YouSaid · the spoken record

Adam Marblestone

lines on the record: 144
first: 2025-12-30
most recent: 2025-12-30
sittings or episodes: 1
sources: podcast

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“That's not exactly the same as having the synaptic weights. That's not exactly the same as being able to simulate the neurons and say, was the functional consequence of having these molecules and connections. But you can also do some amount of activity mapping and try to correlate structure to function. Yeah”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“So you can give different definitions. And one of the things that's cool about So, the kind of standard approach to konicomics uses the electron microscope and very, very thin slices of brain tissue. And it's basically labeling the cell membranes are going to show up, scatter electrons a lot, and everything else is going to scatter electrons less. But you don't see a lot of details of the molecules, which types of synapses, different synapses have different molecular combinations and properties. E11 and some other research in the field has switched to an optical microscope paradigm with optical. The photons don't damage the tissue, so you can kind of wash it and look at fragile gentle molecules. So with E11 approach, you can get a quote-unquote molecularly annotated connectome. So that's not just who is connected to who by some kind of synapse, but what are the molecules that are present at the synapse, what type of cell is that? So molecularly annotated connectome.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Sort of the suite of efforts in the field also are trying to get a single mouse connectum down to low tens of millions of dollars. Okay, so that's a mammal brain, right? Now a human brain is about a thousand times bigger. So if a mouse brain, you can get to 10 million or 20 million, 30 million with technology, if you just naively scale that, okay, human brain is now still billions of dollars to just do one human brain. Can you go beyond that? Can you get a human brain for like less than a billion? But I'm not sure you need every neuron in a human brain. I think we want to, for example, do an entire mouse brain and a human steering subsystem and the entire brains of several different mammals with different social instincts. And so I think that that with a bunch of technology push and a bunch of concerted effort can be done in the really significant progress if it's focused effort can be done in the kind of hundreds of millions to low billions.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, so if I just talk about some of the specific things we have going with connectomics. So E11 bio is kind of like our main thing on connectomics They are basically trying to make the technology of connectomic brain mapping. Several orders of magnitude cheaper. So the welcome trust put out a report a year or two ago that basically said to get one mouse brain, the first mouse brain connectome would be like several billion dollars, billions of dollars project. E11 technology.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Sort of weird. So, yeah. So I don't have a super strong opinion on it. So I think there's a possibility that essentially all other scientific research that is being done is somehow obviated, but I don't put a huge amount of probability on that. I think my timelines might be more in the like, yeah, 10-year-ish range. And if that's the case, I mean, I think there is probably a difference of puno world where we have connectomes on hard drives and we have understanding of steering subsystem architecture. We've compared that even the most basic properties of what are the reward functions, cost function, architecture, et cetera, of mouse versus a shrew versus a small primate, et cetera. This is practical.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“I think part of it is just it is weirdly different than all this brain stuff And so intuitively, it's just weirdly different than all this brain stuff. And I'm kind of waiting for the thing that starts to look more like brain. Like, I think if AlphaZero and model-based RL and all of these other things that were being worked on 10 years ago had been giving us the GPT-5 type capabilities, then I would be like, oh, wow, we're both in the right paradigm and seeing the results. So, my model, my prior and my data are agreeing. Right. And now is like, I don't know what. Exactly, my data is. Looks pretty good, but my prior is.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“What are mine? Know, I'm just watching your podcast. I'm trying to understand the distribution. I don't have a super strong claim that LOMs can't do it.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, I would take the entirety of your collective podcast with everyone as showing the distribution of these things, right? I don't know, right? I mean, what was Carpathy's timeline, right? What's Demesis' timeline? So not everybody has a three-year timeline. And so I think if you...”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Relevant. I think it's fair to say it's not super practical and relevant if you're in like an AI 2077 scenario And so, like, what science I'm doing now is not going to affect the science of 10 years from now because what's going to affect the science of 10 years from now is the outcome of this AI 2027 scenario, right? It kind of doesn't matter that much probably if I have the connectome, maybe it slightly tweaks certain things. But I think there's a lot of. Reason to think maybe that we will get a lot out of this paradigm. But then the real thing, the thing that is like the single event that is transformative for the entire future or something type event is still like. More than five years away, or something. Is that because?”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“You can't do interp on a hypothetical model based reinforcement algorithm like the brain that we will eventually converge to when we do AGI. Fair fair.