Brain Computer Interface Frontier: Movement, Coma, Depression, AI Merge

31:09Think about it like an API. But I think the companies that are able to record at high fidelity and then transmit the neural data are going to be able to create an ecosystem around them to do all sorts of things that are right now not possible. And just to be clear, you've already had inbound from quite a few. Okay. Okay. So yeah, but before we go to break, let me like throw out like one example, like potentially you could be reading signals of depression on someone's brain and then maybe some ancillary company can use that API data to like stimulate the part of the brain that has a deficit of some electrical signals as a potential cure.

31:49I mean, that's already starting in academic research where there's sort of closed loop systems that are helping people who have refractory depression that doesn't respond well to medication and which is very severe with systems. Right now, we have technologies like electroconvulsive therapy, which are very coarse, which effectively incite a seizure in people. But it does have efficacy, which is why it's still used. But if you think about... Imagine being targeted on this stuff as opposed to just using brute electricity. Exactly. Yeah, I think we're headed to that future. You raise a good point and an application space that we've thought a lot about and that many people think about.

32:28And I think kind of what you're alluding to is this concept of a digital biomarker. And it's something that we can do with the precision system that's very difficult to do with the system of penetrating type electrodes for a number of reasons. But - What's a digital biomarker? A digital biomarker is kind of like a signal, but it's instead of a molecular readout like you get with a blood test, it's a digital signal that you get by electrically reading the brain. So think about if you were to place the precision electrode array over a relevant region of the brain that's relevant to depression and some of those are already known and well established.

33:11So in a patient who's prone to depression you might see and this is already very good preliminary data to suggest that this is the case. You might see that when they're beginning to enter a relapse of their depression there are particular digital signatures that occur in that area of the brain and that are predictive of them entering a relapse and that can be life-saving for people you know who may become suicidal due to severe refractory depression so being able to predict those periods before they happen and either deliver stimulation or change their medications or alert you know alert a care team that that is in the process of happening and that kind of concept actually is common across a number of important disease states, including epilepsy and depression and others.

34:00So this is a direction that, you know, that we thought a lot about, that we've had good discussions with, you know, the industry about. And it's actually not that dissimilar from some of the molecular studies that people do nowadays. You know, like in the era of gene sequencing, You know, low cost gene sequencing has enabled many people to do to learn a lot about their own biology and predict things about them that they wouldn't have already known about. So it may be that, you know, one direction for neurotechnology is is is something like this. Go ahead. No, I think Ben's getting a really important theme that we talk about a lot in the company, which is, you know, why has there been more progress in other areas of biology than there has in neurology?

34:47And one of the reasons, I think, as Ben is alluding to, is that we've been able to digitize biology in other areas, genomics revolution being a perfect example of that. And that has led to a number of breakthroughs and very rapid progress today. It's been tough to convert the neural signals of the brain into something that we can apply compute to. The brain is hard to access. Ben knows this better than we do. It's hard to get there. And once you do it's - Some good design keeping that thing protected. That's right. The skull does serve a purpose. And the biology, once you get there, is sort of this mushy mass.

35:25And so figuring out a way to effectively digitize this biological system in a way that is scalable, which again, I think the fact that our system is scalable across different areas of the brain at the same time at super high resolution, this is something that we think is going to end up unlocking a number of breakthroughs, which frankly today are hard to predict. Yeah, I know you wanted to get to where does this take us in the world of AI and foundation models and modern machine learning and how does that connect to what's happening in brain-computer interfaces. And I think this is kind of a good segue for that.

36:05And just a bit of intuition that I would want to provide, this is something special about the precision system because the electrodes that you were holding in your hand a minute ago they form a regular lattice and they have a spatial relationship with one another that's kind of like the spatial relationship among pixels on an on a screen it's the same every time and so when those are placed uh onto the brain of one patient the the data format that they read out is the same data format and has structural elements that are the same from patient to patient. So it brings commonalities across patients that we've studied into very sharp focus.

