← All transcripts

From Restoring Sight to Reimagining the Brain, with Max Hodak Transcript, AI Summary & Key Points

No Priors: AI, Machine Learning, Tech, & Startups · 3 hours ago · Science & Technology · 31:39 · EN

🧠 AI Summary

Science is a medical device company focused on using an engineering-oriented understanding of the brain to improve the human condition. Its Prima retinal prosthesis uses a chip implanted under the retina and glasses containing a laser projector to bypass dead rods and cones and send visual signals to the brain. Prima received marketing approval in Europe in July, with first sales expected in the coming weeks. Clinical-trial patients were able to fill in Sudoku and crossword puzzles and read books, although the current device has a small field of view and produces only black-and-white vision. Science is also pursuing biohybrid neural interfaces and a perfusion program called Vessel. Max Hodak argues that the brain can be understood as a computer and that neural devices could eventually restore sensory and motor capabilities, improve healthspan, reduce human fragility, and support substrate independence. He also discusses the relationship between biological brains and AI models, including the controversial platonic representation hypothesis.

🔑 Key Points

  • Science is fundamentally a medical device company whose mission is to use a differentiated understanding of the universe to improve the human condition.
  • Prima is a retinal prosthesis that Hodak compares to a cochlear implant for the eye.
  • Prima places a tiny chip under the retina for patients who have gone blind because of the loss of light-sensitive cells, including patients with macular degeneration.
  • Glasses with a laser projector send an image to the implant, which stimulates the retina directly and bypasses dead rods and cones.
  • Science explored retinal gene therapy, electrical stimulation, and ultrasound before selecting an electrical retinal stimulation technology developed by Pixium.
  • Science acquired Pixium after identifying its retinal-prosthesis work as the state of the art, and spent about two years after the acquisition preparing Prima for regulatory approval.
  • Prima received marketing approval in Europe in July, making it commercially available there; first sales were expected in the coming weeks.
  • The clinical trial provided an existence proof for restoring form vision: patients filled in Sudoku and crossword puzzles, and some patients read books.
  • The current Prima device has a small field of view, described as like looking through a straw, and produces only black-and-white vision.
  • Science believes it can improve the retinal prosthesis by adding grayscale depth and potentially red and green color; blue is more difficult.
  • Science's pipeline has three elements: vision, biohybrid neural interfaces, and a perfusion program called Vessel.
  • Science's biohybrid neural-interface approach involves engrafting living neurons that grow in and form new biological connections instead of placing metal wires in the brain or genetically modifying the brain.
  • Hodak believes the three pipeline areas could drive a significant revolution in medicine if successful on a 10-to-15-year timescale.
  • Hodak argues that treating the brain as a computer can make some medical interventions more tractable than drug discovery, citing cochlear implants, deep-brain stimulation, motor-cortex implants, and the retinal prosthesis.
  • Hodak considers a retinal prosthesis to be a possible form of brain-computer interface, broadening the category beyond motor decoding.
  • Hodak distinguishes between BCI products that substitute for communication or hand functions and products that generate vision, hearing, balance, or motor control.
  • Hodak identifies a possible boundary between communicating with an external device and redrawing the border around the brain, but says its location is not yet clear.
  • Hodak considers continuity important to personal identity and views a non-continuous software simulation as less satisfying than a continuously changing identity.
  • Connectomics is described as a major missing piece for understanding consciousness and substrate independence; a mouse connectome would be enormously useful, while a human connectome remains relatively distant.
  • The platonic representation hypothesis proposes that AI-model representations and neural representations may share underlying structure; Hodak says Science has obtained alignments between animal-brain neural recordings and AI-model internal representations.
  • Hodak says working on AI may be one of the most fertile ways to study neuroscience because it is easier to study neuroscience on models.
  • Science considers becoming profitable, or at least able to continue indefinitely, a high priority.
  • Hodak says the current Prima market is on the scale of hundreds of thousands of patients in the United States and Europe, while a next version now entering animal studies could expand the market to millions.
  • Hodak's long-term goal is to reduce the fragility and jeopardy of the human condition by repairing, replacing, and upgrading parts of humans.
  • Hodak describes preserving and adapting the self as the same long-term project of achieving substrate independence.
  • Science is focused on generating vision and hearing and achieving substrate independence rather than building a brain keyboard.
  • Hodak describes a roughly 10-bit-per-second cognitive bottleneck supported by several lines of evidence, including asking a person with a perfect memory to draw Manhattan from a helicopter.

✅ Actionable items

  • Study the brain as a computational system when designing interventions for sensory and motor impairments.
  • Evaluate neural interfaces across specific medical conditions and hypotheses rather than treating BCI as a single undifferentiated investment or research category.
  • Use alignments between animal-brain neural recordings and AI-model internal representations as a way to investigate shared representational structure.
  • Use AI models as research subjects to explore neuroscience questions that are difficult to study directly in biological brains.
  • Distinguish between restoring lost capabilities, communicating with external devices, and expanding or altering the brain's capabilities when evaluating BCI applications.

