Discussion with Michael Johnson 2

Transcript

00:00:00Today, I was interested in broaching a new topic and thinking a little bit more about consciousness.

00:00:13We've discussed this a little bit.

00:00:16We talked about vasocomputation last time.

00:00:22I guess what I want to say today is maybe a potential meet-the-middle approach or merging

00:00:33what I would say Michael Levin thought with Michael Johnson thought and see where that

00:00:41can go.

00:00:41Sure.

00:00:42That's great.

00:00:43Yeah, let's do it.

00:00:43Yeah, awesome.

00:00:45So, yeah, just a few.

00:00:48I just have some notes here.

00:00:50I'll just read from them.

00:00:53Just a few notes on my approach to consciousness, dealing a lot with formalism, structuralism,

00:01:04symmetry, valence, physics, and what I'm calling strong monism.

00:01:11And then vasocomputation as the neural system and the vasomuscular system coordinating on

00:01:20patterns.

00:01:21And I guess what I would say that a big theme is how do we get to a proper science of consciousness?

00:01:31And maybe there are certain levels of organization that have somewhat unique affordances for understanding

00:01:38consciousness.

00:01:41And then I think that to put some words in your mouth here.

00:01:48I think that I agree with Michael.

00:01:50I think that we have to be very, very careful about how we read your work.

00:01:51And it's like, there's this sort of beautiful, multi-scale approach to everything.

00:01:58And so collective intelligence and diverse systems having agents and goals, or agency

00:02:05and goals.

00:02:06So, TAME, and I've heard you mentioned polycomputing, and sort of everything is doing some sort

00:02:14of processing and whatnot.

00:02:16Stressors, surprising competencies.

00:02:19So, that's a good point.

00:02:20And then sort of diverse systems having predictive models of the world, predictive world models,

00:02:26and sort of this focus on emergence.

00:02:31So yeah, I want to pause here.

00:02:34Anything else that you would add?

00:02:38Well, we can also talk about some of the latest things that I've been talking about as far

00:02:43as the role of, for lack of a better word, platonic space and so on.

00:02:50And I think, you know, also, just to mention that I don't, the majority of my work is not

00:02:55about consciousness per se.

00:02:57I've been talking about it more recently.

00:03:00And in fact, just this morning, a new talk has gone up, which was a talk I gave at a

00:03:05consciousness conference of last week.

00:03:07So I've said a few things about it, but you know, I haven't made any strong claims about

00:03:11it really.

00:03:12And certainly, I don't yet have my own theory of consciousness to put out there, but I do

00:03:19think about it a bit.

00:03:19So, yeah.

00:03:20I'm happy to, you know, sort of play off of whatever you want to say about it.

00:03:24Yeah.

00:03:25Great.

00:03:26So I guess I kind of want to talk about, are cells conscious?

00:03:32And so you've dug pretty deeply into the biochemistry and sort of electrical profile of cells.

00:03:40And it's sort of one claim that I'd make here is that there are a lot of different sort

00:03:47of theories of consciousness out there.

00:03:50You know, that approach, you know, do systems have a world model?

00:03:58Do systems have integrated information?

00:04:01Markup blankets, quantum coherence, quantum decoherence?

00:04:05Are they sort of EM pockets?

00:04:07What is their shape in sort of space, I would say.

00:04:13I would say that cells are sort of this sort of interesting system where basically any,

00:04:20any theory of consciousness you come to the topic with, cells sort of check the box.

00:04:28So they're pretty interesting.

00:04:30Like I think that, like I think cells are conscious and I think you think cells are

00:04:36conscious and it would be interesting to sort of explore the biochemistry of that.

00:04:41Yeah.

00:04:41Well, I guess the first question we should talk about is, do you think that's a, is that

00:04:47a binary question that we're asking?

00:04:51In terms of things either are or are not conscious?

00:04:54Is that, how you're thinking about it or more of a continuum

00:05:00view? Right, right. Yeah. One second. I'm getting a little hot. I'll open the window here. Sure. Yeah, that's a good question. I think, you know, I think of

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00:05:28linked to space-time and sort of as having boundaries in space-time.

00:05:36And this may be a difference in sort of how we approach this.

00:05:41And I think like my sort of kind of beat in the middle approach is like, I think that we,

00:05:50like both our sort of themes around consciousness would sort of identify the cell as sort of a

00:05:55plausible conscious system. And I think that like there's going to be like a lot of edge cases.

00:06:04And then like we can pretty confidently say, okay, like healthy neurons,

00:06:13like are generally pretty conscious.

00:06:17Yeah. So, so, you know, specifically, I think that it is,

00:06:25it is,

00:06:26I think the question is what kind and how much, and I suspect that, yeah, I mean, I do think that

00:06:37well, what, what, what we don't know yet is to what extent consciousness tracks intelligence.

00:06:43Are they, are they, they're not the same thing for sure. You know,

00:06:47Anil Seth has this diagram where they're pretty much orthogonal, you know, he's got two,

00:06:50two, two perpendicular axes before. I don't know if they're completely orthogonal or if they sort of,

00:06:56tend to tend to track each other. I suspect they do, but, but I, I think any, any system that

00:07:04has that has goal directedness and is putting forth effort to try to reach particular States,

00:07:08as opposed to other States is going to have an inner perspective that, that matters.