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“The most basic things we don't know. And the problem is learning even the most basic things by a series of bespoke experiments takes an incredibly long time. Whereas just learning all that at once by getting a connectome is just like way more efficient.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“We have some repertoire of possible ideas about this, can we just think of the connectome as a huge number of additional constraints that will help to refine, to ultimately have a consistent picture of that? I think about this for the steering subsystem stuff too, just very basic things about it. How many different types of dopamine signal or of steering subsystem signal or thought assessor or so on? How many different types of what broad categories are there? Like even this very basic information that there's more cell types in the hypothalamus than there are in the cortex, that's new information, right? About how much structure is built there versus somewhere else. Yeah, how many different dopamine neurons are there? Is the wiring between prefrontal and auditory the same as the wiring between prefrontal and visual? It's like...”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“But then on the other hand, you can say, well, what if we can actually apply some ideas from AI? We basically need to figure out, is it an energy-based model or is it an amortized VAE type model? Is it doing backprop or is it doing something else? Are the learning rules local or global?”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“I guess there are a couple of different views of it. So it depends on these different parts of this portfolio. So on the totally bottom up, we have to simulate everything portfolio. It kind of just doesn't. You have to just see what are the, you have to make a simulation of the zebrafish brain or something. And then you see what are the emergent dynamics in this and you come up with new names and new concepts and all that. That's like the most extreme. Bottom up neuroscience view. But even there, the connectome is really important for doing that biophysical or bottom-up simulation.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, caught recording and Tim Lillycrap have this paper from a while ago, maybe five years ago, called, What does it mean to understand a neural network or what would it mean to understand a neural network? And what they say is, yeah, basically that. Like you can imagine you train a neural network to compute the digits of pi or something with some crazy, you know, it's like this crazy pattern. And then you also train that thing to like predict the most complicated thing you find, predict stock prices, basically predict the really complex systems, right? Computationally complete systems, I could train a neural network to do cellular automata or whatever crazy thing. It's like, we're never going to be able to fully capture that with interpretability, I think. It's just going to just be doing really complicated computations internally. But we can still say that the way it got that way is that it had an architecture and we gave it this training data and it had this loss function. And so I want to describe the brain in the same way. And I think that this framework that I've been kind of laying out is like we need to understand the cortex and how”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Because we built them. Not because we interpreted them from seeing the waves. We built I think we should do is we should describe the brain more in that language of things like architectures, learning rules, initializations, rather than trying to find the Golden Gate Bridge circuit and saying exactly how does this neuron actually, you know, that's going to be some incredibly complicated learned pattern.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I would somewhat disputed it. I think we have some architectural, we have some description of what the LLM is like fundamentally doing. And what that's doing is that I have an architecture and I have a learning role and I have hyperparameters and I have initialization and I have training data.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“I think I both think that there should be a part of the research portfolio that is totally bottom up and not trying to apply our vocabulary that we learn from AI onto these systems and that there should be another big part of this that's kind of trying to reverse engineer it using that vocabulary or variance of that vocabulary and that we should just be pursuing both. And my guess is that the reverse engineering one is actually going to like. Kind of work ish or something. Like, we do see things like TD learning, which, you know, Sutton also invented. Separately, right”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“You know, I don't know. I think that there's a case to be made for that. And from a kind of research program design perspective, I think there's like one thing we should be trying to do is just simulate a tiny worm or a tiny zebrafish from almost like as biophysical or like as bottom up as possible get connecto molecules activity and like just study it as a physical dynamical system and like look what it does But I don't know. I mean, just when I like it just feels like The AI is really good fodder for computational neuroscience. Like, those might actually be pretty good models. We should look at that. So I'm not a person who thinks that.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“So, like Yuri Buzaki as a neuroscientist who has a book called The Brain from Inside Out, where he basically says, all our psychology concepts, like AI concepts, all this stuff is just like made up stuff. We actually have to do is figure out what is the actual set of primitives that the brain actually uses and our vocabulary is not going to be adequate to that. We have to start with the brain and make new vocabulary rather than saying backprop and then try to apply that to the brain or something like that. You know, he studies a lot of like oscillations and stuff in the brain as opposed to individual neurons and what they do.