🔬 Findings

Prima is a retinal prosthesis in which a tiny chip is implanted under the retina for patients blinded by the loss of light-sensitive retinal cells. assertion 02:17

Patients wear glasses containing a laser projector that projects an image onto the implant. The implant electrically stimulates the retina, bypassing dead rods and cones and sending a visual signal to the brain.

Source: Prima

Prima's clinical trial produced form-vision images in blind patients, including patients who filled in Sudoku puzzles and crossword puzzles and patients who read books. observation surprising 08:55

The transcript presents these observations as an existence proof that the device can produce coherent visual experiences, while noting that current vision remains limited.

Source: Prima clinical trial

The current Prima image has a small field of view, is described as like looking through a straw, and is only black and white. assertion 08:38

The proposed engineering path is to add grayscale depth and eventually color, with at least red and green viewed as feasible and blue described as more difficult.

Source: Prima

The visual pathway can be accessed at the retina, the lateral geniculate nucleus in the thalamus, or visual cortex V1. assertion 03:41

The retina is the first place where visual information enters the brain, the optic nerve projects first to the lateral geniculate nucleus, and the pathway then reaches visual cortex.

Visual cortex V1 contains approximately half a billion cells. assertion surprising 04:03

It is located at the back of the brain and is one of the possible targets considered for restoring vision.

A motor-cortex implant can allow a quadriplegic patient to play video games in about an hour. assertion surprising 07:25

The transcript uses this as an example of how directly interfacing with neural computation can produce an immediate functional effect compared with many drug-development approaches.

The brain receives and sends interaction with the environment through a relatively small number of cranial and spinal nerve pathways. assertion surprising 26:21

The optic nerve carries visual signals, while the vestibulocochlear nerve carries hearing and balance; the broader proposed interface targets include visual, auditory, balance, somatosensory, and motor signals.

Vision, hearing, balance, and approximately a kilobit per second of motor control are described as potentially sufficient to get halfway to the capabilities imagined in The Matrix. assertion surprising contested 14:07

This is presented as a speculative benchmark for how relatively limited neural input and output channels might support major changes in interaction with the world.

A conscious moment combines visual, auditory, tactile, and olfactory experiences in parallel. assertion 17:49

An unresolved problem is how the brain constructs these different components and causes them to be perceived together while keeping one person's experiences separate from another person's.

Continuity of experience is argued to matter more for personal identity than preserving an exact static pattern of responses. assertion surprising contested 18:28

A software simulation that answers exactly like a person but lacks phenomenal continuity is described as less satisfying than a continuously experienced transformation, even if the transformation is dramatic.

A complete human connectome is still described as relatively far away, while a mouse connectome is described as comparatively near. assertion 19:17

A detailed mouse connectome is proposed as potentially useful for understanding brain architecture and for research into how neural systems generate experience.

The platonic representation hypothesis proposes that AI models and biological brains may develop similar representations of concepts. observation surprising contested 20:09

The transcript reports that mathematical objects inside large AI models have geometry similar to structures observed in neuroscience, and that alignments have been obtained between animal-brain neural recordings and AI-model internal representations.

Source: Platonic representation hypothesis; Science

It is not yet clear whether the apparent similarity between AI and neural representations is global or only local. assertion contested 21:22

The transcript says relational structures between ideas may be recoverable locally without implying that disconnected concepts occupy corresponding positions in a single global structure.

Source: Platonic representation hypothesis

The brain is described as having an approximately 10-bit-per-second cognitive bottleneck. observation surprising contested 29:29

One supporting observation involves asking a person with a perfect memory to draw what they saw from a helicopter over Manhattan; the reported recoverable detail corresponds to about 10 bits per second over the course of an hour or two. The transcript says multiple independent lines of evidence point toward a similar bottleneck.

The transcript argues that thoughts do not necessarily exist as fully formed, language-independent content waiting to be read out by a brain-computer interface. assertion surprising contested 29:13

The feeling that an idea is already complete is described as potentially misleading because attempting to write it out can reveal that the thought was not fully formed.

How it works

  • Retinal prosthetic vision04:01
    A laser projector in glasses sends an image to a chip implanted under the retina; the chip electrically stimulates retinal tissue, bypassing dead rods and cones; the resulting signal travels through the optic pathway to the brain.
  • Visual pathway targeting04:03
    Visual information enters through the retina, travels along the optic nerve to the lateral geniculate nucleus in the thalamus, and then reaches visual cortex V1; a neural device could theoretically stimulate at any of these stages.
  • Neural computation10:14
    Matter arranged in a particular configuration changes state over time according to physical laws; if those state transitions solve a computational problem, the arrangement is treated as a computer, with the brain offered as an example.
  • Cross-brain communication14:53
    A person maps an internal concept into a shared representational structure, serializes it into language or another signal, transmits it through a channel, and causes a corresponding pre-shared concept space to activate in another brain or AI model.
  • AI-neuroscience representational alignment20:40
    AI models and biological brains learn or encode concepts in internal mathematical structures; comparing their geometry and aligning animal neural recordings with model representations can reveal shared relational structure.
  • Substrate-independent interaction26:21
    If neural interfaces can exchange visual, auditory, balance, somatosensory, and motor signals directly with the brain, the brain could interact with a substantially different external or computational substrate without requiring the original biological body.