00:07:14And the way I, and then we'll, we'll get to, we'll get to the platonic space stuff later,

00:07:19I guess. But the way I like to think about it is that in certain kinds of systems, the, the, the,

00:07:26the way of looking at it at the world from its perspective is different. So if you have a bumpy

00:07:30landscape and you're looking and there's a bowling ball on this landscape, your view as an outside

00:07:37observer basically tells you everything you need to know. You can, you know, exactly what's going

00:07:40to happen as a third person observer. But if you have a mouse on that same landscape, your view of

00:07:46the landscape is kind of irrelevant. What matters is the mouse's view of that landscape, because it

00:07:50could be completely different. He might've been rewarded and punished at certain areas. He might

00:07:53have different, different attention, you know, all kinds of things. And so it's all very, very

00:07:56preference, whatever. So the degree to which you have to adopt the perspective of the agent in

00:08:02order to know what's going on is relevant to how much of a first person perspective they will have.

00:08:07And so, you know, I think being able to recognize that as a two way IQ test,

00:08:13you know, if we don't know how to take that first person perspective, and I think we're

00:08:18really bad at it. So people argue with me all the time, they say, you know, your liver can't be

00:08:22conscious, I'm conscious. And, you know, nobody actually has a story to tell why the electrical

00:08:28networks of the liver are somehow barred from the things that they think the electrical networks of

00:08:32the brain are doing, that there is no story like that. But everybody assumes there is. And they

00:08:36take their native, you know, certainty about these things, which just, you know, the priors that we

00:08:43got from our evolutionary history, they sort of people often mistake that from some kind of a good

00:08:48argument. So to the extent that sells, I think,

00:08:52absolutely.

00:08:52Absolutely navigate spaces with with valence and reward functions. And they have, you know,

00:08:58they have all the same mechanisms and the same evolutionary history and the same kinds of

00:09:05behavioral repertoires that we see complex organisms doing at least to a smaller extent,

00:09:10but a lot of the same stuff shows up. Yeah, I see. I see absolutely no, no, no reason why you

00:09:15wouldn't, you wouldn't think that they have a degree of consciousness. Now, personally, I think

00:09:19it goes far below that. I don't think you need to be alive or anything like a cell.

00:09:22I think you need to be alive or anything like a cell to be on that to get onto that spectrum. But

00:09:25but but anyway, the important thing is, I do think it's a it's a it's a spectrum.

00:09:29Yeah, nice. Yeah, that makes a lot of sense. And I think that, um, like the sort of perspective of

00:09:35it's the perspective of the like, agent like process that matters. I think that's, that's very

00:09:41right. And I guess I'm, I think that there might be an opportunity to sort of figure out like, okay,

00:09:49what is the typology of

00:09:52a cells world model, like a cell state, world model, like what sorts of things cells might

00:09:59sense, and

00:10:00overall metaphor that I'm going to is cells as qualia pixels in our canvas of experience.

00:10:12So much as we are sort of a conglomeration of cells, our experience is also a conglomeration

00:10:19of many cellular microstates. And so then you sort of can dig into, okay, what kind

00:10:30of values can these pixels take? And then what's happening when a cell depolarizes?

00:10:38And maybe the sort of intensity of the pixel is the B-mem of the cell. And then from sort

00:10:49of the

00:10:50cells are sort of faced with many, many informational imperatives, we can say, where like they

00:10:57had to understand, okay, like, is my environment dangerous? Is it acidic? And then like some

00:11:05cells like, you know, in an organism, some cells specialized in sort of detecting, you

00:11:10know, hydrogen ions in the environment. And they sort of turned into like sour taste buds.

00:11:18And likewise, you know, other cells specialized in, you know, is there umami in the environment?

00:11:25Is there like amino acids with hydrophilic side chains that could be useful, nutritious?

00:11:33So I guess I want to say that there's, it looks like to me that there's an interesting

00:11:40sort of typology of cell microstates.

00:11:47Yeah.

00:11:47And that's where, which could sort of very cleanly map potentially to micro sensations.

00:11:58Like if you took a, so basically if you just kind of categorized all the ways that sort

00:12:08of all the different cell types, you would get a list of different possible types of

00:12:16quality values.

00:12:17Yeah.

00:12:18Does that make sense?

00:12:19Yeah. Yeah. I see. And these, these, um, equalia values are qualia of the cell or,

00:12:26or when you say they're pixels, you think they, um, they somehow add up to the qualia

00:12:31of the animal that they're, that they're part of?

00:12:34Uh, I think the cell actually is conscious of that. Like that is what the cell

00:12:39feels like. And then we are sort of a super set of, uh, of these cells.

00:12:46I see. I see. I see.

00:12:48Yeah. Yeah. Yeah. I mean, um, I, I, I think, I think it's, it's reasonable though. So certainly

00:12:59the first part is reasonable fit. Try trying to, trying to figure out what the world of

00:13:02a cell looks like based on the things that cares about in physiological space in the

00:13:08transcriptional space. I mean, there's a long history of this, this business of the

00:13:11umwelt, right. And trying to, trying to get inside a creature's head by, by asking yourself,

00:13:16what does it, you know, what, what does it do? What does it do? What does it do? What,

00:13:17what matters to it? I think that's reasonable. Um, I, I, so, so while, while I am a panpsychist

00:13:22in that sense, I don't actually think that we are trying to solve, uh, the combination

00:13:28problem here. That is, I don't think that our consciousness is some sort of aggregate

00:13:32or, or amalgam of our components consciousnesses. I think that we have this, this, the cells

00:13:40inside us have, have some degree of consciousness, the tissues and the organs do as well. And

00:13:46so do we, but, but.