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Even like pre trained on like cat pictures and stuff, CNNs, what is the representational similarity that they have on some arbitrary other image versus compared to the brain activations measured in different ways? Jim DeCarlo's lab has this brain score. And the AI model is actually like there seems to be some relevance there in terms of like even like neurosciences don't necessarily have something better than that. So yes, I mean, that's just kind of recapitulating what you're saying is that like the best computational neuroscience theories we have seem to have been like invented largely as a result of AI models. And find things that work. And so find backprop works and then say, can we approximate backprop with cortical circuits or something? And there's kind of been things like that. Now, some people totally disagree with this, right?”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“There may be. I think the reason that we might be onto something is that like. The AIs we're making based on these ideas are working surprisingly well. There's also a bunch of just empirical stuff like convolutional neural nets and variants of convolutional neural nets. I'm not sure what the absolute latest, latest, but compared to other models in computational neuroscience of like what the visual system is doing are just more predictive, right? So you can just like score.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Curiosity interest in others in social interactions, curiosity. Yeah, but that's pretty minimal, I think. And that's true for humans, but it might be less true for something that's already pre-trained as an LLM or something. And so most of why we want to know the steering subsystem, I think, if I'm channeling Steve, is alignment reasons.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah. And so I think that it probably is possible to make super powerful model-based RL optimizing systems and stuff like that that don't have most of what we have in the human brain reward functions. And as a consequence, might want to maximize paperclips, and that's a concern.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“If I channel Steve Burns more, I mean, I think he's very concerned that the sort of minimum viable things in the steering subsystem that you need to get something smart. Is way less than the minimum viable set of things you need for it to have human social instincts and ethics and stuff like that. So a lot of what you want to know about the steering subsystem is actually the specifics of how you do alignment essentially or what human behavior in social instincts is versus just what you need for capabilities. We talked about it in a slightly different way because we were sort of saying, well, in order for humans to like learn socially, they need to make eye contact and learn from others. But we already know from LLMs, right, that depending on your starting point, you can learn language without that stuff, right? And so”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, I think one way of this question is, is it actually possible to make the paperclip maximizer or whatever, right? If you try to make the paperclip maximizer, does that end up just not being smart or something like that? Because it was just the only reward function it had was make paperclips.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“And there are some cells in the cerebellum where it seems like the cell body is playing a role in storing that time constant, changing that time constant of delay versus that all being somehow done with like, I'm going to make a longer ring of synapses to make that delay longer. It's like, no, the cell body will just like store that time delay for you. So, there are some examples, but I'm not a believer out of the box and like. Essentially, this theory that's happening changes and connections between neurons. And that's like the main algorithmic thing that's going on. I think that's a very good reason to still believe that it's that rather than some crazy cellular stuff. Yeah.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“There are some things that cells do, I think, that seem like more convincing. So in the cerebellum, so one of the things the cerebellum has to do is predict over time, like predict what is the time delay. Let's say that I see a flash and then some member milliseconds later, I'm going to get like a puff of air in my eye later or something, right? The cerebellum can be very good at predicting what's the timing between the flash and the air puff so that now your eye will just like close automatically like the cerebellum is like involved in that type of reflex, like learned reflex.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“You know, you just had a lot of plasticity, and like you're part of this memory, and now that's got consolidated into the cortex or whatever. And now we want to reuse you as like a new one that can learn again. It's going to be a ton of cellular changes. So there's going to be tons of stuff happening in the cell, but algorithmically, it's not really adding something beyond these algorithms, right? It's just implementing something that in a digital computer is very easy for us to go and just find the weights and change them. is a cell it just literally has to do all this with molecular machines itself without any central controller right it's kind of incredible”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I don't know, but I'm not a believer in the radical, oh, actually, memory is not synapses mostly or like learning is mostly genetic changes or something like that. Think it would just make a lot of sense. I think you put it really well for it to be more like the second thing you said. Like, let's say you want to do weight normalization across all the weights coming out of your neuron into your neuron. Well, you probably have to somehow tell the nucleus about this of the cell and then have that kind of send everything back out to the synapses or something, right? And so there's going to be a lot of cellular changes, right? Or let's say that.