The Grand Quest To Simulate Life - EP 57 Ed Boyden

Suppose you did simulate a brain, you know, does it have subjective experiences? Would it be conscious? And of course the the core issue in some ways is that we can't really measure consciousness. Like even now you don't know for sure if I'm conscious, right? There's no meter you aim at my head and haha, you have well three out of four or whatever units of consciousness right now.

Um yeah, so in the lab, we are starting to wonder is there a way to to measure consciousness? And a couple ideas. One is that if you have a simulation of a brain, You know, right now in neuroscience we mostly focus on behavior, outwardly manifested.

In the end, movements. I move my mouth to speak, I walk out the door, I you know, there there there's these observables that are governed. But if I'm sitting here daydreaming all morning and I never tell anybody about it, I never change my behavior based on that, there's no way to know that that happened.

So one of my um uh deep hopes is that if we have the simulation of the brain, we can look under the hood and if there's some pattern of activity that doesn't really link to behavior in any way, but we can watch it and simulate it. you know probe at it, we could ask ourselves what kind of information processing is happening in that situation.

Ed Boyden. Hi, how are you? I'm good. How are you? Good, good. Good. Welcome. Thank you. Um, I wanted to talk to you for so many years. I I feel like who run around the world talking to all these interesting people and very often someone the phrase that comes out of their mouth is I worked in the Ed Boeing lab for some of the most interesting people oh w I run into and this seems to happen the most with you and George Churches. Oh yeah.

Wow, interesting. Yeah, you've got this litany of uh of fascinating students and then obviously I followed your work. Um great, great. For people who don't know your research and your work. I I'll just frame it a little bit and then and then please, you know, correct me if I get anything wrong. But um yeah, I'm just I'm so pleased to be a legendary scientist researcher. You

done such incredible work in especially around the brain and w and how we get to know about the brain or what we know about the brain. We are at the McGovern Brain Institute. You're also a professor at MIT and then you are affiliated with or have co-founded numerous startups. Is that fair so far? Yeah. Anything I missed? No, sounds good. Okay. And uh this is funny. Pat McGovern, he was my first boss. Oh wow.

Small world. I worked at ID G uh back in the day as a Cub Cub reporter. So cool. Yeah. Did you meet Pat? I did, yeah. Yeah. Yeah. Pat and Laurie were very involved. Uh I met them many times in the early days and of course Pat sadly passed away. Uh but Laurie still comes to the meetings and uh So I worked at IDG, the publishing side of what he did, how I guess how he made his money really. And every Christmas Pat would come by and

Hand you your Christmas bonus in person. Wow. To like all I don't know how many thousands of employees yeah. He would yeah, he would travel the whole world and then it was it was it was obviously a very nice gesture. It got slightly comical at times because somebody would brief him about who he was about to meet and I was on the crossed wires. Uh he confused two of us and and and he would like he would kinda recount your achievements for the year.

And I just have to nod as he was like talking about somebody else and Wow. Yeah. Well it's so great that he did that. I mean it's all about the people, Dan, and I think that's really awesome that he did that. I didn't know that. It is, it is. Uh like obviously I'm still talking about it, so it leaves leaves an impression. Yeah. That's great. Um that's great.

Okay, well there's a million things I want to talk to you talk to you about, uh Pat McGovern related. If you you know, when I do my research For these shows, I mean, again and again, the thing that kept getting called out was was that you co invented optogenetics, which helped us understand how the brain works in in profound new ways that we couldn't before and that you developed expansion microscopy which is kind of

swelling parts of of the body and the brain so that we can understand them them better. I would I was curious though, you know, when you're reflecting on your work, um, yeah, what are the things that that really stand out to you during your career. Yeah. Well I guess for me it's um these are all like puzzle pieces, but there is an ultimate goal. And uh the goal is really I trained as a physicist, um, an engineer before becoming a biologist. You know, can we understand a biological system?

the same way that an engineer would completely understand a system that they built.

Um of course the problem with biology is we didn't build it and it's also really messy. But I take great inspiration from physics. So in physics they've hit what you might call the ground truth, the list of the parts and how they work together. And uh on the surface of the earth, you know, quantum mechanics is, you know, more or less that that gives you lasers and microchips and cellphones and the internet and all sorts of stuff, right? Um Can we have sort of the microchip moment for biology?

Now, in contrast to physics, where there's like a couple things and a couple ways they work together, in biology there's thousands of things, right? Genes, gene products, biomolecules. And so the overarching vision uh is really can we just understand all of that? Can we map all the parts and how they work together? And my dream is that we can make a simulation in a computer of a living thing. You know, could you

see all the parts working together and maybe even pinpoint where in that network you could treat a disease. Or, you know, maybe someday, this is obviously in the future, could you run a clinical trial on a computer? And so you mentioned optogenetics where we can control

signals with light and then we have expansion where we can map the building blocks of life. And there's a third branch of technology we've recently been putting out, which is how to image many things at the same time in a living system. But the way I think about it, these are three legs of a tripod, and my hope is that we can integrate them and collect the right kind of data that you can use it to make simulations of living.

And that's that's what you feel like you've been charging after your entire career? Like did you you set out with this goal in mind?

Yeah yeah, in the end. Uh uh when I switched from physical I guess I always was very intrigued by the intersection of science and philosophy. And so um my first lab experience was in an Origins of Life lab. They were trying to create DNA out of clay, which of course didn't work or you would have heard about it, but it was still a very educational time. Um I left home really young. I was only fourteen when I started that uh job.

Um and so uh eventually I came around to the brain as a you know, a sort of philosophical practical intersection. Uh but my dream is that we could really understand the human condition, like why do we do what we do and feel what we feel.

Um but the the practical angle that pays the tools that keeps things going and is also very important to me is can we understand these complex biological systems in terms of their We will pause the genius that I am no doubt interviewing right now to tell you briefly about Bracken.

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35,000 plus companies are running on BRACs. Give it a try. You will not regret it. Since you brought it up I was gonna save it for a little bit, but you were talking about when you were fourteen, working on the origins of life. Y I mean, when anyone reads about your biography, one of these things that stands out as you were For all appearance, who looks like a prodigy as as a kid and and started at MIT I think at sixteen.

And and got a triple degree plus a master's degree by the time you were nineteen, I I think. What was it? Electrical engineering? I did a two bachelors in electrical and physics and I did a master's degree in physic uh in electrical engineering. Okay. And you grew up in in Plano, in Dallas. That's right. Okay. And so

I'm always fascinated by people that excel at such a early age. I mean, w I don't know. I mean, what was childhood li did you have some sense that you were a bit different from the other kids pretty early on? Well I had a uh I think a very thoughtful childhood. My mother stayed at home and we would talk about science. You know, we would run little experiments in the kitchen. Um uh my dad uh he's retired, they're both you know

It was a management consultant um and uh so it was a very sort of thoughtful home environment. We talked a lot about, you know, problems and how to solve them and things like that. Um I was probably twelve years old. I went to a science fair and I had my project, which I think was something like microwaving a bean in the microwave or something, and what would happen to it.