36:48And that has been a major limitation of the ways that we've interfaced with the brain, you know, for generations, including with the penetrating electrodes that are used by other systems because when you penetrate into the brain using needle-like electrodes, the spatial relationship of what you're recording from is kind of a little bit random. Right. And so that relationship is not preserved from patient to patient, and it makes it very difficult to apply learnings from one patient to the next patient. In the precision system, one of the inherent advantages is that the data is so regular in structure that we're able to compress it.

37:26We're able to learn across patients, across populations, and leverage those learnings in the machine learning algorithms that we developed. And that we have found to be just a, you know, a massive advantage. I want to take it one level deeper and ask about decoding full brain activity and making the brain less mysterious. But why don't we do that right after this? So let's take a break and come right back. We're back here on Big Technology podcast with Michael Major and Ben Rappaport, the co-founders of Precision Neuroscience. Before the break, we talked a little bit about unraveling the mysteries of the brain through electrical signals.

38:04And at the moment, we could all agree the brain is a mystery, even though the technology companies like yours are getting better at decoding parts of it and, you know, being able to do something with that information. But do you ever anticipate a moment where the totality. I started this show saying, can we build a foundational model for the brain? And I guess that was a way of saying, can we find a moment where the totality of everything happening in the brain is decoded by technology? And if that happens, what does that lead to? We talk about this a lot. This is sort of in the zeitgeist right now in the tech world, this question of the whole brain interface.

38:43And I'm happy to discuss it. We have kind of our own view of what it means to have a whole brain interface and i think understanding what that implies um requires a few things one is that as we mentioned earlier the distribution of information through the brain is not uniform there are areas of the brain that are much more relevant to our interaction with the world than others. So most of the brain is actually not relevant for communicating with the outside world or with artificial intelligence. Most of the brain is taking care of the body and not in ways that are particularly relevant to interfacing with the outside world.

39:35Does that mean like controlling like blood flow and stuff like that? Does that happen in the brain? Let's call it our vital functions and unconscious functions and things like that. So that's all being directed by the brain. A lot of it is, and not all of it is, but some of it is. And certainly - It's fascinating, because I guess like we think that the heart beats and the blood goes and it has nothing to do with the brain, but the brain really is the command center for a lot of this stuff. The brain is involved. It's not necessarily doing everything moment to moment. Certainly the heart has its own intrinsic ability to function.

40:05But the brain is heavily involved in a lot of what goes on in the body. And, but my point is just that, and also a lot of the brain, as we mentioned before, is white matter connections between, you know, between different parts of the brain and from the brain to, for example, the spinal cord. And those are incredibly important for how the brain functions in a biological system. But with respect to interfacing with the outside world, those are much less relevant when you think about a whole brain, what we think about as a whole brain interface intuitively. So I want to start with that, that even though the brain, there's this notion that you want to have a whole brain interface.

40:47Actually, what I think we really mean by that is we want to be able to interface with the parts of the brain that are responsible for our conscious interaction with the world. and that actually is a spatially limited uh portions of the brain but isn't that relatively unambitious i mean i know it's very ambitious but this is easy for me to ask but i'm saying that like to me the thought is what about taking my memories and kind of dragging them from the brain i totally get that right and so the point i'm trying to make is that your memories have a spatial location within the brain for you know to it to a significant extent and so the problem of how to do that is not the same as how do we record the continuous state of every single cell in the 1500 grams of the brain i think it's very important to understand the brain is a physical thing it has structure and how we think about interfacing with the brain begins in part with with understanding that there are some parts that are more relevant to forming that interface than others?

41:49And then how do we get there? And how do we listen in or interact with those areas of the brain? So as we mentioned earlier in the conversation, we're really focused right now on movement-related areas, the so-called motor cortex. That's an area that's very, very salient to our interactions with the outside world in moment to moment. But the vision-related areas and sensation-related areas and hearing-related areas and memory-related areas and decision making areas. These are all surfaces within the brain that if you want to build an interface that encompasses all of those functions, you have to touch those surfaces.

42:30So in some way. Can we talk about two of those memory and decisions? So do you anticipate at one point, the science might or your companies like yours might be able to effectively go in and download our memories or maybe go in and like, you know, decision scientists would have a field day with this, like basically decode how we make decisions just by reading the signals off the brain. I think from the standpoint of those, those are two very different problems. From the standpoint of decision making, I think the answer is much closer to yes. And we have an understanding of how that sort of thing might happen.