00:13:47At every point, I don't think it's created by summing up the parts. I think the larger

00:13:54scale allows, it allows a better interface for an aggression of a more complicated consciousness

00:14:00that actually comes from this, this platonic space. Right. I think, I think our, our, our,

00:14:05our physical bodies, including embryos, you know, biobots, uh, whatever, um, robots, whatever

00:14:12are all sort of haunted by these patterns in the same way that triangular objects are

00:14:17haunted by the truths of mathematics that pertain to triangles and to, um, you know,

00:14:22prime numbers and then all of these kinds of things. It's, it's kind of like, it's like

00:14:25that, I think. So, so I'm not trying to, I'm not trying to do any kind of a summation of

00:14:30consciousness of the parts, but, but, but I do think that the cells have it in quite

00:14:34probably the components within the cells as well, actually, um, from, from what we can

00:14:40see.

00:14:41Sure. Nice. Yeah. Um, so I want to talk a little bit about the, the platonic realm.

00:14:46Uh,

00:14:47Although just to, to sort of, uh, close this loop. Um, I think that like my expectation

00:14:54is that the, the body sort of, if you look at it in four dimensions,

00:15:00sort of three dimensions plus time.

00:15:03Like consciousness is sort of, you know, these sort of, you know, probably dominantly affected

00:15:12by the EM field.

00:15:14And it may sort of...

00:15:19There's probably one sort of biggest chunk of consciousness.

00:15:23And then we call that our consciousness.

00:15:26consciousness. But there may be smaller chunks in four dimensions. And like, for example,

00:15:31the liver may have its own sort of pocket of consciousness, which we don't really have

00:15:38direct access to. And so we can interface with, but not really in control. So I guess

00:15:47I was thinking about the platonic mind hypothesis that, you know, we sort of are tapped into

00:15:53this sort of larger and almost more beautiful space of sort of dynamics of possibilities

00:16:04of these platonic forms of shapes. And you've written about this. And I guess I'm wondering,

00:16:11to what degree could they be considered symmetry groups?

00:16:16Yeah.

00:16:19Well, my current model and all of this is up for grabs, of course, but my current model is that platonic space has levels or domains, parts of which are occupied by things that we recognize from math.

00:16:36So this is where like the low agency version of things like the truths of number theory and things like that live there.

00:16:43And then there are similar regions for things, more abstract things like symmetry groups, possibly, you know, the kinds of things that Plato and others talked about, you know, beauty and things like that, right, that may be related.

00:16:58And then there are regions that are also occupied by more complex dynamic forms that we would typically recognize as behavioral propensities or kinds of minds.

00:17:09And, you know, are they the same as symmetry groups?

00:17:12I don't know.

00:17:13I probably wouldn't think so, but we don't know.

00:17:17How do you see it?

00:17:20Yeah.

00:17:21I mean, I think that past a certain point, you get to sort of this, you know, a lot of things work out to be equivalent.

00:17:33So like the platonic shapes, you know, are equivalent to like some sort of mathematical classes and so on.

00:17:40So I don't know whether to sort of anchor this.

00:17:43To symmetry groups or to sort of a more general platonic frame.

00:17:47I guess to touch, like to take this back to the sort of sensation stuff, you know, I'm, I know is I'm in awe of chemistry.

00:17:58That there's this, this sort of, we can say mesoscale structure where it's, you know, chemistry is not necessarily sort of inherently in the laws of physics.

00:18:10It's emergent from the laws of physics.

00:18:13And, you know, one of your colleagues, Eric, he all has this wonderful causal emergence 2.0 paper just kind of talking about how real our, our various things.

00:18:28And sort of can the whole be more real than the sum of its parts and so on.

00:18:33And I guess I would just observed that chemistry is surprisingly real.

00:18:37That, you know, okay, maybe what really exists is like electrons or something like that.

00:18:43or fields, or strings, or strands, or, you know, there's many sort of approaches in physics

00:18:49to sort of what really exists. But chemistry is surprisingly real. It's sort of a way of

00:18:59course-gaining reality that is surprisingly sturdy, stable, predictive, descriptive. And

00:19:13I was looking for, okay, what could analogous structures look like in consciousness? And

00:19:20so how can we course-grain sensations in a similar way? You know, I've thought about,

00:19:30okay, is there like a periodic table of qualia to be found and so on. But you know, it's

00:19:36the periodic table is based on this harmonic structure and valence shells and so on. But

00:19:42I guess like, you know, I'm not sure if I can answer that question. But I think it's

00:19:43like, the move that I would want to make is something like maybe sort of these atomic

00:19:51sensations that we have as humans, sourness, bitterness, sweetness,

00:19:59smell of citrus.

00:20:02I think David Guinty has written about 15 to 18 different types of touch receptors and done some great work there.

00:20:13And, you know, can we understand each sort of, each of these as a different sort of symmetry group or symmetry breaking event?

00:20:24And then if we could do that, I feel like then we could sort of slowly build up this basic alphabet of human sensation based on sort of what's happening in the cells themselves.

00:20:45Yeah, interesting. Do you know if, have any aspects of chemistry or chemical reactions

00:20:53been analyzed?

00:20:54For example, from the perspective of causal information theory or anything like that?

00:21:00Because we just did something like that that's coming out in a couple weeks.