But then at the science sphere, other people had like real projects. They were looking at cancer genes and all sorts of stuff. And I was like, wow, I need to get to a place where I can do this. And so I just got really uh hardworking and ambitious and then I started taking summer courses at a local community college and Um the state of Texas has this really quirky and interesting and amazing program called TAMS, the Texas Academy of Math and Science.

And people skip the last two years of high school on their way to college. And so, um I I end up skipping the last I guess you know, four years I guess, more or less, and went at at fourteen. But uh It's on the University of North Texas campus and you get to do real

Scientific work, lab work, you're side by side with college students and it was a lot of fun. So you were home schooled before you did that? No, no. I went to the regular public schools. Oh you did, you did. Okay. Okay. And then I mean you mentioned the science fair.

At twelve, didn't I mean didn't you end up winning the science fair fairly quickly? Oh, there was a later year where uh I did a math project,'cause you know, math you don't need a lab to do it. So I I was uh very intrigued by geometry and the rules of geometry and Did a project that um I don't think

With with a current lens, uh, I would be proud of, but you know, as a as a twelve or thirteen year old and uh I said thirteen by then. Yeah. Um I I was pretty excited that you could do mathematics and uh so math was sort of one of my first loves was that you could Analyze things and think about them. But then quickly the question became what can you do about reality, right? Tangible things, the world, can we make it a better place?

And you and you left home at fourteen to go to the school at the end. Yeah, so at fourteen I went to this boarding school, um, which is on the U University of North Texas campus, and uh they pick a hundred and fifty kids from the whole state and they all move there and It's a very interesting program. Were you the you were the youngest one? I think up till that point I was the youngest person. I mean that has so yeah, is that strange or uh

Exciting, all of the above. I thought it was a lot of fun. Yeah. Yeah. I had a great time there. I made lots of good friends there. Um It was a fantastic environment for doing science, um and it was only half an hour from home. I mean Texas is a big state, so some people had a long commute, uh, but uh, you know, it was not so far away from home that

I would be, you know, too distant from the family. Yeah. Yeah. No, I just I always picture it's kinda you know, just being a young kid off on your own.

Especially w you came to MIT at sixteen. Yeah. Did you live in the dorms? No, no, I lived in Baker House, uh same floor with uh but had roommates, uh the whole nine yards. Yeah. Yeah, and and that was Not that wasn't strange hanging out with all these hard to know what's strange or not strange'cause I have no other reference uh than my own life, I guess.

Uh, for me I was um in a state of constant curiosity. I guess for a long time I had this frame of mind that, you know, I was much younger than everybody. So I was here to learn from them and And so, uh, when I came to MIT I was in a continue I was I was actually studying uh focused on chemistry when I was back in Texas and I thought, All right, I'm gonna continue majoring in chemistry and then

But this is nineteen ninety five and like the whole internet thing was coming out then, you know, web web browsers were just exploding that very year. And so everybody on my floor was majoring in computer science. So I was like, okay, I guess I'll go along with that. Yeah. So I ended up ch switching uh to physics and electrical engineering and computer science, which I don't regret because

Um you know, that turned out to be so useful as as you know. Yeah. And had had you coded or anything before that? I did, yeah, yeah. I guess I was very interested in mathematics beforehand, but I often use um computer code to solve math problems and so that was my my entry point into computer sciences. Okay.

Okay, so if we go back to your your central quest to understand The body almost is this engineering problem. Um I mean there's a there's a bunch of things that I've reported on where we've made Stabs at doing this. The the connectome is this effort to image the brain on the level where you can see individual neurons and synapses and and you know, it's been a struggle. I mean, yeah, we've done a worm, we just finished the fly. Th w it seems like it could take

many years and ridiculous amount of computing power to start doing a human brain on the same level. We've all I think the most we've done is like a cubic centimeter or something. of the the human brain so far. Um well this spring though, um A group in Austria showed that our this expansion method that our group invented um can be used to get knectoric information. And importantly, uh because it's a it's a light microscopic technique, you could also get molecular information.

So the way that I think about thinking about the brain is so the connector of course is the wiring diagram of the brain, the shapes of the cells, if you will. But in the end we're made of biomolecules and biomolecules work by touching and when two molecules touch they can cut, bind or change shape, you know, and of course there's for the case of the brain, electric fields as well.

Um but so I want to map more than just the kinectome. I also want the molecules, right? The molecules that make the cells do what they do. And that in disease states are the things that go wrong. And so this expansion method that we built uh looks like it can give you not just kinectomics. Uh but also the molecules along those wires and so forth. And one of our former students, uh Andrew Payne, is running this.

Uh nonprofit that's called an FRO focused research organization called E11, where they're adding in barcoding as well, basically a way of telling the cells apart. But the point I want to make is

I'm really obsessed with the idea of ground truth. What are the fundamental building blocks and how do they work together? And in physics, of course, you have the particles and forces. In biology, we have the biomolecules and how they interact. So if we can get that We should be able to make a simulation of like

Okay. I mean this is my question where I was going. And Andrew is actually he's coming on the show in a couple of weeks. I've been to E eleven and um it's fascinating. Uh yeah, so you mentioned they barcode they they sort of inject brains with the virus to put all these barcodes in so you can map the wires almost automatically, I guess for lack of a better term. But yeah, I okay, so w you know, we've been on this quest to to map the brain, whether you pick a neuron or or a molecule, um

And it's been this long, arduous path. It's been expensive. Um, we've had like entire nation states trying to fund these efforts. W where would you say we're at and and i if we really wanna get this complete picture of the mind, I don't know, is you know, when do you think this might happen? Yeah.

Well so this expansion method that we developed uh Can you explain how it works? Sure, yeah. Yeah. So um I guess for literally three hundred years the way biologists have imaged cells is with some kind of lens, right? So the microscope was invented hundreds of years ago. That's how cells were discovered in the first place. About 150 years ago, neurons were discovered in the brain. Um but light has a finite size or wavelength, and so you can't see really tiny things.

So many people have tried to come up with tricks. Super resolution microscopes use clever tricks to break that so called diffraction limit. Electromicroscopy, X ray microscopy, you can use particles that have smaller wavelength, basically. Um but they're all tricky in some way, right? You know, x-ray and electron imaging can be quite expensive and they also struggle to give you molecular info.

And light microscopy methods that break that resolution limit are it can be quite slow and difficult to do three D imaging. So So in our group we thought, you know, we have lots of like critical thinking and creativity skills that I I like to think of as as our uh learnable and teachable skills. And so we started thinking like what's the most opposite thing we can do rather than zoom in, and we thought, let's just make it bigger.

So we can take a brain or or any biological specimen for that matter, and we immerse it in a solution of what are called monarchs, basically little building blocks, and they self-assemble into polymers, basically a dense spider web like mess. And that's basically a mesh of polymer that's a lot like the stuff in baby diapers, except that it winds its way through the biospecimen.

So if you do it just right and you process the sample just right, like softening it up a little bit, when you add water, the baby diet material swells, but it makes the brain or whatever it's embedded in bigger. And what I think is kinda the surprising discovery we made is that that expansion process is even. In fact, um with some colleagues in in Germany who we've been collaborating with, um uh it looks like that uh the expansion process might be precise nearly down to atomic scale.