43:07From the standpoint of memory, it's a little bit of a a little bit different and we can take those two questions, you know, one at a time. I'll just say that for memory, it's important to understand that the way the brain stores memory is very different from the way we think of memory being stored in the digital world. Yeah, this is important. Yeah, I think this is important to understand that memory as it's stored in the digital world, really the bits have a physical manifestation that on some level you interrogate them. When you store a bit, it's a spin state or something like that. And so the reading of those memories is really the reading of the state of something that at a very, very small physical level has a representation in the physical world.

44:02Yeah, click on a file. It will go into the sort of semiconductor mainframe and then access where that file has lived. Right. A transistor state is changed, right? Or a spin state is changed, or something in solid state is actually changed to represent the bits. So when we think about, you know, people talk about bits and atoms as being intrinsically linked, they are, right? There is really a one-to-one representation between a particular bit that you're trying to store and some state in the physical world. So how's the brain different? The brain is different because, and this really relates to how one of the ways that neuroscience has been so important in motivating developments in artificial intelligence is that the way that a particular memory is stored is not really in the flipping of a state.

44:59in order to read out a memory from the brain, you have to stimulate the network, what we think of the network as of the network that represents that collective, you know, memory, and you have to stimulate it with something that triggers the recollection, and the network then either completes or reproduces that, right? So if, as an example, you know, you can be reminded of a memory by by a particular trigger right or you can you can trigger yourself to remember something right but there's no scan that you can do or that we can do that looks into the brain and says there is the face of your family or there is the you know the the combination of your combination lock do you see the difference weird question then like where do the memories live when they're not there they they they um they don't really exist as such wow they they um they the brain is a system that uh that can produce the recall of the memories when appropriately triggered but it's not like somebody by reading the physical state of the brain with a scan the way you could a disk drive for example can can find all of those bits of information does that make sense it's like it's very different where do they exist so they just don't exist it's not that they don't exist but the the storage mechanism is very different it's like saying that in order to in order to get the in order to retrieve the memory you need to trigger it right so in order to in order to get the memory of a combination lock out of your brain you need to basically say what's the combination to your combination lock and then you'll retrieve the answer right um but it's much it's much more difficult to like there's no file address that we know to go to in your brain that contains the digits of the combination law.

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47:59I don't, what I'm trying to say is that it doesn't exist as such to the best of our understanding of how the brain works. So then how could a technology company then go and basically stimulate the brain to share memories? Maybe there's a way that, you know, I'd like to, for instance, like relive a memory. Or maybe, you know, there's something that my father told me 20 years ago that I forgot. But I really want to remember what he said word for word. Can technology one day be able to be used to stimulate that and then recall those memories? I don't think we know. I think we're far from knowing the answer to this.

48:36I think, well, let's put it this way. It's known that by electrically stimulating the brain, you can reproduce certain memories. But it's much at this stage of our understanding of neuroscience, the predictability of how we do that is really not well understood. Okay. um and uh but what one sort of uh way that i think we think about some of the questions that you're getting at is that we've just never had the tools before in neuroscience to interrogate some of these questions um so we've never had as high resolution a picture of the awake human brain as we now have with the precision system so you know the the electrodes that i mentioned earlier the 1024 tiny platinum electrodes most of them are 50 microns in diameter which is actually the size of a neuron.

49:22And we're starting with a postage stamp sized electrode array over motor cortex, but the medium term vision for precision is a much larger electrode array covering much greater areas of the brain's cortex with hundreds of thousands, someday millions of electrodes. And I think once we're able to achieve that and apply the cutting edge compute algorithms that are available today, we're going to learn answers to questions that right now we just haven't been able to interrogate properly. I think that kind of interface will allow us to fluidly interact with the kinds of digital memory that we kind of have more of an intuition for in our daily interaction with technology.