00:21:04But have you seen anything like that?

00:21:06Nice. No, I haven't.

00:21:09Yeah, I hadn't either. But what we did was, this is Federico Pagosi's work in my group.

00:21:16It's really, really wild. Basically, well, I'll take a step back.

00:21:23You know, when

00:21:24you have a rat and let's say you do some associative conditioning.

00:21:29So if the rat presses the lever, it gets the reward.

00:21:32Well, we know that no individual cell has both experiences, right?

00:21:35So the foot of the rat touches the lever, the gut gets the delicious sugar.

00:21:40But you know, in order to have that associative memory, you have to be a collective intelligence.

00:21:46You have to have an integration that allows the rat to know things that none of the individual cells know.

00:21:51Yeah.

00:21:52Clear enough.

00:21:53What I wanted to know was, what are the things that the rat can do to help the individual cells?

00:21:54Does it work in the opposite direction? That is, if you train something,

00:21:58does it become more of an integrated agent by virtue of being trained?

00:22:03In other words, does forming new memories raise your causal emergence?

00:22:08And so we looked at it in the context of models of gene regulatory networks.

00:22:12So this is just chemistry. There's no cell. There's no, you know, there's nothing.

00:22:16All there is, is a set of differential equations that control how certain chemicals turn other

00:22:23chemicals on or off. That's it.

00:22:25And previously, we have a few papers previously showing that when you have a system like that,

00:22:30it can learn. It can do about six different kinds of learning. It can do habituation,

00:22:35sensitization, associative Pavlovian conditioning, and so on. So what Federico did was he looked at

00:22:40a measure of Phi D, of causal emergence as we train these things. And he found that these networks

00:22:49divide into several different categories. We don't have a good name for it yet.

00:22:55But in some of these categories, so not all networks, but some and many,

00:23:01the more you train them, the higher the causal emergence goes.

00:23:05Oh, wow.

00:23:07Yeah, it's pretty wild. They do become, I wrote a blog post about it. And at the end,

00:23:13I have a diagram of Pinocchio. And, you know, he was told, if you want to be a real boy,

00:23:18you got to go to school. And that's the thing, right? It like reifies the process of learning

00:23:22new things as a collective. Right? So, yeah, that's a good point. I think that's a good point.

00:23:24reifies the agent as a collective intelligence. And you can quantitatively, you can watch it

00:23:29happen. And there's some other interesting aspects to it. But, yeah, I mean, chemistry, apparently,

00:23:37does already have these features, you don't need to be a cell to do this. And, yeah, we have some

00:23:43other stuff that isn't public yet, that it takes it one step further, and, you know, the origin of

00:23:50these things, and so on. So, yeah, yeah, I agree with you, chemistry is already, you know, I don't

00:23:54know, I don't know what we could do below that, if there's anything, anything, you know, in the at

00:24:00the particle level that could be analyzed this way, but the chemistry is already doing it.

00:24:04Right. Nice. Yeah, I mean, it does seem like you're, you're sort of putting some

00:24:09optimization pressure on, on the integration term. And I guess what comes to mind is like,

00:24:19Zurich has this quantum Darwinism brain that like, even at physics, like physics is the product of,

00:24:24of some natural selection for patterns that can persist and copy themselves into the environment.

00:24:31When he says physics, does he mean specific physical phenomena? Or does he mean the laws

00:24:38of physics? Like, is he talking about a small and kind of multiple universes thing that's Darwinian?

00:24:42Or does he mean, within our universe, the patterns are the physical instances are trying to persist?

00:24:51I believe his work deals with the patterns in

00:24:54our universe. So kind of motifs in the, I guess the formal term would be like motifs in the Hamiltonian.

00:25:00I wouldn't want to define that. Nice. Interesting. One thing that comes to mind here, there's always these questions of everything can be multiscale. And then the next question

00:25:28is, what are the sweet spots to coarse-grain the system on? To say, okay, this is a really interesting phenomenon that doesn't necessarily happen in the same way at other scales, but it does happen at this scale.

00:25:45And so I guess my sort of attention on the cell is this sort of ping pong between hyperpolarization and depolarization. I mean, neurons and muscle cells and some obscure immune system cells and so on, they sort of obsolete between a polarized and depolarized state.

00:26:16And so I'm sort of imagining sort of a

00:26:17sort of

00:26:17computational thing. And there are like cool things to do with how muscles move and how

00:26:25neurons fire. So movement and communication sort of arise from this dance between the

00:26:33sort of really charged state and the state which happens when that charge kind of gets

00:26:40released and collapses. And the question that I'm looking at right now is sort of what

00:26:52happens to the cell's internal structure when it depolarizes. And I guess to just say a

00:27:04few words there, I'm looking at depolarization as a symmetry breaking.

00:27:10So, you know, you pump energy into it and you sort of create some symmetries and that's

00:27:17sort of, we can say the, for most cell types, that's the neutral state. And then you break

00:27:24that symmetry and it sort of, maybe physically, but more so electrically, it sort of collapses

00:27:33into a more high entropy, more directional state. And I'm just wondering, like, what

00:27:40your intuitions are in terms of, like, if there's some sort of origami, like cells origami,

00:27:49and if you pump up their energy, they sort of unfold. And then when you release the energy,

00:27:56they sort of collapse. What's that look like?