And so the idea of mapping all the building blocks of life throughout an entire system

Uh is no longer science fiction. It sounds like it might be within grasp in the near future. Yeah, I mean'cause I kinda cut you off to explain explain that technique, but but when you say in the near future

Because even if I talk to E eleven, any of the Connect Homics people, they still present it as something of a journey and I I don't I'm not looking for like a precise year, but I mean you think where this is within what, five, ten, fifteen, twenty years or Well, I mean, let's take a single cell. If we were to map all the proteins and nucleic acids and you know the major macromolecules of a single cell,

And if we could simulate that cell, you know, basically if some biomolecules aren't touching, they're diffusing around, and we know the mathematics of that. And if two biomolecules are touching, then you know, with alpha fold and other methods of simulating molecular contact. you can imagine making a model of that

Um you might be able to make a model of a cell. So uh these numbers that I'm going to say now are just made up, but um you know, I think it's very intriguing to think of whether you could try to make a model of a cell and maybe a small brain, like uh that of the worm, C elegans. in the next couple of years, let's say three to five years, would be um ambitious but interesting to shoot for. Now if you show that that can be done, then

What happens, of course, is that more and more people will adopt the technology. We all share all of our tools freely, and optogenetics and expansion are being used by thousands of groups each year. So if we have a way of converting a biological system into a computer simulation, I'm sure there'll be a similar kind of growth afterwards that could be hard to predict. But my hope is that if we can show a proof of concept with a small brain or a small cell or maybe a bit of both.

Um and we do also some work on small fish as well. Um zebrafish. Yeah, larval zebrafish and the worm sea elegans, and then also uh very small cells are interesting as well. Um if we show that's possible, then I think it'll be irresistible for many of of

us of the community to give it a try for different purposes. If you can simulate an immune cell, could you understand how it works? Can you simulate a cancer cell and find its weakest spot? That kind of thing. Okay. But what y you're okay. I I feel like we've been on the same path with the the central connectomer from the from the C elegan. To the fly. to the human and it has still been this slow process. Yeah, yeah. So two thoughts. One of course is that with um

Electromicroscopy, which is how the fly connectome and the worm connectome and so forth were done. Um, again, you see the shapes of the cells in exquisite detail, but it's really hard to identify the, you know, specific molecules, right? And you want the molecules.

The way that brain cells work, they generate these electrical pulses. You have ion channels, you have receptors, you have transmitters. You really want to know where they are. And so my hope is that with our method of expansion, because it lets you label those.

We can help pinpoint them. And you're gonna get and the second is scale. So when you expand something, now you can use much, much less expensive optics to uh image it. And in fact, one tantalizing thought is if you expand something big enough, can you chop it into sections? And then use like dirt cheap optics, maybe even modified kinds of optics, the kind that you find on a cell phone.

to image the brain. So if you can make sort of an asymptotically zero cost microscope, um, and then you use commodity chemicals to do the magnification, maybe we could democratize the ability to do Extremely high volume scalable nanoimaging. Okay, because with the connect home we've been doing these slices of the brain and each slice has to be imaged with pretty much the best Imaging techniques.

We have and it's it th it it it's this manual labor part of this that's part of the reason it's so slow and and difficult. I think it's part of it, yeah. Yeah, we did a collaborative paper many years ago with a couple of other groups where basically it took a hacked webcam.

And then we expanded uh some bacteria. We showed that we could image bacteria with the hacked webcam. So this is not this is not uh out of the realm of what has already been envisioned. Okay. And you hit on it a little bit at the very beginning, but uh

Okay, with the connectome one downside has been that it's you're getting this image of the brain in a fixed moment in time. It's not a living brain, it's just a snapshot of whatever was happening. And so there's There's people who'd argue you can get tons of information even from that snapshot and it's fascinating. And then there's some people who cut it down on how valuable this could be because you you don't have the activity

If we use your techniques to get this much more detailed picture of a brain, what what do you think this unlocks? Yeah. Well so if you have a map of the static organization of molecules of a brain, of course Um one can then look at the molecules and then using the principles of chemistry, which are well known, you could try to simulate what happens next, right? You know, so again, molecules that are diffusing around, you can simulate that if they're bound.

In this post alpha fold world you could try to simulate that interface. But knowing the ongoing activity is also really helpful, right? Like right now there must be millions of these MacBooks that you have on uh all over the earth, but right now they're probably all doing somewhat different

things, right? So knowing the ongoing activity is important because all these MacBooks have the same wiring more or less, but you know, their ongoing dynamics can be quite different. And so the the other two technologies we've been building, which are

the imaging of signals in living cells and then the optogenetic control of living cells, I think are still very important. So my dream experiment would be, starting with a small brain, like a fish or a worm, let's image all the activity, as many molecular signals as we can. Use optogenetics to perturb those cells and look at what happens.

And then at the end of the day, preserve the specimen, expand it, and make a map of the molecules. Those three data sets I think could be combined to make models um even better than if we use the technologies alone from each other. When you so when you say this is your dream experiment, is it something is that How you're spending your days trying to to to cr create that experience. Mm-hmm. Yeah, yeah. I think that um

Yeah, we've kind of two goals. One is to advance each of the individual technologies to bring them to their limits of performance, and then the other is to integrate them so we can get these kinds of

integrated structure and function data sets. Okay. Yeah. And then I mean my and my question about w what you get at the end of this, uh I I guess it's it's sort of a philosophical one. I mean on on one hand you're getting just this immensely useful tool to understand how our body works and and to study it. We're uh also at this Hundreds of billions, trillions of dollars are being funneled into creating an artificial intelligence. I keep

seeing overlap between these fields. I well, you know, this just brings up a million philosophical questions about simulating artificial brains while we're trying to understand how our brain works. And I mean one of the things I was most interested in Talking to you was your take on the convergence of these worlds and and and the interplay between all this. Oh yeah, yeah. Oh it's so intriguing. I guess a couple of thoughts. One of course is that if we can simulate a brain

would you be able to develop interesting kinds of AI that at warlike brains? Um, you know, for like large language models, for example, um now they're very good at language, but uh every week there seems to be some example showing that they're not really thinking the way that we do because they'll make some error that a five year old would would not make, right?

And so um maybe they kinda solve language, but do they solve thought? Probably not at C And so if we can understand how the brain works though, in enough detail that lets you simulate it, maybe that does help you um understand what thinking or feeling or other things are. But that brings us to a second big question, which is almost philosophical, which is suppose you did simulate a brain, you know, does it have subjective experiences? Would it be conscious?

And of course the the core issue in some ways is that we can't really measure consciousness. Like even now you don't know for sure if I'm conscious, right? There's no meter you aim at my head and aha, you have well three out of four or whatever units of consciousness right now.

Yeah, so in the lab, we are starting to wonder is there a way to to measure consciousness? And a couple ideas. One is that if you have a simulation of a brain, You know, right now in neuroscience we mostly focus on behavior outwardly manifested.