50:15And certainly many of the ways that we think of expanding our memory type capability is in that kind of file system storage way with addresses. So certainly we can think of ways and the way we interact with those memories are with the kinds of brain computer interface type technology that we're already talking about, right? So I definitely foresee a future in which we can, you know, a near future in which we can augment, you know, memories through that kind of fluid interaction. So we could have like an external hard drive that the BCI accesses? We kind of already have that, you know, with assistive technology today.

50:51I mean, you carry it in your pocket instead of in the cloud. But a direct link between a device and a brain would be wild. I think that we are already building towards a state of brain computer interface technology that will facilitate that. No question about that. And I think that that's important because it's based on just an extension of what we're already doing. Right now, we're already cyborgs in some way. We have this digital extension through a black box at the end of our hands that we tap on furiously. And that's how we access, you know, our external hard drives in the way, you know, whether it's, you know, a Dropbox in the cloud or Wikipedia or whatever.

51:32You know, I think the evolution of the way that human beings are able to control technology and compute has changed. It's changed repeatedly over the course of the past 40 or 50 years from mainframe computers where we have like punch cards to desktops and laptops where, you know, we use our hands to control a keyboard or a mouse. Now it's mostly phones. Increasingly, I think this is moving to wearables. Think about AirPods that people forget they even have in and, you know, makes them sort of quasi cyborgs. I think over time, it is likely that a more seamless, a more intuitive way for us to engage with the digital world is going to happen.

52:12And I think this concept of sort of thought-based control of computers, which right now still sounds like science fiction, even though we're doing it in clinics across the country, and even though it's been done in academia for a couple decades, it still sounds sort of fantastical. but the moment for real clinical adoption is very near. And this concept of seeing people control computers with their thoughts is going to become much less amazing and much more commonplace. And I think as that happens, our attitudes towards how to control computers is going to change. What about studying decision-making?

52:50Yeah, so I think decision-making, we picked the more difficult one first. Oh, yeah. Memory is more difficult. I think memory is a little more difficult. Decision-making seems easier. Decision-making, I think, we're already doing that in many ways. I think we have a much better understanding of certain aspects of decision-making because a lot of that relates to the pre-planning of speech and motor function. And so we have a better lens on that now. And a lot already is understood about the neural systems that serve decision-making. So predicting decisions before they happen, at least at the fraction of a second level, is already possible.

53:31And we have already some understanding of the areas of the brain that are responsible for that. So both decision support and decision prediction is kind of already in the near term roadmaps. Stock traders are going to have a field day with that. And by the way, I think that that has the potential actually to be influential in some of the more cutting edge foundational models that are being used and they're being developed in the area of artificial intelligence today. So interestingly, a lot of AI has been inspired by the architecture of the brain. Neural nets are where we've started. And some of these more abstract ways of decision making are likely to help with breakthroughs towards sort of the next stage of generative AI.

54:20That's why you're starting to see some convergence of the pure software players with folks like us who are interested, who are actually developing hardware that interacts with biology. What about decoding states of consciousness? So we've talked a couple of times now before we've done this episode, just so I can try to wrap my head around what you guys are doing. And one of the things we spoke about was coma. As right now, coma, I think, is very little. It's minimally understood. people just sort of say okay they're laying there and kind of like a half sleep but what can for instance putting a series of these brain computer interfaces on the brain of a coma patient potentially tell us about what's actually happening inside their mind as they're laying there yeah i mean this is something that we think is profound that we're actually actively working on and um it's due in part to work done over the last decade or decade and a half in the neurology and neuroscience community to try to understand coma.

55:21And, you know, this notion of consciousness is something very, very deep in philosophy and neuroscience. And, you know, a lot of time and effort has been spent trying to even understand what that means. But everybody has some intuition for what consciousness means and that coma represents a kind of disorder of consciousness or a lack of, or almost lack of consciousness. But there's a spectrum between coma and normal wakefulness that all of us here in the room experience and it's not exactly even a linear spectrum so you know we we're all familiar with sleep right and different sort of phases of wake different degrees of wakefulness and and people who have certain forms of brain injury, for example, severe trauma or debilitating strokes, they, especially in the early phases of their disease, and, you know, many of the listeners may be familiar with family members who've had very severe injury that results in a coma or a severe change in the state of consciousness.