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“And Beth Jazos and whatever. They're like, no. That is actually one read of being granted. I haven't really worked on AI at all since LLMs took off. So I'm just like out of the loop. But I'm surprised and I think it's amazing how the scaling is working and everything. But yeah, I think Jan Lacun and Beth Jezos are kind of onto something about the probabilistic models, or at least possibly. And in fact, that's what.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“It's not just amortizing everything that the neurons are also very natural for that because they're naturally stochastic. And so you don't have to do a random number generator and a bunch of Python code. Generates samples and it can tune what the different probabilities are. And so Learn those tunings. And so it could be that it's very co designed with some kind of inference method or something.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“In Python or whatever, and load that up and copy that in principle, right? So the fact that it can't be copied in kind of random accessed is very annoying. But otherwise, maybe these are has a lot of advantages. It also tells you that you want to somehow do the co-design of the algorithm and maybe it even doesn't change it that much from all of what we discussed, but you want to somehow do this co-design. Yeah, how do you do it with really slow voltage switches? That's going to be really important for the energy consumption. The co-locating memory and compute. So I think that probably just hardware companies will try to co-locate memory and compute. They will try to use lower voltages, allow some stochastic stuff. There are some people that think that this like all this probabilistic stuff that we were talking about, oh, oh, is actually energy-based models and so on is doing lots. It is doing lots of sampling.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, I think in the end we will get the best of both worlds somehow. I think an obvious downside of the brain is it cannot be copied. You don't have. External read, write access to every neuron and synapse, whereas you do, I can just edit something in the weight matrix.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“So there's maybe this group selection or whatever of these things is like more model free But now I think culture. Stores some of the model. Yeah. Right.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“And so, what does that tell you? Maybe the simple algorithms can just get you anything if you do it enough first. Yeah, I don't know.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Evolution is the simplest algorithm in some sense, right? And if we believe that all of this can come from evolution, like the outer loop can be extremely not foresighted. And yeah.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Plan sampling from plans that could lead to that. And so if you have this very general cortical thing, it can just do, if you have this general, very general model-based system and the model, among other things includes plans and rewards. Then you just get it for free, basically.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“So there's that. And then there's maybe like higher order stuff. So we have these cortex making this world model. Well, one of the things the cortex world model can contain is a model of when you do and don't get rewards, right? Again, it's predicting what the steering subsystem will do. It could be predicting what the basal ganglia will do. And so you have a model in your cortex that has more generalization and more concepts and all this stuff that says, okay, these types of plants, these types of actions will lead in these types of circumstances to reward. So I have a model of my reward. Some people also think that you can go the other way. And so this is part of the inference picture. There's this idea of RL as inference. You could say, well, conditional on my having a high reward, sample a plan that I would have had to get there. That's inference of the plan part from the reward part. I'm clamping the reward as high and inferring.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Layer one thing on top of that is that some of the major work in neuroscience like Peter Diane's work and a bunch of work that is part of why I think DeepMind did the temporal difference learning stuff in the first place is they were very interested in neuroscience. And there's a lot of neuroscience evidence that the dopamine is giving this reward prediction error signal rather than just reward yes no gazillion time steps in the future. It's a prediction error. And that's consistent with learning these value functions.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I think there are some parts of the brain that are thought to do something that's very much like model free RL, that sort of parts of the basal ganglia sort of striatum and basal ganglia. They have a certain finite, it is thought that they have a certain finite relatively small action space and the types of actions they could take, first of all, might be like tell the spinal cord or tell the brainstem and spinal cord to do this motor action, yes, no. Or it might be more complicated cognitive type actions like tell the thalamus to allow this part of the cortex to talk to this other part or release the memory that's in the hippocampus and start a new one or something, right? But there's some finite set of actions that kind of come out of the basal ganglia and that it's just a very simple RL. So there are probably parts of other brains in our brain that are just like doing very”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Learning basically means you have some kind of a value function of like what action I choose now doesn't just tell me literally what happens immediately after this. It tells me what is the long run consequence of that for my expected total reward or something like that. And so you would have value functions like the fact that we don't have value functions at all is in the LLMs is like, it's crazy. I think because Ilya said it, I can say it. I know one one hundredth of what he does about AI, but it's kind of crazy that this is working. In terms of the brain.