In the end, movements. I move my mouth to speak, I walk out the door, I you know, there there there's these observables that are governed. But if I'm sitting here daydreaming all morning and I never tell anybody about it, I never change my behavior based on that, there's no way to know that that happened.

So one of my um uh deep hopes is that if we have the simulation of the brain, we can look under the hood and if there's some pattern of activity that doesn't really link to behavior in any way, but we can watch it and simulate it and and you know and probe at it, we can ask ourselves what kind of information processing. is happening in that circuit. And that that's sorry, go ahead. And then maybe you know, a theory emerges out of what a subjective experience might be.

In the end of course, uh in the current stage of history you still have to test it with, you know informed consent human volunteers who you know maybe we uh will uh there's ways of stimulating the brain with electric fields or other modalities that it let you activate brain cells, uh, even non-invasively in people. Um, and so maybe one could then ask a question about whether that pattern that we saw in the model doesn't actually change um subjective experience.

So the simulation you're talking about is the one that's based off this new era of brain data that you're hoping to get. And and so you would be creating a r a r a replica of the brain, more or less. Yeah. And and and so and then getting getting it to a level where we can watch it We can watch its genuine activity and like probe a brain in ways we can't because people don't want us running around with electrodes out of their head all day. Yeah, yeah. And and then How excited or not?

Yeah, do you get with the progress you're y you you see in the uh in the AI fields. There's people who would want to match the yeah, the the software brain versus the flesh brain and look for Overlap or have the have our AI models based even more on on of the brain to make them sort of more aligned with humans. I I don't know if this is stuff that you get interested in at all.

I mean I've talked to people about it, yeah.'Cause um a lot of people in AI are concerned about things like AI safety and you know, what if you create something that you cannot control and so forth. Yeah, I do think that there are some interesting arguments for simulating brains in support of that. One of course is that if you understand what ethics is, like what is our brain doing when we make an ethical judgment or an empathetic judgment or a socially beneficial judgment.

You know, could we re recapitulate that in some way? The second thing of course is problem solving. You know, so again, you know, LLMs are are pretty good at certain things, but you know, they you know if you're thinking about like generating entirely new ideas that solve a problem.

Um, humans, I think, still have vastly the upper hand on that, um, for for a lot of real world problems anyway. Um, maybe not contrived problems or specific, you know, problems that are defined in in like competition space and so forth. But um You know, but if we wanna have creativity, if we wanna have like effective problem solving, there are things that the human brain does that

We might not even understand them at all. I mean, uh somebody's walking down the street and an idea pops into their head, you know, where did it come from? We don't know. And uh the history of science is full of people, you know, Einstein daydreaming or, you know, the chemists who thought up the benzene ring that appeared to him in a dream, uh when he thought of a snake swallowing its tail. You know, there's all these sort of irrational subconscious things that

are so important for human creativity. And yet maybe we haven't understood any of them completely, maybe even partially, in terms of how the processes occur in our brain. And then finally, I think um there is a hope uh among some that, you know, rather than having AIs over here and humans over here, we'll find ways to work together. And I think for that to happen, we kind of have to understand a bit about how our brains work, right? Because if we enter information in

in a way that is um completely incompatible or has unpredictable effects, right? Um and, you know, every neurotherapy out there, um, to my knowledge, has the a you know decent chance of causing side effects, at least in some people, right? Um, you know, because the brain is a network. You stimulate one part of the brain, it's gonna activate other parts of the brain. And so uh if we really want to have

machines and brains talk to each other in a a really meaningful way. I think we need to learn more about the brain. I mean the hard part of neuroengineering, I think, is often the neuro part. You know, we built You know, as a community, electrodes and non invasive machines to deliver magnetic fields and ultrasound, the list goes on and on. But but where do you aim that energy? Where do you record information? What do you do with it? These are open questions. You seem my you seem kinda

Not terribly impressed with L L L L Ms. Well, it's maybe'cause I'm a scientist looking for, um, in my own life I guess how we could generate really creative ideas. You know, so if you think about really big ideas in biology, for example, PCR, CRISPR, things that really changed the game. Has an LLM built anything of that caliber? And maybe I'm just sitting too high a bar.

Um but I'm very intrigued about how we can make creativity more learnable and teachable and and to boost it. And so if we could build AIs that have that capability, it'd be very exciting. But don't get me wrong, I mean I do see LMs doing amazing things in lots of other domains. Hello, geniuses. Let me tell you about E1 Ventures. They are a venture capital firm in Silicon Valley, a longtime supporter of this podcast and a longtime supporter of big, fantastic, world-changing ideas.

If you have such an idea, hit up E1 Ventures or send me a note and I'll put you in touch with E1 Ventures. It's uh it's quite a quite a deal for listening to this podcast. Um thank you again, as always, to U1 Ventures for their support. Do you spend a fair amount of time using AI and or digging into how they work?

Um let's see. So using AI, I mean yeah, we use AI routinely for things that, you know, uh I think it's good at. So um if we want to, you know, analyze something in terms of physical principles or equations. It's pretty good at mature sciences like physics. We can run, you know, hey, here's this material, what's it gonna do? And it can know it can look up coefficients and make calculations and so forth. When it comes to chemistry, which is a bit more nebulous, then

You know, I I I have asked AIs to help me design chemical reactions and so forth. And there I think now we're already in a much more nebulous space. I think humans might still have the upper hand for doing really creative chemistry for sure. That's what I was kinda curious about. Like And then in biology. Part of the problem with biology is that the literature has a lot of hidden hidden structure, a lot of w which is not even written down sometimes, right? Like maybe um

You know, a group bought this chemical from a company and the company went out of business five years later. And now, twenty-five years later, somebody wants to replicate that study, but you can't buy that chemical.

And, you know, that kind of thing won't be written down in the scientific literature. Um, who knows? Maybe somebody even bought the brand of the company, rebooted it, and they're selling something with the same name, but it's very different, right? And so I think the problem with biology is that there's a lot of unwritten metadata, so a lot of unwritten wisdom. You know, one group did it in, you know, their their lab had

the air condition air conditioning blasting and the temperature is a little bit lower, another group in maybe a a country where they have less air conditioning, you know, had it uh their room is at a higher temperature, maybe the reaction went differently. And but again, people don't write down The temperature of their room typically, right? Yeah. A scientific paper. Yeah. Chat GPT or Cloud open on your

Laptop on a day to day basis? I think I've been using uh just Google Gemini a lot because it's able to um I I I feel like it's very integrated with different Google search functions that are just familiar to how I think. Yeah. Uh And uh but MIT now does have a chat GPT subscription for faculty where it won't use the

the uh information to train the model and so I'm playing with that as well. Yeah, I guess I was curious because I I keep running across these twenty-year-olds when I'm reporting on stories and they are I feel like they're sitting with their laptop while I'm talking to them and they're just using it in ways that like I use.