Commonly believed, but no

  • Brain-computer interfaces are primarily about decoding motor signals or creating a brain keyboard.11:03
    → The transcript describes BCI as a broader category that can include restoring vision, hearing, balance, and other sensory or motor functions, with brain keyboards representing only one possible product.
  • A retinal prosthesis only produces flashes of light rather than coherent visual forms.08:55
    → The transcript distinguishes earlier retinal prostheses that produced flashes from Prima, whose clinical-trial patients reportedly experienced form vision and could perform tasks such as reading and completing puzzles.
  • Thoughts are fully formed, nonlinguistic content that can simply be extracted faster through a brain-computer interface.29:13
    → The transcript argues that thoughts may become fully formed through thinking, speaking, or writing, so the feeling of a pre-existing latent thought may be misleading.
  • The brain is fundamentally unlike a computer because it is biological rather than built from transistors.10:14
    → The transcript uses a broad computational definition in which any physical system whose state transitions solve computational problems qualifies as a computer, and applies that definition to the brain.

Still unresolved

  • How does the brain construct separate sensory components and bind them into one simultaneous conscious experience?
  • Where does communication with an external device become a new structural capability integrated into the brain rather than ordinary communication?
  • Whether continuity of experience, rather than informational or behavioral similarity, is required for a software copy to count as the same person.
  • Whether the shared geometry between AI-model and biological-brain representations is global or only local.
  • What the detailed overall architecture of the human brain is.
  • How close researchers are to achieving substrate independence.
  • Whether neurodegeneration can be addressed through neural-interface and perfusion approaches.

🧰 Tools & AI usage

AI is used for

  • Compare internal representations in AI models with representations in biological brains. — Investigate whether AI models and brains develop shared underlying representational structure.20:09
  • Align animal-brain neural recordings with AI-model internal representations. — Use representational alignment as evidence and a research tool for understanding intelligence and neuroscience.20:41
  • Study neuroscience on AI models. — Explore neural and cognitive phenomena in models because they are easier to study than biological brains.22:10

📄 Transcript

Searchable transcript of From Restoring Sight to Reimagining the Brain, with Max Hodak — No Priors: AI, Machine Learning, Tech, & Startups (31:39). Search for a phrase, then click its timestamp to jump straight to that moment in the video.

Captions sourced from the original video on YouTube, published by No Priors: AI, Machine Learning, Tech, & Startups. The video, its captions and all related intellectual property remain the property of their respective owners; AINotes claims no ownership. Provided for research, accessibility and search — see the Transcript Notice and Copyright Policy.

00:00 the brain very literally, very clearly, plainly as a computer. You can solve computational problems by arranging matter in a certain way and then like taking your hands off and pressing go. We talk about being a brain in a vat, that's what the skull is. Like the brain is connected to the environment through a small number of wires, the cranial and spinal nerves, these little cables that carry your interaction with the world.

00:20 If you can get the visual signal, auditory signal, balance, motor in and out of the brain, that is an end in itself, that is the central object. The retinal prosthesis is right now I think is [music] a great proof of concept that we're on the right track. Nobody had previously ever been able to restore a form vision image in the mind's eye of a of a blind patient in this way.

00:36 We need to add [music] depth of gray scale, we think we could see a path to get at least red and green. And so there's ways that we can compound upon this path through an engineering process to make a product that's better and better. >> Hi listeners, [music] welcome back to No Priors. Today, I'm here with Max Hodak, the founder and CEO of Science, [music] formerly of Neuralink.

01:03 We talk about Prima, the implant that helps people who have gone blind see again, which just got regulatory approval in Europe. >> [music] >> Their quest to sustain the human experience and substrate independence for the brain. We also talk about alignable representations between AI models and the future of neuroscience. Welcome, Max. Max, thanks so much for doing this.

01:26 >> Thanks for having me. >> So, for anyone who is not familiar with Science, can you just describe a little bit about uh you know, why you started the company, leaving Neuralink, what the mission is? >> Fundamentally, we're a medical device company. Um but I think if like the mission of lowercase S Science is to use a differentiated understanding of the universe to improve the human condition.

01:45 I mean, that's that's the mission of uppercase S Science, that's what we do. We use uh specifically an understanding of how to work with the brain to get big effect sizes that you don't get in medicine often. Um our main product is a retinal prosthesis. You can think of it like a cochlear implant for the eye. Um, cochlear implants are some of the biggest impacts in in all of medicine.

02:03 I mean, you can if you've ever seen a video of a newborn turning on >> [snorts] >> uh, turning it on for the first time, it's striking. And our goal is to to build things like that, including our Prima retinal prosthesis. >> And for people who are not familiar with that, it's a chip that was inserted with glasses. >> It's So, it's a tiny chip that's implanted under the retina in the back of the eye for patients that have gone blind due to loss of the light-sensitive cells in the eye.