00:28:00Yeah, that's an interesting way of thinking about it. You know, what we see from our work in

00:28:07non-neural cells is that, you know, we're not going to be able to see the energy that's going to

00:28:10voltage change is slow and gradual. Now, all

00:28:13be coming out of the cell. All of these things are relative because it has a unit associated

00:28:16with it. So they seem slow or not to us, but it's all relative, of course, but slower than what you

00:28:22see and much slower than what you see in neuroscience. And the symmetry breaking that we see is spatial

00:28:30at the level of a multicellular collective. So you have an initial homogenous pattern

00:28:36of cells and you've got these, just for example, you could set up these local amplification

00:28:43long range inhibition loops that basically symmetry will break a certain cell will well

00:28:49let's say depolarize and become an organizer or something and it will automatically tell everybody

00:28:54else basically you you don't do it i'm doing it it will suppress everybody else right so that's a

00:28:59that's an example um of uh of that kind of thing and and but but in any case much like with touring

00:29:07patterns you can have uh symmetry breaking and spontaneous pattern formation in electrical

00:29:14with with no underlying hardware differences you know so purely at the level of the physiology

00:29:18that can happen so so yeah so so we see that as a multi-scale a kind of thing uh well one one thing

00:29:25that i've always wanted to do and i have a student that's actually gonna gonna try it finally is uh

00:29:30do some of the voltage mapping uh okay we've already found we've already mapped in in within

00:29:38individual cells the voltage is not homogeneous so we already know there are patterns within single

00:29:42cells but but

00:29:43most single cells are kind of featureless in the plane so we so what i want to do is work um examine

00:29:49some some very highly patterned cells so some ciliates you know we're talking paramecium

00:29:54luckily you know this this kind of thing that has that has very very uh very complex patterns

00:30:00yeah, so what does the voltage look like, right, within a single cell? Are there regions?

00:30:06I'm almost certain. We did a little bit of Stentor, I think, in an old Danny Adams paper from my group

00:30:12like a while back, but there needs to be a lot more of this done.

00:30:16Nice, nice. Yeah, that seems really interesting. And I think like one question that comes up in

00:30:24thinking about this a lot is like, you know, how do you proxy the internal structure of the cell?

00:30:33Like, you

00:30:34And what do we even mean by sort of internal structure? So, just in terms of like

00:30:42cell membrane polarity, Nick Lane has some great pieces. I think he gave a talk about what is a

00:30:49feeling in biophysical terms and like talked about sort of different, like,

00:30:54what are the different places on the membrane would be the configuration of the electrical

00:30:59membrane would correspond to sort of how the cell might feel. And I thought that was a really clever

00:31:05approach. Another sort of cluster of ideas, and I know that, so I've been speaking with Ben Anderson

00:31:18and his team.

00:31:20and a friend.

00:31:24Yeah, I've been talking to a friend, Nick Ford, about this a lot. And it's basically this idea of

00:31:30is the water within the cell structured? And this, you know, gets into Gilbert Ling's work,

00:31:38Albert St. Georgi and so on. And like this could be like an interesting proxy for what

00:31:46else is happening in the cell, but it also could be sort of causal in this, in a sense. But anyway,

00:31:53it should be a very sensitive topic. And I think that's a really good point. I think it's a really

00:31:54sensitive thing. And so I guess, have you spent much time thinking about what could be happening

00:32:03with like the water and the hydration shells around proteins and so on and so on?

00:32:08No, I haven't. I mean, it's certainly an interesting thing. You know, Jerry Pollack has

00:32:12written about this kind of stuff a lot. I'm sure there's something to it. We have not studied it

00:32:18much. We have not. Okay.

00:32:20Yeah.

00:32:24Yeah. It's just beyond, you know, I've got my hands full at this point with all the stuff we do,

00:32:29and I don't have any expertise in that anyway. But there are a number of people looking at it,

00:32:34and I'm sure there's something there.

00:32:37Yeah. Yeah. Cool. Yeah. I mean, Martin Picard has also written about sort of Christie alignment. I

00:32:45might be pronouncing it wrong, but basically how mitochondria in the cell kind of align or

00:32:50can get disordered as well.

00:32:54I guess like my optimistic hope here is that a lot of these metrics might sort of overlap.

00:33:03That, you know, if you can measure Christie alignment, you're also proxying water structure,

00:33:08and you're also proxying EM fields, you're also proxying, you know, anything that sort of matters.

00:33:15But that's very weakly held.

00:33:20Yeah.

00:33:21Yeah. Yeah. I tend to think that pretty much all the materials inside a cell are A, being hacked by

00:33:32all the stuff around them. They're being used as a memory medium. They're being manipulated

00:33:36and conversely have their own, some degree of an agenda of what they're going to do in terms of

00:33:43various ends to the goal states they're trying to achieve. I would think that water was probably

00:33:47part of that.

00:33:50Right. Right. Yeah.

00:33:53Yeah. I guess like to sort of put a...

00:34:06To sort of try to say something real about sort of sensation and cells and whatnot. I

00:34:22think it's very important to think about the kinds of possible ways that cells can sort

00:34:25of depolarize or collapse into a sort of less lower charge state.

00:34:30When you say low to mid hundreds of ways, do you mean the channels that are causing

00:34:37it or do you mean the specific physiological states that they can then occupy?

00:34:40The specific physiological states, which will definitely be like correlated with

00:34:45the channels.

00:34:47So if we pretend the whole membrane has one value, then...

00:34:52Yeah.