AI, you know, a bit and and every day for some purpose. But I mean, they have like seven or eight AI apps open. They're like talking to their laptop. They it's just it's it's It reminds me of you were talking about the rise of the consumer internet, sort of like one era to the next and you're now you're just using your computer in a different way than the generation before and I don't know, I was trying to put myself in your shoes a bit because you're doing such high level science and um

Yeah. Yeah, I was I was kinda curious if you had adopted where I see sort of where I feel like this next generation is is going with this stuff. Yeah. Well one of my former students, Sam Rodriguez, he started a thing called Future House, another F R O. Now they are trying to build AI scientists. And um to

uh be able to, you know, analyze the literature and draw conclusions and make um design experiments and so forth and and other entities are also trying to design AI scientists of different kinds. So it is a very active area of research. But uh it seems like they have made great advances. But also is that there's a long way to go in terms of like really revolutionizing science, like a a drastically out of left field idea.

And maybe it's because just of the way that machine learning works that where they get a corpus of data and are trained on it and they're great at kind of interpolating and extrapolating, but But doing like really out of distribution predictions? And uh it seems like m n no current AI does that super, super, super well. Do you last AI question. I don't know what this is Do you You know, where do you fall on the um Going off what you just said.

There's tons of people. I live in Silicon Valley. If you talk to like Larry Page or you know people who are knowledgeable about this. Right in the thick of it, there's it's easy to find ones who would say those limitations you talk about in the next three years are blown away for sure. Superintelligence is is here. Um and then those same people usually are are

the most optimistic I find, um, about where this leads. Um, this doesn't strike me as something that's like consuming you as something you're thinking about, but Hm. Do you have a take on on where this is heading in the relatively near future?

Well it's certainly not my core expertise since I'm much more of a biologist, but um it does seem like people are trying to scale to larger and larger models, people are trying to tweak the architectures and build networks of agents of them and so forth and uh you know but

But again, it's not my my core expertise. I don't I haven't seen like a radically different architecture proposed. Actually, that's what got me thinking. Like maybe a little bit of brain data could go a long way, you know? And you know, if you take a a simple motif and then scale it up you know, with uh Google or OpenAI or whatever scale, um now it starts to exhibit interesting emergent behaviors. Well, what if we learn more about the brain and we could then try

To scale that up. Yeah, I know. This is why I wanted to ask you. I just feel like you have a better handle on the complexity of the body and the brain. Um And are are obviously clever enough to kinda compare that against what the L L Ms. As you mentioned, you just throw enough GPUs, maybe consciousness just arrives out of out of enough complexity from throwing enough.

compute at something and and connections and and um I don't know, I felt like you might have a intuitive sense as to to whether you believe something like that or not. I don't know, I tend to be very data driven. Like I would love to measure consciousness. I want to be able to model it. I I think I think we need to be very quantitative and detailed in our characterizations. Um

Okay. And if it's the history of other sciences, that's how it has been too, right? You know, centuries of astronomical data, and then Kepler made Kepler's laws. And then Newton came along and then, you know, distilled them further and made comparisons of things on Earth and so forth and then got Newton's laws, but um and people love to talk about how theory driven physics is, but It started with centuries of data.

Yeah. So if that's physics, how what hope do we have to do biology without lots of data? But and the right kind of data too. That's that's why this idea of ground truth, the fundamental building blocks and how they work together, I think has been such a driving force for our our research. I will note for listeners of the podcast, if they hear

Some noise. I think people are washing washing lab equipment above us. I think yeah, there is a dishwasher room overhead, I believe. Uh so if that's what you hear, it's just science. Taking place. Uh this relaxing waterfall sound here.

deeply into I know I remember when I was reporting on kernel in the early I think it was the first time I ever talked to you were an advisor, I think, to to Brian and they were trying to build a kind of external They started internal and then ended up in a external BCI. You also have you have a startup that's um or you're affiliated with a startup I talked to the other day that

In in the the bone matter of the skin. Inner cosmos? Right, right, right. Yeah, yeah. Right. And so that's not fully going into the brain, but it's it's sitting in this layer of the skull and and and it's for mental health. It's in m modulating I don't know. Yeah, yeah. Well the core idea is, you know, you can

have non invasive devices, but they're outside your scalp and that can be quite inconvenient. And then you can put wires in the brain, but that can also damage or displaced brain tissue. And so our idea was what if you you had a sort of a hybrid. You had a minimally invasive device, so it would never enter the brain or displace or damage brain tissue, but also wouldn't be sticking out, you know. And so you can imagine this sort of

You know, inside the skull, so to speak, implant, and then you can deliver electric fields. And yeah. So there is a a surgical team and uh an engineering team that is exploring. Uh topics like yeah, could you go after depression or other other conditions? Yeah. In this field you have so many different approaches. I mean

Neuralink is in some ways the most drastic, I guess, being the most invasive. Um, and then all the way up to things that are totally external. You've got things that are in blood vessels and yeah. I mean when you And this is this has moved pretty rapidly. You have the Utah array, which was the main tool of of for researchers doing this type of work for twenty, twenty-five years and and it was um an invasive device, but it was it's very hard to use. You have to be in a hospital or a research.

setting and then you know over these last twelve years All this venture capital money is poured into this. We have all these different approaches. There's a you know, each one has pros and cons. Um This must be kind of fascinating to you to see all this activity and then do you tend to favor one approach over the other. W I I was I'm curious what you make when you look at the BCI field. Well Since there's no ultimate theory of the brain, what matters most is data.

Um, our group has put out a couple inventions which are being used in in human patients or human subjects. So um optogenetics, where we borrow molecules from plants, put them into brain cells, the molecules convert light to electricity and then you can use light to control the brain. uh very widespread in use in animal neuroscience to study the brain, but a few summers ago uh a brave team in Europe did put one of our molecules into the human eye for blindness.

And they're now I think a couple dozen people walking around. I mean it's not approved by any regulatory body, but uh with at least a partial restoration of functional vision. So they lost it. Yeah. So uh blindness specifically or optogenetics in general? Let's let's explain optogenetics through the blindness example. Okay. All right.

Yeah, so um millions of people have lost the photoreceptors. These are cells in the eye that capture light and translate that into signals the brain can understand. So electrical signals. Um uh if somebody has this, then you know, there th there's not a whole lot you can do for most of the of the patients, unfortunately. So um

With optogenetics, we take molecules from single-celled algae, microbes, and so forth, and what these microbes have are proteins. And these proteins convert sunlight into electrical current. Like little solar panels, basically. And uh what we did uh with optogenetics is we took the gene that encodes for this protein.

put the gene into a brain cell, and now if you shine light on the brain cell, you can activate the brain cell too. Because that little solar panel converts your light from your LED or laser into electrical activity. So back to the eye. Um, the photoreceptor cells have died off, but the rest of the eye is still there, right? You could take the gene that encodes for one of these light-activated proteins.

put it in with, you know, gene therapy vectors, of which there are many, um including many that are already used in in people. Um The gene therapy vector will deliver the gene for light activated protein to one of the spared cells of the eye in the retina at the back. Those cells become white sensitive. They were not beforehand. And now you basically have, biologically speaking, installed a camera in your eye. So these people wear goggles that

take light from the world and project it onto the area of the eye that has the molecule. But they can recognize, you know, lines of a crosswalk or doors on a a hallway. They can see household objects. It's not perfect vision, but it's a pretty uh significant restoration of functional vision. Is this the stuff that Science Corporation, the the French company, they acquired, or it's different? Uh I don't know what the status is of it business wise. There is a French company called Gensite. Yeah.