02:27 Um, so specifically, this is diseases like macular degeneration, which our clinical trial was done in and we're about to do studies in retinitis pigmentosa and Stargardt's and a couple of other diseases. So, it it's a chip that sits under the retina and then converts it So, the patient wears glasses that have a laser projector that projects an image onto the implant that then stimulates the retina to bypass the dead rods and cones and stimulate the retina directly to get a visual signal back into the brain.

02:53 >> How did you go from uh, we should have like a nick basically in the brain to this particular form factor as the first premise? >> Well, when we started the company, we had a couple ideas. Um, the one of the ideas was this was the biohybrid neural interface um, direction, where instead of placing metal wires into the brain or genetically modifying the brain, what we do is we engraft in living neurons that grow in and form new biological connections.

03:25 That's a big research project. It's very exciting research, but also um, needed to be paired with another near-term business. And we asked ourselves like, what was the most valuable thing we could do? And we thought that we could restore vision to the blind with the resources available to us and and where the state of the field was in early 2021. And it So, if you want to do that, you have to start from this understanding of like, how does the brain get vision?

03:45 What is vision in the brain? And you you could look at the retina, which is obviously how vision gets into the brain the the first place it's created. The the first stop of the optic nerve into the brain is a structure called the the lateral geniculate nucleus in the thalamus. So, that you could think, "Oh, we'll stimulate the LGN." And the connection from there is visual cortex.

04:04 Kind of like it's a half a billion cells up at the back of the brain. And so, if you want to restore vision, you can think, "I can go into the retina. I can go in through the the thalamus, or I can go in through V1." There's a bunch of scientific technical reasons that lead you to think if you have an optic nerve, you want it to be in the retina. And from there, you have a choice of do you stimulate There's two types of cells, and there's a couple different ways you can stimulate them.

04:29 And so, we explored kind of all variants of that early on. We developed an in-house gene therapy that affected the retina in one direction. We did a survey of electrical stimulators. We looked at ultrasound. And what we ended up doing is we developed indigenously a state-of-the-art gene therapy, which is probably going to humans next year, as well as we we found the state-of-the-art out there in the world of people electrically stimulating the retina.

04:53 And there was a company in France called Pixium >> [snorts] >> that back in late 2022, um had by far the state-of-the-art work. It was originally developed by an inventor at Stanford and then licensed to this small French company. And they were in the middle of clinical trials. And we got to know them over the course of a couple years, and then we're in a position to acquire them when we saw something that I think kind of nobody else really saw at the time.

05:20 And that I mean, we that deal has turned out to be great. >> Can you talk about the recent um CE designation regulatory approval you got? >> Yeah, so it took us about 2 years for post acquisition to get it to the place where this was was possible, but we just in July got marketing approval in Europe for Prima to start commercially selling it there. Um and so, that's a major milestone.

05:40 That means it's it's really commercially available. The first sales will happen in the coming weeks. >> That's amazing. I think most people think of anything in the BCI field as, you know, a a moonshot project that may or may not pan out 10 years from now. >> Well, I mean, people forget that the moonshot worked. Like, we went we left like footprints on the moon.

05:56 And so, this comparison, I mean, I think that there's it has gotten used in Silicon Valley to mean these things that have extremely long odds and are unlikely to work and therefore we can vaporize a bunch of investor money just fine. It's like, you know, when we went to the moon, we did it. And so, historically, the success rate of moonshots is higher than I think people give them credit for.

06:15 The most one of the most important thing is having a real business here, and this is the start of that. >> Can I ask how you um when you were exploring both uh different signaling pathways and form factors and just conditions to go attack um or uh how you thought about scope of timeline and engineering cost and risk? Were you Were you just looking for like the um like big enough to be useful and feasible in some period of time or how did you think about funding the project and how long it could take?

06:46 >> So, there's three elements to our pipeline. The first is our work in vision, second is our biohybrid neural interfaces, and then the third is a our work in a different area of of medicine, um perfusion a program called Vessel. These three things together form kind of the minimum set of things that I think if they're successful on the time scale of 10 to 15 years, could really drive a a signi- I think a significant revolution in medicine broadly.

07:13 People have spent huge amounts of time and money looking for drugs to restore vision or to restore hearing or to stop Parkinson's or to to help paralyzed people move again. Understanding the like the biology and the molecular detail required to make a drug has been very difficult. Humanity just isn't that good at that, to be totally honest. On the other hand, the brain is a computer, and when you deal with the brain as a computer, you get these these things to work very like it's just again there you don't see

07:40 demonstration you don't see things in medicine like a cochlear implant being turned on or a deep deep brain simulator being turned on or I mean, you can implant to a quadriplegic patient a motor cortex and and have them playing video games in like an hour. Like this just you just don't really see things like this in meta in most drugs. Um and so there's this >> you know, in small molecule random walk, you know, sifting in in nature.

08:04 >> Yeah, I mean, small molecules especially are super hard. I mean, even I mean, you can do some super highly engineered patient specific car-T and instead you get like an giant immune overreaction. It's like if I put electrodes in M1, you will probably be using a computer in an hour. Um and so it's just it's easier, it's more amenable to biology in many ways.