00:34:52you're talking about a scale that basically goes from roughly zero to roughly minus 80,

00:34:56something like that. And as far as we can tell,

00:35:00the cells are only sensitive to plus or minus five millivolts,

00:35:05any given cell.

00:35:07Like it's probably not going to read any finer than that.

00:35:09So that tells you, right, that you've got a small number of tens of distinct states.

00:35:16However, the cell membrane is not a single value.

00:35:20When we've looked at it, the domains that can be different voltages are about two to

00:35:28five microns in size.

00:35:29So potentially, potentially a cell could be like a soccer ball of different polygons or

00:35:36whatever on it.

00:35:37So that's a lot more.

00:35:39And then, right, so that would be, you know, I don't know, probably in the thousands, I

00:35:44guess.

00:35:44Yeah. Interesting.

00:35:46Because my guess is, and so we don't know how finely cells react to that, you know, how

00:35:53finely do they read that whole manifold.

00:35:55But my suspicion is that it can matter, that there is a code there that it can, you know,

00:36:01that it can interpret.

00:36:02Yeah. Interesting.

00:36:04So I guess the follow up question there would be, it's like, if there are dangers to cells,

00:36:14if like there's some acid or there's a predator, there's like some bad condition, you know,

00:36:23somewhere, or there's some good conditions.

00:36:24Yeah.

00:36:25And then you know, close by and it's like what components of cells would the cell want to be

00:36:33very protective of?

00:36:35It's like, so just to like tell this sort of very simple story with water structure, you know,

00:36:44Ling talks about how the water in the cell is sort of structured around proteins and sort of

00:36:55proteins kind of get unfurled and then water sort of being a dipole molecule, it sort of

00:37:02attaches to the charge sites and then other water attaches there and they sort of hold

00:37:08the dipole such that it's a little bit more polarized. And in theory, you can get sort

00:37:13of chains of water molecules, sort of hydrating proteins. And then just like trying to tell

00:37:22the story about how Ling thought of this as like the living state and it's kind of a delicate

00:37:30balance. And then if you have something like hydrogen ions kind of trying to bump into

00:37:40this, it would disorder this system. And so it would be kind of a danger and kind of it

00:37:49would lead to symmetry breaking of this water matrix.

00:37:52In a specific sort of taste or flavor. Likewise, you'd have something like amino acids with

00:38:04hydrophobic side chains. So things that taste bitter. And if this bumped into this water

00:38:10matrix, it would also disorder. They would also sort of lead to symmetry breaking, but

00:38:15in a different motif with sort of a different flavor.

00:38:21So I guess I'm...

00:38:22I'm looking at sort of cell microstates as sort of corresponding to various symmetry

00:38:30breaks of this water matrix. Now, this is very loosely held, but I guess I think like

00:38:42a big question is like, what is the cell trying to preserve? What is the cell trying to protect?

00:38:51And like, this is one case where I'm like, I'm going to try to find out what the cell

00:38:54candidate uh but it's like sensory states will sort of revolve around like the core

00:39:02things that the cell wants to maintain we can say yeah yeah interesting um i think that's i think

00:39:13that's a good uh that's a good thing to to think about this there's an there's another issue here

00:39:20to think about which is in in induced versus intrinsic motivation so in our and this is just

00:39:32the beginning so i i'm not certain about you know what what the what the bigger picture is going to

00:39:38be but but in our in our work on sorting algorithms yeah these are short deterministic

00:39:44algorithms to sort numbers what we found is that there's the thing that

00:39:50we make it do via the algorithm which is to sort numbers and yeah sorts numbers all right but also

00:39:56there are these weird side quests that it takes that are nowhere in the algorithm

00:40:00They're not prohibited by the algorithm, but neither are they you know uh instantiated by it they're sort of and so and so you can loosely i so so i've been playing with this with this notion of there's the there's the reward function that we force on it but but then there's the intrinsic motivation so i think you can sort of see that in biology too so evolution would be

00:40:22InScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScript

00:40:24say you have to do this and this but in the meantime there's some others that as long as

00:40:29you don't interfere too badly with it too much of the time you're also free to do some other stuff

00:40:34and what that other stuff you know we're used to i think we're very used to looking at biological

00:40:40functions from that evolutionary lens and saying okay why is it doing that that's got to be good

00:40:45for reproduction or it's got to be it's got to be a side effect of something else that's good

00:40:49for reproduction or you know but i have a feeling that that there's also a bunch of other stuff that

00:40:56things are doing even very simple things are probably doing other things that i don't think

00:41:01are coming directly from any of their experiences in the physical world maybe you know whether we

00:41:08can flesh out a theory of of platonic space for it or yeah i don't know but you know it's like

00:41:13it's like some of the stuff that we see the xenobots and the anthropos doing like they do

00:41:18things that were clearly evolutionally

00:41:19important for their primary goal but or their primary lifestyle i should say but when you take

00:41:25them out of that lifestyle then you get to find out here's what it would be doing if the other

00:41:29cells didn't force it to be a two-dimensional skin layer on the outside of the embryo right

00:41:34and normally all that is suppressed and it's it's sort of um uh you know it's like it's like uh

00:41:41you know forcing a kid to sit in class and do math you don't get to find out what else you'd

00:41:45be doing if you if you weren't doing that right but if you but if you let up to some extent then

00:41:49then then you get to find out what the intrinsic motivation is and then possibly possibly you work