the company that licensed this the molecule from us and we're they were the first to put these molecules into into people if uh if they got acquired. I don't know. I feel like it was called Prisma maybe or something. There may be multiple companies, yeah. So Gensite was the first And now there are a bunch of other ones that are going after different targets or using different molecules. But um uh there was a uh it was a French team that did uh December twenty twenty two?

was the first person who had uh these options put into the eye. Well and then in the B C I feel DCI field writ large, the all of this technology right now is being used for people who are suffering from usually quite dire conditions, whether it's blindness, ALS, paralysis, I keep getting both like excited about where all this is going and then and then sometimes a bit muted in that you almost want to see more. Um yeah. And so I guess this was part of my

When you're looking I don't know, y you could pick Neuralink if you want, but but um or or any like how like you know, okay. In terms of Really restoring somebody to um Something like an ALS patient being able to get their powers of speech back to where they could communicate like they could before they had their illness. How excited are you about the power of this technology?

by reading their activity out, even with um you know older technologies, but with enough machine learning to try to interpret it.

very interesting predictions of what spoken words the person was intending and so forth. So uh on the one hand I think um

At the phenomenological level, with enough data and machine learning, uh, it's quite possible to have a lot of restoration of of different kinds of functions. Um I think if we really want to understand like the the depths of cognition and emotion and and uh be able to build brain machine interfaces that have arbitrarily useful functions, then That's where the understanding of the brain um

would be wonderful to greatly increase. So that's one reason why we've although we spent, you know, the first decade of the group building lots of brain machine interfaces, we also sp um developed um a technology for non invasive focusing of electric fields into the brain, which also got spun out as a company.

Is it though? No. This is called uh temporal interference. Okay. And the company's in Azuric called TI solutions. Okay. Yeah. So basically brain cells are nonlinear low pass systems, which is a fancy way of saying they act like old fashioned AM radios.

And so if you deliver multiple high frequencies to the brain, the brain kind of ignores them the same way that, you know, broadcasting across the city, you know, the radio waves go right over your head, you won't even know they're happening, right? But where the different frequencies collide, what a nonlinear low pass filter does, what an old-fashioned AM radio does, is basically subtract off that high frequency carrier, and then you get the voice.

Um or whatever. In the case of the AM radio, in the case of neuroactivity we get whatever signal we want to deliver. But to make a long story short, basically it's a way of having multiple high frequency fields delivered to the outside of the brain, and then where they collide, you get information delivery. And so that's one technique that we built that uh is capable of non invasive but deep.

stimulation of the brain. So the point I want to make though is just that, yeah, there are these different tools How do we use them? You know, what are they best at? Uh right now, the only way to know is to try. There's no grand theory, so we must be empirical about it. But my hope is if we can make really good models of the brain, you can be like, wait a second.

This region and those re those two other regions are actually talking to each other this way we didn't know about. What if we stimulate the three regions with these three different patterns? Could we restore this function that can be quite complicated and and maybe we don't even understand it at all currently? But now because of the precision of our knowledge, we can dial in something that helps somebody and and r relieves their suffering. Yeah.

Well, I I feel like I keep trying to get you to rank things and and put dates and and predictions on stuff. I I I mean well I mean my my All the stuff that I cover, I usually feel like we're heading to some strange new world where where humans and machines really are merging in in some dramatic way. When I hear you talk, I I feel like my timeline in my head is Probably too quick. Um Well it depends. I mean, if you want to have like a general strategy for any kind of

brain augmentation. I think that's somewhat far off. But if you record from a specific region and your goals are very specific, you know, already several groups I've I've been marveling at the videos and so forth can read out neuroactivity and do things like generate language or control a computer cursor, right?

And and that seems to be like a very well posed problem. Now, does it work in the real world when, you know, the environment is rapidly changing? I mean, if you look at like even uh a different field like self driving cars where, you know, in the desert the DARPA Grand Challenge, you know, driving across the desert was solved a long time ago.

getting it to work in a busy city with, you know, kids and pets and so forth running around, you can argue that still is not completely solved, right? And and so Um, I think one of the the big questions for brain machine interfaces is what do they look like when they're put into the busy, complicated world? And you could argue that nobody's really um

put a uh you know, en masse a large set of people with brain machine interfaces out into the real world. At least not to my knowledge. And we have ability to read out data with optogenetics you can control the brain as far as inputting data. As far as I'm aware, I mean w the Not we're n we don't seem terribly far along on on something like that, putting information in. Well, I mean so optogenetics in the eye is in several dozen patients. Okay. So that's entering information into the eye.

I think if any of that gets approved, then people might start wondering about putting it to the brain. But I think a lot of people are kind of waiting to see what happens. Yeah. Um, because if a lot of people are doing the eye, um and the eye of course is much better understood than than the brain, um, let's see how it goes. But yeah, if we could you know imagine a holographic projector that would aim light in three D patterns.

and you can then make brain cells sensitive to light. And also you know enough neuroscience that if I stimulate these cells, I know it's gonna happen because remember the brain is this complex network. I can be locally stimulating

But still influencing things all over the brain, right? So it's important to be be able to predict that, I think. But that would be generating what a f like'cause I I'm I'm I'm sort of talking about putting almost like an idea, a thought in. Are you giv uh you describing more Like a reaction in the brain.

Well, that's why I brought up the idea of holographic projection. Okay. So if you built a very good holographic projector, um and so that uh one of our collaborators, Valentina Miliani in Paris, um was one of the key pioneers of this. Um you know, y uh h a hologram is basically a three D sculpture of light, right? So you should be able to give every cell its own

recipe, its own information, right? So if you do that with enough fidelity, you know, you should be able to enter arbitrarily complicated information into the brain, is my hypothesis. Um of course you'd have to build such a machine, but you know, optics is a is a field where, you know, with enough engineering, you know, one could imagine anything eventually coming within grasp.

And so, um yeah, could you enter an idea or a concept with a holographic projector and optogenetics? Maybe. Have you looked at the biohybrid stuff Max Hodak is doing? Uh tell me more. I don't know but He he co founded Neuralink and then went off. That's right Science Corporation and they have They used IPSCs to create lab made neurons that live in this kind of gel. Yeah, they cut a hole out of a skull. put the gel next to the the hole and and uh

the mi hu the human made neurons start to form axons and dendrites down into the actual brain. Yeah, very intriguing. Yeah. I mean what do you make of that? If you can get you know, consistent connections, if they're stable. Um, if you're not getting side effects where, you know, um, you know, neurons are getting wired up in the wrong way or, you know, then then it's intriguing. But yeah, it all it all boils down to the data, right?'Cause you don't have a theory of

Yeah. I just I know that you approach it with the stuff philosophically. Like what do you think humans and machines are like in thirty years? Yeah. Well, if we can really build good models of small things the next three to five years, like we were saying earlier, and now, in the same way that with earlier tools we spread it freely, so now everybody's modeling biology in this way.