08:24 You can do drug discovery for a decade, run a clinical trial, you're going to turn over a card, the answer might be no and then like what do you like you everybody goes home. Whereas here, we have a clear sense of how to make thing better. Um the retinal prosthesis right now I think is a great proof of concept that we're on the right track. Nobody had previously ever been able to restore a form vision image in the mind's eye of a of a blind patient in this way, but at the same time, it's it's a small field of view,

08:52 it's like looking through a straw, it's only black and white. Um we need to add depth of gray scale, we think we see a path to get at least red and green, blue is a little bit trickier. And so there's ways that we can compound upon this path through an engineering process to make a product that's better and better. >> Can you talk a little bit about what you saw in the clinical trial in terms of variation between patients or what the ceiling was so far?

09:15 >> Yeah, I mean, in the clinical trial, I mean, the main thing was just the existence proof of like that success was an impossible outcome, right? Like that we had patients filling in Sudoku puzzles or or crossword puzzles. Um there were patients that were reading books and so I saw some of these patients some of these videos, um met with one of the patients, talked to the surgeons.

09:35 We um I mean, this is one of those things that seems too good to be true. >> How did clinicians react to all of this? Like, do would would the people that you work with say at the beginning like, yes, Max is right, like the brain is computer, this should definitely work. It should work at a higher likelihood and better rate of progression than our random walk in biological understanding.

09:55 >> Well, if you want to make people angry, you should tell the internet that the brain is a computer. >> Okay. We'll start by doing that. All right. >> Yeah. Um, that kind of starts you off in a in a um, like a defensive place. >> Why don't people like that? >> I don't know. This is one of those things This just feels like bike shedding to me. I mean, to me, I don't mean that metaphorically.

10:12 Like, the brain very literally, very clearly, plainly is a computer in in my understanding of the world. I also view the universe generally as a computer. Like, we can solve pro- like, you can solve computational problems by arranging matter in a certain way and then like taking your hands off and letting impressing go. And so, the fact that like that that that that unfolds in time to solve some computational problem, I think of that as a computer, the brain is the same thing.

10:38 Um, and that I don't think there's necessarily >> That's a broader definition of computer than I had before. >> there. >> Yeah. >> Yeah, I mean, there's nothing special about transistors. I mean, we understand computers in this idealized way as the as like a Turing machine, that's an abstract computer. Um, it's just you're going from state to state in ways that are subject to laws that mean that the transformations are interesting and meaningful.

11:00 But, no, I think this was fairly contrarian. Um, the both in the sense that BCI has this broader interpretation than motor decoding, um, as well as the like like, is a retinal prosthesis a BCI? And that's also kind of a this minor definitional question, but if you think that it is, then that that kind of opens up this interpretation of of a lot of areas of medicine that could be accessible to it that other that people weren't really thinking about.

11:27 I mean, clearly there was interest in look like looking into this. Like if it wasn't that contrarian. It's a different approach and I think we come from a different culture than a lot of the conventional biotech industry. Um there's always been kind of an East Coast, West Coast divide in biotech especially. Um and we are more of a tech company than a conventional biotech company.

11:49 >> Mhm. >> And our device view of a lot of historical biology problems makes us even more of a tech company by biotech standards. So we mostly raised from from tech investors, not that much from biotech investors. In fact, there's only one VC that I sought out at all at the series A that I went to go pitch, which was Bob Nelson, who's a biotech investor.

12:09 >> When you um describe different types of BCI products and missions, uh I think you have a really good way of explaining it that is, you know, on a spectrum. Can you can you talk about just the landscape of what devices and approaches people are are working on in BCI today? >> Yeah, I mean I think BCI is a category kind of like how pharma is a category.

12:28 I think sometimes you I I'll talk to VCs and like, "Oh, we have a BCI bet." I'm like, "Do you have a drug bet? You made one bet on a drugs? Like that's that's how you think about the category?" >> Mhm. >> Everything from >> versus thinking about it like in, you know, neurodegeneration and Parkinson's or specific conditions. >> even different bets within neurodegeneration.

12:45 Maybe you've got a degrader, maybe you've got a gene therapy, maybe you've got something else. Like because they're um >> different hypotheses. >> Yeah. And similarly, I think on one end of the spectrum, you've got silent speech devices that may be BCI in a greater or lesser degree. Like maybe they're recording a neural signal like EEG. Maybe they're using something just like radar through the face, which I know like you know it's an idea out there.

13:08 Um but these are all basically hand substitutes. And on the one hand, hands are great. Two On the two hands, hands are great. The they work really well. You don't need to think like I'll talk to teams that say like, "Oh, well, it'd be really nice if to go to your next thing you didn't have to like open the Uber app and like call an Uber. You just like thought of it and it was there.

13:28 I'm like, "You probably want to communicate really unambiguously with the Uber app." It'd be pretty annoying if they just start like spontaneously getting notifications during meetings that like, "Oh, it thought that you were thinking about an Uber, therefore it decided to summon summon two for you." And so you'll probably want these to be pretty explicit.