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, this is another one of these things. I mean, again, all my answers to these questions, any specific thing I say, it's all just kind of like directionally we can kind of explore around this. I find this interesting. Maybe I feel like the literature points in these directions in some very broad way. What I actually want to do is go and map the entire mouse brain and figure this out comprehensively and make neuroscience the ground truth science. So I don't know, basically. But yeah, I mean, so first of all, I mean, I think with Ilya on the podcast, I mean, he was like, it's weird that you don't use value functions, right? You use the most dumbest form of RL basically. And of course, these people are incredibly smart and they're optimizing for how to do it on GPUs. And it's really incredible what they're achieving. But conceptually, it's a really dumb form of RL, even compared to what was being done in 10 years ago, right? You know, the Atari game playing stuff, right, was using Q learning, which is basically like, it's a kind of temporal difference learning, right? And the temporal difference.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, there's all this stuff I feel like it's come up in your shows before, actually, but even like the design of the human eye where you have the pupil and the white and everything, like we are designed to be able to establish relationships based on joint eye contact. And maybe this came up in the sudden episode, I can't remember. But yeah, we have to bootstrap to the point where we can detect eye contact and where we can communicate by language, right? And that's like what the first couple years of life are trying to do.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“But even a fly brain has like associative learning centers that actually do things that maybe look a little bit like this like thought assessor concept from Barrens where there's like a specific dopamine signal to train specific subgroups of neurons in the fly mushroom body to associate different sensory information with am I going to get food now or am I going to get hurt now?”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, you have some amount of learning going back all the way to anything that has a brain, basically. You have something kind of like primitive reinforcement learning at least going back at least to like vertebrates, like imagine like a zebrafish as like a These kind of other branches, birds maybe kind of reinvented something kind of cortex like, but it doesn't have the six layers. But they have something a little bit cortex-like. So some of those things after reptiles in some sense birds and mammals both kind of made us up somewhat cortex-like but differently organized thing.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“And so I'm not saying there aren't something special about humans in the architecture of the learning subsystem at all. But yeah, I mean, I think it's pretty widely thought that this is expanded, but then the question is, okay, well, how does that fit in also with the steering subsystem changes and the instincts that make use of this and allow you to bootstrap using this effectively? But I mean, just to say a few other things. I mean, so even the fly brain has some amount of, for example, even very far back, I mean, I think you've read this great book, The Brief History of Intelligence, right? I think this is a really good book. Lots of AI researchers think this is a really good book, it seems like.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Maybe, maybe. I'm not super deep on this. There may have been. Yeah, changes in architecture, changes in the folding, changes in neuron properties and stuff that somehow slightly tweak this. But there's still ascaling. That's right. Either way, right?”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“I'm not sure that there's agreement about that. I think there might be specific questions about language. Are there tweaks to be able, whether that's through auditory and memory, some combination auditory memory regions? There may also be macro wiring of you need to wire auditory regions into memory regions or something like that. But yeah, I mean, I think that. Is it that something changed about the cortex and it became possible to do these things? Whereas that was that potential was already there where there wasn't the incentive to expand that capability and then use it wired it to these social instincts and use it more. I mean, I would lean somewhat toward the latter. I mean, I think a mouse. Has a lot of similarity in terms of Cortex as a human right.”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source
“Incentive to have a bigger cortex which can learn these things. And that can be done with a relatively few genes because it's really replicating what the mouse already has. It's making more of it. It's maybe not exactly the same. And there may be tweaks, but it's like from a perspective, you don't have to reinvent. All this stuff, right?”
2025-12-30 · Dwarkesh Podcast · Adam Marblestone — AI is missing something fundamental about the brain · IDENTIFIED FROM THE TRANSCRIPT · source