Maybe we do understand the brain so deeply and I'm just gonna make this number up, but what if, you know, within ten to fifteen years we have good models of mammalian brains and maybe human brains? Um but if we understand what thoughts really are, if we understand what emotions really are, um maybe we could try to, you know, um uh augment them in certain ways. The the thing about augmentation is that

You really wanna know what you're doing, right? Because if you augment something and then but you've introduced a side effect that you know, causes something negative later, then that can be cause for regret. Right. So I think we want to find ways to to to deeply understand what we're doing to the brain if we're going to go beyond, you know, the the the most um uh pressing medical needs for sure.

But like in the thought um humans trying to keep up with AIs or merging with AIs or um evolving the species as this flesh computing hybrid are these things you think about, are these things you think should happen, are inevitable? Well I think at some point it's inevitable. The question is when? Uh is it now 50 years, 500 years, or some other time point? My guess is it probably will happen in decades. But here's the thing. I think we want to

You know, there's what the old Silicon Valley saying, move fast and break things. You might not want that if it's your brain, right? And so, um my hope is that if we can understand the brain rapidly enough, right, let's say models of small brains in three to five years, understand the human brain deeply in ten to fifteen, again, these are just made up numbers, but uh they're not entirely unreasonable.

Then you can imagine putting the field on a very firm foundation, right? Okay, here's what you want to do if you want to help somebody with this, but not mess up these other 17 things. And so I think if we could do it right, um there could be a lot of benefit of technologies that help us understand ourselves or improve ourselves in some way. Um

That said, uh if you look at the history of biotechnology and maybe neuroengineering in particular, when we don't understand something, you know, there often are side effects that result in something, you know, not working out well. I mean, there's so many examples, right? Like um I don't know, Merc BadeViox, the pain drug. It had side effects in a small percentage of people and they pulled it off the market, right? You know.

Um, you know, uh you know, in in I I do some work in the Alzheimer's field and there's lots of examples of Alzheimer's drugs where, you know, uh it's just it's been a long, hard slot, right? And if they have a side effect then You know, you have to take this drug for years, right? It's a chronic disease. You know, will people will people do that, right? So I think there's a lot of questions that are about um

Like will we really do it? Will it really work? Yeah. And so that I think it does make sense to put it on a well posed footing and make sure we really understand what we're doing. Yeah. Okay. The we You you and George Church and you I I both see you involved with lots of startups but then still

Heavily affiliated with your respective research institutions. Yeah, I'm always I'm always interested w how you make the decision of Staying at a place like MIT versus just going all in on a startup and and Chasing some giant idea full time, all the time. Sure. Everything. Yeah. Well, I feel every problem has a natural home.

Some things go well in academia where you have open collaboration and you can publish and you can look at certain time horizons. You know, your startup will have to have a shorter time horizon. You'll need much more focused, less serendipity perhaps. Um and then a couple of my group members developed this uh FRO focused research organization concept and Adam Marlestone and Adam Marlestone and Sam Rodriguez and and and so forth.

And and so maybe that also fills in a gap where you need something more scalable than academia, but not as profit making as a startup. So that's great. For me because I am just uh You know, the the risk in biology is so high, right? You can work for

A decade and you can spend billions of dollars and then your therapy can fail with a side effect that, you know, in some part of the body you've never thought about, right? And that happens all the time. And so the way I think about it is we need to remove the risk. from biology. I meant this idea earlier of this of the microchip moment, you know, this moment where, you know, after the microchip you you can be a dropout and start Apple, Facebook, and Microsoft, right? The risk of science.

that is represented by the microchip as far as physics goes, is a huge reduction of science risk, right? And in biology, can we get to that microchip moment? Can we get to the point where, you know, a college dropout could start, you know, a company that cures a disease. We're not there yet, to my knowledge, but but um my hope is that if we can make simulations of living things

And how any kid in high school or college can m you know use a simulation to try to go after a problem. You know, maybe that is what causes the true democratization of biology. You have this reputation, your lab has this reputation for people having quite a bit of um intellectual freedom, um, the ability to pursue their curiosity, not terribly um

Sort of rigid and self serving to your particular interests. Like is this a was this a conscious decision that you made when you started this? Is it just just a reflection of your personality. I didn't know if you had some management genius wisdom to to pass down. I mean the things we're doing in the lab are things I'm interested in. I guess uh I feel that my role

You know, it's not just to let people do random things, but neither to micromanage. I'm here to persuade. Look, okay, here's this idea. If it's great, let's talk about it. Let's deconstruct it. You know, is it gonna solve the problem? Is there a path we can realize? And so it's more of a process than a rigid set of rules. But if we have an idea, whether it's from me or from a student or you know, so forth, and we can uh

show to ourselves that it is likely to work. We show to ourselves that it will give us what we want in terms of solving the problem. You know, um and there are some heuristics that I like. I love to build technology that's very inexpensive to use. So both optogenetics and expansion microscopy, anybody can do it. Um, because I really do believe in democratizing science. Um

You know, uh then we can do it. So um and in fact I'm starting to write a blog where I want to talk more about like our problem solving methods. Um and so we posted a couple of articles about um how to generate ideas or how do you um you know think about uh what to learn in order to solve a problem and so forth. And um

Uh so I I would like to just write down a lot of our problem-solving methods and get them out there. Um But I think if we apply those methods, Then it's very easy for a group member and myself to be aligned, because we will converge upon something that ideally is extremely impactful, uh, but also is very powerful.

W i this is a big question, I guess. W uh like what do you make of the state of US science at this particular moment in time with all kinds of interesting political and and um sort of nation-state level competitive things going on. Yeah, yeah. No, I mean science is being very disrupted with um, you know, mass cancellations and reductions in national institutes of health, national science foundation, and so forth.

Um priorities. Yeah, I do think it uh has a real risk. Uh the real risk has already happened of hurting national competitiveness in science. Um I've had people, you know, uh in the group who've gone to other countries or um you know been unable to continue on. You know, funding of course is always an issue. Um yeah, it is quite quite worrisome. Um and especially

at this moment where it felt like we were poised to you know, like with advances in AI like we said earlier, with advances in ground truthing at biology, you know, it felt like many fields are poised to really go to the next level. So in terms of timing as well as Um you know, both the the state of funding as well as the sort of the the general freedom of of people to be and do things. It's uh it does seem like uh quite a quite a disruptive state. Where do the students tend to go?