13:43 And to the degree that that is a volitional intent, like you already don't need to do a lot to your hands to do things. Um now, could you have extra hands? Extra hands famously useful. Um and so having some easier way to communicate um might it might be useful. That is kind of outside of the scope of things I spend a lot of time thinking about because if you can if you get vision, hearing, balance, and a kilobit per second of motor control, you're halfway to the Matrix.

14:12 And this takes you into some like really trippy interpret reinterpretations of medicine. And that's the stuff that we work on. I think other people will do things like speech to text and and uh AI communication. There is a distinction, so there's there's a Let me come back to your broader question in a second, but there's some point where you go from communicating with a thing to ex- redrawing the border around your brain.

14:40 And we don't have a great sense of exactly where that transition is yet, but there's a sense that there is one. Like you the way that you use the two hemispheres of your brain as one integrated bound thing is different than the way that you talk to another person. And [snorts] it's not just that there's correlation cuz like all communication is about creating correlations between brains.

15:00 When we speak, there's big correlations that are being driven between our brains because there's uh I mean all all communication is is like premised on that. If we didn't pre-share a language or some common education, like some sense of math, then we wouldn't be able to communicate those concepts because there's some there's something that's lit it in my brain.

15:20 I can serialize that to language, can send that to you, that lights up the same pre-shared concept spaces. And so, there's one mode where you're you've pre-shared some structure between the two brains, whether this is an AI model or biological brain, and then you're communicating over the channel. The other is you've added some new structural capability.

15:37 I think figuring out where that transition happens is a really like a really compelling area of research for us. >> What are you most personally interested in in terms of exploring that boundary yourself? >> Yeah. Well, I mean, that is a like what is you is a really central question here. Um like if the end of the artificial intelligence quest is >> care.

15:59 What if I just want my brain to be a better computer or a richer one in terms of understanding other people's experiences? >> I mean, I think that you still there is an important question here. So, if I just like scanned your brain into a computer and there is a software simulation of you, >> Mhm. >> is that does that count as you? Like would that make you feel better about dying of cancer?

16:19 Like if you were diagnosed with lung cancer and so you said, "Okay, well, we'll scan you into a computer." So, you So, imagine that we do it like non-in non-destructively. So, you're still you are still there, but then you're talking to the software replica of you. >> Mhm. >> And then you're like, "Okay, I'm going to go to hospice, but this thing will keep doing my venture investing job."

16:37 >> Mhm. >> Like does that make you feel better? >> That much? Well, I I think on this question I'm Have you ever been under [clears throat] general anesthesia? >> Yeah. >> Yeah. Well, >> And that produces a break there and that's This is the type of thing that you have to explain about. Why does that >> feel different? >> Mhm. Because I think it does feel different.

16:51 I think that people are reticent to undergo general anesthesia, but they do it and they survive and they realize it's fine. And then there's if I could make a copy of you and you can talk to that copy and you're like, "Okay, I will go away now." I just don't think that many people are going to be like, "This is it." Um and so, you have to answer why it's different.

17:08 There's an asymmetry in the uh so, when you've got like some of the operators that actually change things in physics. So, like a creation or annihilation operator. And we get these in life, right? You can create a new life or a new mind or a new soul. And then there are times when they can be annihilated. They can get destroyed. And then there's ways that they kind of change while intact.

17:33 >> Do you study consciousness um at science in a like a sequential way or directly explicitly today when you talk about the operators that are part of it and science? >> So, so your conscious moment is a you're experiencing a bunch of things in parallel. So, you you're seeing things and you're hearing things and you're feeling things and you're smelling things and these things happened just simultaneously together.

17:59 But they are they're kind of different elements of the experience and we want to understand how does the brain construct each of those and how does it cause them to be perceived together to the exclusion of other things? Like you have your vision and your hearing. You never get my vision and your hearing. Um and I like you kind of have this like you might think like that sounds really obvious like it's in my brain, it's not in your brain.

18:19 But we need some more fundamental explanation for really how that partitioning happens. >> Okay, so you think that's a a foundational component. Yeah. >> And so and yeah, so I'm in the camp that like continuity is greatly important. And so people will accept significant drift in their identity over time as long as they have continuity. >> Mhm. >> But if you preserve the sense of identity like you have a software simulation that answers exactly like you would now, but it's not phenomenally continuous.

18:46 >> Mhm. >> That is less satisfying. >> Yeah, that's an interesting trade. I think I would take dramatic morph but con- continuous experience. >> Yeah. I don't know if I'd take like significantly degraded IQ. Laura Deming asked me this. >> Yeah. >> It's like life with provable characteristics is a thing we've never seen before. And it might be might be transient.

19:03 Like you probably accept degraded IQ for some period of time if it then got backfilled some number of weeks later and then you got some expe- I mean, at that point where you achieve substrate independence, you can really you can take that almost anywhere you want. Which is why that's really really interesting. One of the big missing pieces here is connectomics.