00:41:54with that right so there are of course you know educational um uh philosophies that that target

00:42:00that as opposed to trying to you know do a a strict reward function so so i wonder you know

00:42:06when we look at these cells i wonder how much of that and and that also relates to some other

00:42:10conversations that i've had with other people about whether problem solving so we've cashed out

00:42:16all when we study intelligence i define it as a problem solving problem solving is a problem solving

00:42:19it as problem solving so goal directed problem solving but that's just for convenience there are

00:42:23of course other aspects of being cognitive that have nothing to do with with that they're you

00:42:27know just play exploration right there's all this other stuff that isn't captured by the by this

00:42:31kind of thing and so we talked about what does that like we all know what it looks like when

00:42:36birds and mammals play so you can see crows doing these things you know they're sliding down roofs

00:42:40on these on these little little flat things that they've you know found somewhere and they you know

00:42:44clearly like they're just having fun you can you can see it it's not anything useful that they're

00:42:48doing so so the question is what do you think about that and what do you think about that and

00:42:49question is what what does it look like when cells do this so right so there's the evolutionary

00:42:54extrinsic motivation like yeah you have to keep your ph in this level if you don't do that you're

00:42:58going to die fine right but alongside of that what does what does play look like on the cellular scale

00:43:03what what else are you doing and you know and and these you know some people say well cells are too

00:43:08simple to do that if six if if bubble sword can do it i'm pretty sure cells can do it and and you

00:43:13know and so i think i think we're just bad at noticing it is all it is and we need to uh

00:43:19as much as we've been focusing on intelligence and problem solving we we or somebody needs to

00:43:24needs to develop uh some tools to be able to recognize play and exploration in unconventional

00:43:30embodiments yeah yeah nice that's great um i'm i'm such a fan of your your work on xenobots

00:43:38yeah good stuff um and i guess like i was thinking about you know what is

00:43:44you know if we if we take the perspective of um cells as quality pixels

00:43:49um uh although i i keep wanting to use the word quarks as quality pixels

00:43:55i'm getting some pushback on that but um but then uh uh you know taking a look at like what is like

00:44:04a lone xenobot uh look like as a as sort of a dynamic quality pixel how does it how does its

00:44:13value change uh in different environments and like is it this sort of unitary pixel

00:44:19uh that the best way to look at it is like okay like there's the xenobot there's the cell and it

00:44:26has a value or um is it heterogeneous and that you know maybe we could think of its mitochondria

00:44:34as its pixels um so yeah yeah i don't have a clear answer there yeah yeah it's a good question

00:44:46that's a good question uh

00:44:51yeah yeah i don't know i guess i guess we'll have to we'll have to see uh

00:44:55to what extent we end up needing to solve some kind of a summation function

00:45:00Function or not, or whether it's just completely different types of consciousness that shows up when you make a particular interface. Yeah, I'm not sure how much, how constraining the parts are.

00:45:18Yep.

00:45:21For what you get. The causal architecture is clearly important in some way, but.

00:45:27Right, right. Yeah, and I guess this gets into questions of,

00:45:33does consciousness require definite extension and location in space and time?

00:45:42Or can it be more of a logical computational thing?

00:45:47Yeah. I mean, I tend to think that

00:45:52a particular embodiment of consciousness

00:45:56will have location in space and time. That location will be fuzzy to some extent because

00:46:02there is no unified, there is no indivisible intelligence anywhere. We're all made of parts,

00:46:08we're all collective intelligence. And so, I don't know, once you get to electrons or something,

00:46:12I don't know what the deal is in physics. So it's going to be a little bit fuzzy.

00:46:19But the other question that this brings up is, to what extent are there lateral interactions within

00:46:26space in addition to, among things that are not currently coming through any interface?

00:46:32Because if they are not static, which I strongly suspect is the case,

00:46:38then there will be some sort of its own chemistry of patterns in that space that

00:46:43are doing things regardless of their connection in the physical world.

00:46:46Yeah.

00:46:47And those things, then how much spatiality there is, I sort of, I can sort of imagine that it's not,

00:46:56it's not spatial the way we're, it doesn't have a location the way we're used to,

00:47:00but it's much more, it's almost like a, it's almost like a content addressable memory instead

00:47:05of a location addressable, right? So instead of saying, this is where this information is,

00:47:10it's like, well, what is this information about? Well, then it must be somewhere near this other

00:47:14thing, which is about the same thing, right? So something like that.

00:47:20Yeah, that makes sense. Interesting. I guess one, one sort of,

00:47:27for this sort of analysis is that it's always a question of, for me, so I guess nine years ago now,

00:47:37I had came out with this symmetry theory of valence. And sort of similar to what you've said

00:47:46about sort of geometric frustration is real frustration. And it's sort of, if we had a

00:47:53mathematical representation of an experience, the

00:47:57symmetry of this representation would correspond to the pleasantness of the experience. So wrote a

00:48:03short book on this. Yeah. And so it's sort of, it's speaking about, you know, a formalism of an

00:48:13experience and, you know, not necessarily making a big claim in terms of how to create the formalism,

00:48:18but if we had a formalism, how to interpret it. Yeah. And then, but I, I'm always eager

00:48:26to, you know, to, you know, to, you know, to, you know, to, you know, to, you know, to, you know,

00:48:27to try to apply it to biological systems. Yeah. And, you know, there's, there's been a lot of

00:48:33questions about, well, how do you apply it to, to brain or to a nervous system? And I guess I'm,

00:48:40I'm optimistic that it can be applied to like a cells symmetry group. Although there's a big

00:48:48question of how do you coarse grain a cell symmetry group? I think, you know, I think

00:48:52it'd be interesting to try to apply some of these things to,

00:48:57data in, for example, transcriptional space, right. So omix data. What does, what does symmetry,

00:49:04you know, beauty, what does all that stuff look like in the, in that space?