Well, let's see. Well, my group, like many, uh is very international. Um and so um Yeah, I mean many people uh uh you know, uh if if they have a visa issue or something will try to go to uh their home country or other countries and so forth. Um but uh it's pretty chaotic to be honest. I don't know if there's like a uh and all all we can do is try to support our our our group and and help help people, you know, just as people. Um but one of my hopes is well

Is there maybe a new model that emerges of international labs working together? Um I don't know. I didn't really prepare a detailed thought on that topic, but um thinking a lot more about like You know, in in uh an earlier time of crisis, right, with like the Cold War and mathematicians and physicists started talking across, you know, lines of political distance and you know, maybe that helped. Yeah, with with some

Greasing of the wheels and communication so forth. Is you know, would there be the pendulum swinging the other way? And now maybe there will be more international collaboration than science. Um I don't know. I don't know. Right, because it well, I mean It would be nice if like the Ch China and the US could collaborate on

all these fields and push the world forward together. That doesn't seem to be the way things are trending. I guess this is one reason also I wanted to start writing this blog and writing more for the public and so forth, which is It seems that, you know, of course, if somebody has Alzheimer's disease or terminal cancer or something like that, uh th the disease does not care what nation you're from or what political party you are. It's just gonna try to kill you. And so

You know, uh is there a common enemy here? You know, can is there a way to to tell a story in a way that motivates us to go after, you know, the things that are, you know, causing so much suffering? Yeah. And I feel like that story You know, may maybe there maybe if if fresh voices can can tackle it, maybe there's a way of telling that story that makes people realize, wow, you know, there's a lot of suffering here that we are just

you know, giving up the ground on you were s you've had this prolific career and y you started so young chasing big ideas. Is it harder as you get older to find the big ideas? Well, I mean I feel like the big idea that I had was sort of near the beginning, which is the idea of c could we convert biology into physics? Could we solve the ground truth? Um and the the basic thinking from day one was if you could understand a complex biological system in terms of its parts and how they work together

That is the answer. You know, you should be able to see all the parts, control them, and make a model of them. And um my very first biology experience when I was still an undergrad here, uh, was trying to make a little, you know, model of a a circuit in the songbird brain.

You know, how does the the songbird clock out the syllables of a song? And I made a model that kind of explained the data, but how can you test it, right? And so that motivated me to go down this direction of building tools, of really getting into the the molecular, you know, nitty-gritty, I guess, of it. But um uh and then I don't know, it seems like often the idea that solves the problem almost has this sort of feeling of inevitability about it.

Um but sometimes we have to go through what I call constructive failure to get there. I'll give you an example. So um we had the idea, the first idea for expansion in 2007, a long time ago. But we didn't know that it was an important idea at the time. And then in 2012, 2011, 2012 or so, you know, two uh fantastic grad students in the group were trying to do nanoimaging with super-resolution microscopy. And uh we built our o and also electrodecroscopy, you know, classical technique.

And it was hard, you know? And then even if it did work, it's it's slow and expensive. How would you ever scan a whole brain? And that's when we kinda learned a secret about the field, which is wow, nanoimaging is really hard if you want to image anything that's like a big biological structure. And so then we mothballed those projects and started doing expansion. Um so I think in some ways

It's almost like, you know, a a proselynation. Let's carve away what was it? Michael Michelangelo's like carve away all the parts of the marble and the sculpture is simply what's left behind. you know, uh very often we'll fail as we try things and then as we eliminate the different possibilities, there's kind of a nucleus defined by the failure of us in some ways, but in a constructive way to tell us what to do.

When you like whenever you talk about these models and simulating things, I I just makes me think I don't know. You are you one of these people that thinks we live in a simulation? It's a good question. I'm not sure. I mean the laws of physics and the laws of science are very intriguingly concise and there's so many interesting coincidences. You know, like if this parameter was a little bit bigger, a little bit smaller, then the universe would be totally unrecognizable.

Um that said, uh I guess again I'm very data driven. I would love just to analyze reality until we have some clue about what it what it is, but I don't feel like I have a strong opinion about whether, you know, It is one extreme of, you know, total you know, uh atheistic nature of ki total chaos versus a contrived simulation or something in between and

I don't know. I feel like I'm very data driven. I would like to if confront some evidence that some one or more of these possibilities is the case. But I don't feel a strong belief or opinion. You said hm, like you hadn't thought about that before, but I'm sure Uh well I have wondered about it a bit.

how much structure the universe has, right? Like it's kinda weird if you think about it that, you know, the laws of physics, there's only a couple of them, right? You know, there's and then there's only a couple of things, like electrons

protons, neutrons, that's it, right? And then a couple forces. And then if you're big enough, then you wear gravity. But for most things, you know, you can kind of neglect gravity for many chemical and and physical things. But then if you if you do the equations, you have to the periodic table of the elements, right? Now you got carbon and nitrogen and all that. And then take carbon. Carbon is this interesting atom. Forms these long chains. You can get DNA, you can get proteins.

No other atom seems to do that, right? Silicon is right under carbon. Uh silicon doesn't do those things. You know, is there silicon life somewhere in the universe? So anyway, there are all these interesting coincidences there. Is it evidence for simulation? Is it evidence for religion? Is it evidence of just you know, some people call it the anthropic principle that there's lots of chaos and we just happen to be here and we notice it'cause it's the only universe where we

uh can exist to notice things. But um uh yeah, I don't know. I would love to to see if we can discover evidence uh for one or another. And

I have a sneaking suspicion that this is why investigating consciousness is so interesting, right? We don't have any measurement device or theory which helps us understand why this. Bit of matter feels its feelings, has subjective experiences, and this other bit of matter, presumably, of course, we can't prove it.

does not. And yet it's so essential to everything, right? If you have a robot vacuum cleaner, nobody thinks twice about throwing it into the trash or recycling it when it breaks, but you know, you know, with beings uh with subjective experiences you know, pets and humans and so forth deserve justice and also are held accountable. And so uh it's very important even uh even though we don't have a scientific grass over it. Yeah, yeah. Um well

I got to ask most of my big questions that I wanted to ask you and I'm just being cognizant of of time. Um it was just a absolute treat to actually get to

Sit with you for a bit and chat. Thank you so much. Yeah, let's stay in touch. The next couple of years are gonna be hopefully Really exciting. Yeah, I mean is there it I you went over so many things and you talked about your research but but um is there a particular thing we should keep our eye on that you're you're excited about that you're working on at at the moment?

Well, I'm very intrigued by this idea that you could map all the building blocks of life to the point where you could simulate it. I think that would be a real game changer. Yeah. And Just in the last year, um some papers have been coming out from us and collaborators and others which suggest that. you might be able to map the dilemma box of life. So that's that's very, very intriguing. And if we can do that, this idea of converting biology into

You know, basically physics with computer science run computer science running on top of it. Yeah. Yeah, absolutely. And we like what happens in these I was just walking down the hallways. I mean, th this is is this where you do Y you would work on a day to day basis? Yeah, yeah, yeah. Our group has much of the second floor of the McGovern wing of this building. Okay. And um yeah, here we do things like expand brains. We build microscopes to scan things.

We work on optogenetic molecules and are building optics to Do the holography that I mentioned earlier. Okay. So just pushing all those different fronts for it all the time. Yeah. I think of the is three layers of a tri of a tripod, right? What an image lots of things. Returb lots of things and then make a map of the structure of the things and then integrate that to a model. Okay. So most of the products in the lab are are

directly on the lines of one of those three things or opportunistically related to one. Okay. Okay. Well th and thank you so much. We really appreciate it. Great. So a lot of fun time. Ashley Vance and or Kylie Robison or Yeah. Thank you. Subscribe. Thank you