19:17 Um that is getting to the that is getting pretty close, I think. In terms of to the point where the project could be done. Um we're still relatively far from a human connectome, but I think we're not that far from a mouse connectome. That would be enormously useful for for like facilitating this research and understanding about how all this works. We need to understand like even really basic questions like what is the overall architecture of the brain?

19:44 We have some answer for, but I don't know that it's like a really really detailed one at this point. >> You are of the view that it makes sense that there is this increased like uh interest, this surge of investor interest and founder and engineer interest in BCIs a field given the progress of AI model research because of the representations actually should be shared or they they empirically seem to be.

20:09 >> Yeah, I mean this is this is the idea called the platonic representation hypothesis. And this is really interesting. It's it is controversial in the community, but I mean from where I sit there's clearly something real happening. And so when you look inside these big AI models, the mathematical objects that you see look a lot like the things that you see in neuroscience.

20:25 So if you look at how do how do these AI models represent um just like represent concepts and you look at the parts of the brain that represent concepts, you see these you see very similar geometry. That to me was one of the first clues. Like when I really saw that and we we use that practically. Like we use that constructively at science. Like that's we know that that is that is true because we can get alignments between animal brain neural recordings and AI model internal representations.

20:53 And that was a big clue to me that the AI AI was on the right track and this was like not a gimmick and not hitting a wall. There was like something deeper deeper that's true here. Um there's some fact about the universe where these things as they're learning are grabbing onto some true underlying data manifold. I mean it feels like a lot of physics.

21:08 Like if you apply enough compute to matter, you get this thing that looks like intelligence. >> Why do you think that's controversial? Or why is it in the field? >> There's some faction of people that kind of don't want this to be true for reasons that are not totally clear to me. Um it is also not clear we don't complete we don't really under fully understand the whatever phenomenon is happening here.

21:29 It's unclear if the structure is global or if it's local in some sense that in the like there's you can recover relational structures between ideas, but it might be that this this works locally. It doesn't like that where disconnected things might be placed might like this this gets fairly detail like tech technical quickly, but there's a bunch of stuff that we just don't know and I think this causes um great space for people to wonder is this as giving us this fundamental of like a hint as it might seem.

21:59 I think that it is. >> What do you think are the most fertile ways to study neuroscience today if if your set of beliefs is true? >> Yeah. Well, I mean ironically it's probably working on AI. Yeah, I have some I have a couple of neuroscience [clears throat] friends at at Open AI and Anthropic who it's like we would joke like, "Oh, you left neuroscience?"

22:18 Like, "No, no, no. It is just way easier to do neuroscience on the models." Um but to the the degree to which it is neuroscience is fascinating. >> I want to talk a little bit about the future and um the maybe the very short and then the medium time scale for for science short of you know, changing the boundary of who who we are. So, um what does it what does it look like to commercialize um the uh first program for you?

22:43 You said that there need to be hundred million dollar run rate businesses in this field. How do you get there? >> Yeah, well I mean becoming profitable or at least have like having the ability to do this forever is a super high priority. Restoring vision to the blind is pretty good business if you can actually do that. >> Especially since almost everyone has the problem as an age-related problem.

23:04 >> Yeah, so AMD it's like one in two have some early stage by 80. Um the it's like one in 10 85 um that I'd actually have it. The it is definitely a major issue and and not just vision but these topics in general affect everybody. We don't have firm pricing yet. This is a thing that we are being a little cautious about how we talk about public because we aren't like totally sure yet.

23:29 But the precedents for vision are all I mean I think we can say they're expensive. I mean Second Sight 10 years ago they So there was a company about a decade ago that had a retinal prosthesis that works differently than ours does. It did not get out the type of performance that Prima does but was briefly approved cuz then there's really nothing for these patients.

23:51 There's always been a lot of enthusiasm for anything that could possibly help them. And they didn't get what we call form form vision. They didn't get like a coherent like face or like like paragraph that that your eyes could scan over. They got these flashes of light that patients could look at and kind of think about assembling into what they meant.

24:08 Um they got paid about $150,000 per patient um in the mid-2010s. There's a gene therapy that works that is only relevant in the first place for about 5% of patients in one narrow indication um and it really doesn't work that well. It gets a 0.1 lines of improvement. It kind of slows the rate of degeneration for some patients. That reimburses at almost half a million dollars per eye.

24:35 And so there's I mean some of this is a function of just how expensive it is to develop these therapies and how high the failure rate has been historically. Um and then um some of it is that there's just it is I mean vision's very dominant sense for us. If you if you lose that, that's totally debilitating and restoring it is is very important even just like minimal vision.

24:58 So, the the TAM will grow over time. For this first version, it's on the scale of like hundreds of thousands of patients in the US and Europe. So, for the the current version, frame is probably hundreds of thousands of patients. And then the next version, which is going to animal studies now, will be in humans hopefully next year, um should expand that to millions.

25:17 >> You said something that surprised me as a intermediate point between um vision and, you know, fully understanding consciousness. Um how does oncology or other like how do other indications fit into the picture in terms of what you might work on? >> I mean, the thing that makes you you the only organ that you can't even in principle transplant is the brain.

