we've done uh along the way that's interesting and certainly we've had

plenty of dead ends and you know plenty of made plenty of mistakes but most of the interesting things that our lab has along the way very very good uh very successful smart people said don't do

this there's no way this is this this is going to lead to anything and so the only thing I know is that um paths in science are no nobody has a crystal ball paths in science are very hard to

predict and people should really be very um circumspect about being being t taking extremely seriously specific critiques of specific things that will help them improve their process versus

these large scale you know sort of career level level things that Um, yeah I don't think I don't think you should be taking almost anybody's advice about that. Can you be specific and give an

that. Can you be specific and give an example of where you liked the minutia of a critique and then where you disliked the grand scale critique?

Yeah, I mean the minutiae happens every day because because uh you know every day we get um we get comments on uh you know let's say let's say a paper submission and and and we see and

somebody says well you know you you're it would have been better if you if you included this control or I I don't get it because you know uh uh you know it's clear it's clear that

that the um uh that the reviewer didn't understand what you were trying to get at and so that's that's on us that's on us to to to to describe it better to do a better experiment that forces them to accept the conclusion whether they like

it or not. Right? The best the best experiment is is is one that really uh it it forces the reader to a specific conclusion whether whether or not they wanted to go there. It's it's

irresistible. It's it's so compelling.

You know, it's clean. It's compelling.

So, that kind of stuff happens on a daily basis where you see where what somebody was and wasn't able to absorb from what you did and you say, "Okay how can I do this experiment better?

what kind of a result would have gotten us to a to a better conclusion where everybody would would have you know been able to see. So that that stuff happens all the time. Um the other the other kind of thing I mean I'll I'll give you

an example uh uh from the from the tail regeneration uh kind of uh era. Uh we we showed we showed that normally when when tadpoles normally regenerate their tail

it um there's a particular proton pump that's required for that to to happen.

You know a a proton pump in the in the um frog embryo. And so what we showed is that you can get rid of that proton pump and then the tail stops regenerating and then you can rescue it by putting in a

proton pump from yeast that has no sequence of structural homology to the to the to the one you knocked out of the frog but it has the same bioelectric effect. Right? And there that's how you

effect. Right? And there that's how you show that it really is bioelectricity.

Right? So so so we had two reviews on that paper and the first reviewer said oh you found the gene for tail regeneration that proton pump is the gene for tail regeneration. get rid of all the electrical stuff. You don't need

it. You found a gene for tail

it. You found a gene for tail regeneration. The second uh the second

regeneration. The second uh the second reviewer said, "Oh, the the gene obviously doesn't matter because you just replace it by the proton pump." So

by the one from yeast. Uh yeah, get get rid of all of that and just do the just do the biological stuff, right? So, so

that shows you right away that two different perspectives, right? Each

person had a a particular way they wanted to look at it. They had exactly opposite uh uh suggestions for what to what to throw out of the paper. And only

together do those two perspectives explain that what's going on here is that yes, the natural the embryo naturally has a way of producing that bioelectrical state, but what actually matters is not the gene. It's not the

it's not how you got there, it's the state itself, right? And so and so that kind of a thing th those kind of perspectives or you know the uh the the

uh the people who are upset at um you know for example calling zenobots bots right we call them bots because because it's we think it's a bio robotics platform., So so, one, thing, that, happens

platform., So so, one, thing, that, happens is that um you've got uh you've got the people that um are sort of from the organis tradition and they'll say it's not a robot it's a living thing. How you

know how dare you call it a call it a robot. Uh, and part of the issue is that

robot. Uh, and part of the issue is that all of these terms, much like the cognitive terms that we talked about it's not that the Xenobot is or isn't a robot. It's simply the idea that by

robot. It's simply the idea that by using these different uh using different terms which are signaling is what are some of the ways that you could have a relationship with it. So, for example we think that we might be able to program it to use it for useful

purposes. That's what the bot that's

purposes. That's what the bot that's what the terminology bot emphasizes. Do

I think it's only a zenobot? Absolutely

not. But I also think it's a protoorganism with its own you know its own limited agency and its own you know things that that we haven't published yet which we're working on its uh their

learning capacity and and so on. So um

you often run into that is that people think any everything should only be one thing and that right and that this is all a debate about which thing is it and I don't I don't think that's true at

all. Um there's another uh just just you

all. Um there's another uh just just you know kind of one one last example um again having to do with with terminology. Somebody said to me once

terminology. Somebody said to me once you know, uh the re people are very um resistant to the use of the word memory for some of the things that we study.