00:49:08We're already trying to think about, what does it look like to have

00:49:12barriers? What does it look like to have, you know, what does a mirror test look like in,

00:49:16in, in, you know, in transcriptional space? Yeah. It's been very hard to think about these things

00:49:20cause we're so obsessed with the three-dimensional world and so on. But I feel like all this can be

00:49:26defined and, and so I'm looking at it in a more qualitative and qualitative perspective.

00:49:27and it would be interesting to see what does symmetry breaking look like in that,

00:49:32you know, in these other spaces.

00:49:34Right, right.

00:49:36Well, yeah, one thing that comes to mind is I do think that symmetry breaking

00:49:42is directional, which is, it's a very useful property.

00:49:47So it's like you have the symmetries of a system,

00:49:51and like a starfish is a pretty simple example where it's just basically

00:49:57a ring of neurons.

00:49:59And then

00:50:00symmetry is the success condition. It's like homeostatic success. And then if a fish comes and starts nibbling on a leg, then the symmetry gets broken in a way that the different parts of an organism can tell where the problem is. There's kind of a lensing effect. And then the starfish can move or

00:50:28adapt to that. And then once it's safe again, the symmetry gets restored. So I guess in terms of looking at transcription networks and so on, I don't know. But it does seem like there's some sort of directional high information perspective that the system can take, such that if you have a

00:50:58symmetry and it gets broken, then every part of the system knows a little bit about where the problem is.

00:51:06That's very interesting. So what I'm hearing is symmetry breaking as a cognitive glue. So some kind of non-locality that is... And yeah, I can see how that would be connected to geometric

00:51:28illustration, right? And so, yeah. And you'd have some sort of propagation speed of light thing for getting it around. But yeah, I think that's very interesting. I think that's worth more development as symmetry breaking as a binding set of policies that create the collective intelligence. I think that's a cool idea.

00:51:58Yeah, nice.

00:51:59Yeah.

00:52:00Nice.

00:52:01Yeah.

00:52:03Nice. Well, I'm mindful of your time. But yeah, any other cool things to talk about?

00:52:14Let me think.

00:52:18I was looking at my notes. We covered most of what I wanted. Yeah, let's go off and think about this symmetry breaking business.

00:52:26And we could...

00:52:28Yeah, I think we could look for it if we knew how to recognize it in the abstract, like in its general form.

00:52:35Yeah.

00:52:37Yeah.

00:52:42Yeah.

00:52:42Yeah. I mean, just a few words on that. So there are different numbers of symmetry in different dimensions. I think in 2D, there are 17 sort of wallpaper symmetry groups.

00:52:55Like, you know, different ways things can...

00:52:57get flipped or rotated. Frank Wilczek has this nice

00:53:03um definition of symmetry as change without change yeah yeah anytime you can apply an

00:53:09operation to a system but leave it yeah same thing yeah and then there there's something

00:53:15like you know 300 plus symmetries in in 3D and I think almost 4,000 and 4D although you might

00:53:22want to check my numbers on this uh but yeah um and then I guess I see in yeah go ahead so I was

00:53:30just gonna say that that by itself is one of these you know people people often ask you what you know

00:53:35what do you mean by by by facts that that don't have a physics I mean that right there like like

00:53:41the number of these groups at under various circumstances that's just what it is yeah yeah

00:53:46that's just that's just how it is that's it there's no you know there's no there's no fact

00:53:50of physics there's no history there's nothing that's gonna that's gonna I mean you know underlie

00:53:54that as a more reductive explanation it just is what it is yeah totally I think I think that's

00:53:59really interesting yeah

00:54:00nice yeah I I also see that uh so the the symmetries of a self-organizing system

00:54:08um I almost see as sort of kaleidoscopic grooves that the system can sort of follow to get back

00:54:16into a state of order um so my water has uh I believe tetrahedral symmetry uh so I I believe

00:54:28that's exactly like 24 symmetry

00:54:30um and

00:54:33like

00:54:34and like every symmetry is sort of a

00:54:36every symmetry is sort of a

00:54:36every symmetry is sort of a like I I think of them like as like grooves

00:54:39like I I think of them like as like grooves

00:54:39like I I think of them like as like grooves in a kaleidoscope that you can kind of

00:54:41in a kaleidoscope that you can kind of

00:54:41in a kaleidoscope that you can kind of um uh

00:54:42um uh

00:54:42um uh follow back to order

00:54:44follow back to order

00:54:44follow back to order and it would be interesting to do this

00:54:48and it would be interesting to do this

00:54:48and it would be interesting to do this sort of analysis for your Gene regulatory

00:54:50sort of analysis for your Gene regulatory networks I I yeah I think I think it

00:54:52networks I I yeah I think I think

00:55:00the calculation. But I think that would be quite interesting. Yeah. Yeah. Yeah. You know, we have, of course there's genomic data, there's transcriptomic data. We have electrophysiological data. We have lots of simulations so we could look at it in, you know, sort of in silico

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00:55:18that.