25:38 The like the heart, pancreas, the liver, the lungs, as far as I'm concerned, they're really support characters. They're there to keep the brain activity interesting and and going. And [snorts] I think we're going to get to a point where because the biology is so difficult, I mean, you've got this like alien nanotechnology that is around us that we're like completely surrounding us, that we're completely dependent on, that we understand still very poorly.

26:01 Instead of needing to solve that, are there ways where we can accomplish the same fundamental goals, you know, like using a toolbox that humanity is much more advanced in? And so, I'm going to be ultimately fairly disappointed if I'm murdered by my pancreas. And that I think that's that's the worldview. It's that the thing that matters is the brain.

26:21 The brain is the computer that gives us this. You could We talked about being a brain in a vat or have like these upload uh thought experiments, but you already that's what the skull is. Like the brain is connected to the environment through a small number of wires, the cranial and spinal nerves. The optic nerve is nerve two. The vestibulocochlear nerve that carries hearing and balance is nerve eight.

26:43 You've got these these little cables that carry your [snorts] interaction with the world. That world is is generated by the brain. And so, if you can get visuals the visual signal, auditory signal, balance, motor, like somatic sensory motor in and out of the brain, that is that is an end in itself. That is the central object. >> Mhm. >> And through a mix of the BCIs that allow you to kind of change the the the thing that it's interacting with and our perfusion medicine program, um we think that there's ways to

27:17 significantly improve um not just lifespan but healthspan and kind of create a better a better quality of life for many patients in ways that I think we'll feel kind of like a lateral move rather than just solving many of the things that people have seen on the horizon. >> For people who are um interested in working at or investing in science, if you are successful, you know, what will be the change to human experience 20 years from now besides you not worrying about your pancreas as much?

27:48 >> Yeah, I mean that's it. Like that's the there's the there's a like a fragility that we all live like there's this jeopardy that we all live under as part of the human condition. And I think that if we're successful, what will happen is that sense of jeopardy will fade. Like we will be we will just become much less fragile. Um we will have the ability to upgrade and replace parts of ourselves.

28:09 So, neurodegeneration we don't know about. That one still seems that's still difficult. That still needs like real investment. Um the two leading causes of death though are cardiovascular disease and cancer that metastasized to the brain and I think both of those are going to be really attackable through this type of work. Um the other extreme is if we're serious about exploring the universe and going to the stars, we are going to have to adapt ourselves to that environment.

28:36 We're not going to export Earth with us everywhere we go. And [snorts] these bodies are great, but they're designed for this planet. And it is going to be adapting ourselves to the hard vacuum of space is definitely going to be um I think the thing that we want to do in the long run. And ultimately those are the same those are the same project. >> Being able to preserve yourself and being able to adapt yourself or update yourself.

28:59 >> substrate independence, yeah. >> Yeah. Substrate independence, I'll use that phrase. The the simplest premise for a company in the BCI domain today is like you can in some way and basically non-invasively talk to an AI model um in like a high-bandwidth way. That is not your focus of interest. Why? >> Yeah. Well, I mean first of all, I think that talking or writing is thinking.

29:21 I think this idea that there's the stuff that's just this kind of pre-formed in your brain that if you could access it through BCI, it would be faster is probably not not the case. >> You don't think there's some special latent state that's not language? >> No, I think that but the again feels like it you'll have you'll it'll feel like it's fully formed, but until you really sit down and try to write it out, it is it isn't really.

29:43 And I think that feeling is misleading. And so there's this there's this like 10 bit per second kind of famous like cognitive bottleneck. There's this observation that the brain seems to process information. Like if there's a bunch of ways you can triangulate this. You can put somebody with a perfect memory on a helicopter right over Manhattan and ask them to draw what they saw and then you look at all the details that works to about 10 bits per second over course of an hour or two.

30:05 There's like a a bunch of different independent lines of evidence for this. So there's some deeply evolved cognitive bottleneck at a about that. I think that this kind of rolls up to language. But even so, but even if you if you take that it probably I mean it probably would be nice to be able to walk down the street with like a cap on and like ask questions to my AI through monologue.

30:26 Like that might be possible. There's probably some combination of EEG and MEG that might be capable of this. Um that is still just like a different type of product. That is not the thing we are trying like brain keyboard is I'm not it might be valuable. It might turn out to be like AR AR glasses where it's just we were our attention was already fully 100% occupied and putting it on the face didn't really change that.

30:49 We were already consuming all of the available time. But the at the other end of that spectrum are things like generating vision or generating hearing or um achieving substrate independence. Those are the things that we are focused on, not brain keyboard. Um both of these are potentially BCI um problems or products, but very different types of companies that will build them just as I think you have a huge range of of drug companies.

31:20 >> Find us on Twitter at No Priors Pod. >> [music] >> Subscribe to our YouTube channel if you want to see our faces. Follow the show on Apple Podcasts, Spotify, or wherever you listen. That way you get a new episode every week. And sign up for emails or find transcripts for every episode at no-priors.com. [music]