And she said, why don't you uh why don't you just come up with a new term, you know, shmemory or something. And then

nobody has to be mad, you know, you can say, okay, you like this is, you know human human learning is memory and then this other thing where these other things learn well that's shmeymory. So

then and that that's the kind of intelligence. Why you're calling it

intelligence. Why you're calling it intelligence? Yeah. Yeah. Exa Exactly.

intelligence? Yeah. Yeah. Exa Exactly.

And and that's the kind of Okay. So that

that's just an example of the kind of advice you might get from somebody and and in a certain sense it's true that if you do that you will have fewer fights with people who are very purist about you know they want they want memory to

be in a very particular box you'll have less fights with those are true but bigger picture though imagine um so there's there's Isaac Newton and you know the apples fall I mean I know it didn't really probably happen but but

let's you know the apples fall in the tree and he says okay so so gravity I'm going to call gravity the thing that keeps the moon you know in orbit of the earth And then I'm going to call schmavity the thing that makes the apple fault. That way there won't be any

fault. That way there won't be any arguments, right? Like yeah, but what

arguments, right? Like yeah, but what you've done there is you've missed the biggest opportunity of the whole thing which is the unification. The thing that the fact that actually no, the hill you want to die on is that it's it really is the same thing. You don't want a new

term for it. So that's that's just an example of of the kind of, you know, it it's good advice if you want to um avoid arguments, but if if your point is that no, it actually is that's the whole point. We need to have a better

point. We need to have a better understanding of memory. this is this is you know I want those arguments then then that's that's something else and that's the kind of you know that's the kind of um strategic thing that you should decide on your own what you want

to do. Now in that case why couldn't you

to do. Now in that case why couldn't you just say actually it wouldn't have been a mistake for Newton to call this one gravity one and that one gravity 2 until he proves that they're the same mathematically just like they're

different there's inertial mass and then there's another form of mass and then you have the equivalence principle.

Yeah, you could you you could uh the thing is that um in in my my point is the issue is that we never know a priori whether we're supposed to unify or distinguish. That's correct. Yes. A no

distinguish. That's correct. Yes. A no

true true a priority you don't know. And

so the question is in your own research program uh which road do you want to go down to because because because if you if you commit to the fact that um that I that they're separate, you don't do the

you don't try the unification, right?

you you try the unification you spend your time I mean it takes years right you spend time and effort in a particular direction because you feel it will pay off if it were truly uh you know it could be this or that are you

going to spend 10 years on one of these paths right you you really need to in science you don't there's no doovers like you commit those those 10 years are gone so so you need to have a feeling you need to have an intuition of which way it's going to go and you definitely

don't need to declare ahead of time that I know how it's going to turn out because you don't but you do need to know despite everybody telling me this or that I am going to commit. That's

really all you have, right? You you

don't you don't have any kind of crystal ball. You don't have a monopoly on the

ball. You don't have a monopoly on the truth. But what you do have is uh a

truth. But what you do have is uh a responsibility to manage the limited time that you have. So, how are you going to spend your 10 years? Um and and it's going to be hard, right? Lots of

blood, sweat, and tears. It's a hard job. There's, you know, constant

job. There's, you know, constant criticism, and that's how science goes.

Um lots of uh lots of stress. But so now the question is, are you going to have that stress following somebody else's research agenda or yours? you'll you'll

still be old and stressed out by the end of it. But the question is, will you

of it. But the question is, will you have tested out your own best ideas or somebody else's view of what science should be? That's my only hope. Well

should be? That's my only hope. Well

Michael, speaking of limited time, I appreciate you spending yours with with me and with the crew here today. Super.

Thanks so much. Thank you so much. Thank

you. Thank you so much. Yeah, it's great to see you again. Uh great discussion. I

I love talking to you. Thanks for having me so many times. Um it's been it's been really excellent. So, Taylor Swift has a

really excellent. So, Taylor Swift has a tour called the Eeras Tour. Okay. Okay.

You've been around since 2000, active in the in the field. This is akin to the Michael Leven eras tour. All of

Michael's work, well, not all of it, but the milestones, the greatest hits in approximately 2 hours or so. So, share

this if you're a fan of Michael's work.

And well, Michael, thank you. Thank you

so much. I really appreciate it. Thank

you.

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