56:32And for decades, this has been a really vexing problem, trying to understand, is the person who is currently unconscious or currently in a coma going to emerge from that state? And if they do, will they emerge as the person that we knew? And in the period in which they're not wakeful and able to communicate, are they in there, so to speak? right is that person in there are they are they thinking and a not just not able to communicate or are they not there at all in the way that we knew them and um it turns out that uh for some disorders of consciousness some people who are um you know seemingly not able to interact with the outside world their eyes are closed they are not moving or speaking um some of those people it's now known about maybe even 15 or more percent in some cases have the ability to think at least for some portion of the day and and even can modulate their neural activity in kind of the same ways that we do in order to to drive speech or to drive movement but they can't make that movement manifest in the outside world through vocalized speech or movement which are ways that we normally communicate and express our consciousness and that um if you think if you stop to think about it is it can be both troubling you know on a deep level but also represents kind of an opportunity which is that the same brain computer interface technology that we've been talking about to restore movement and people who we know to be totally lucid but paralyzed That same technology actually can serve as a bridge, both to help diagnose and provide prognostic information for whether the person who has this brain injury is likely to recover from it.

58:31And even in that period when they're not fully recovered, to provide a window into what's going on inside so that they can actually communicate in some ways with the outside. So there's a world you're saying where it might be possible to effectively talk with coma patients through BCIs. Not coma patients, because coma means that they don't have a level of consciousness that can provide that. But there is an intermediate set of states. They're called, for example, minimally conscious state, for example, or cognitive motor dissociation is the term that's often used for these states, which are in between coma and full wakefulness.

59:10on this sort of spectrum. And those patients, they look effectively like patients who are in a coma. And it's very difficult to distinguish them in some cases. And so we feel, and we're working on this, that brain-computer interface technology can provide a tool for distinguishing those patients from true coma. And yes, providing a way for them to communicate. That's unbelievable. And, you know, this has important predictive power in terms of, as Ben mentioned, determining the chances that they recover and become themselves again. Right now, you know, this sort of continuum of consciousness is most often diagnosed by nurses who are just trying to perceive whether there's any wakefulness or movement or an ability to respond.

1:00:02But that's in the context of, you know, loud hospitals and lots of patients who command their time. And so the error rates are extremely high right now. So being able to do this in a way that's much more definitive and also, which is, as Ben mentioned, gives people who are in there, who are able to modulate brain activity so they can imagine. You ask them a series of yes, no questions, and they can actually answer them by imagining making certain movements, allowing them to express themselves and communicate out to the world. I mean, it's just it's sort of an unimaginable thing to be in that state and to be conscious or to be at least aware of what's happening and to be completely uncommunicative because you can't control the muscles in your body.

1:00:46And so I think this this is a bridge that has the potential to be really important. Crazy. All right. I have two questions for you before we leave. The first is we kind of touched on it a couple of times, but what happens when people trust their brains to BCI companies? Let's say this, you know, 10 years or 30 years down the road becomes commonplace to have some sort of device in your brain. I know we're right now or right now you're mostly using this for disabled people or exclusively using it for folks who like need it to be able to function. Is there a worry that someday that technology, if it becomes too commonplace, can be used to hack into brains or to write signals in a way that, you know, you get a bad actor in there?

1:01:30Like there's this study, I think we're going to talk about it with Sally Adi, or she's already been on the show to talk about it. But there were like these rats that were able to hit this pleasure lever and that would send an electrical signal into their brain. And they would basically do that all day and not do anything else. So what do you think about the ability to write and should we be afraid of it? I feel like that button for rats is like Instagram, right? Look, there's definitely parallels in the human experience today, no doubt. Yeah, I mean, these are incredibly important questions. The issue of neural data privacy, neural data security, you know, there's nothing more inherent to who we are than our brain activity.

1:02:12I'd make a few points about this, and it's obviously an evolving space. one is we're a healthcare company. We're developing medical technology in the context of the FDA regulatory regime. Yeah, I'm not worried about your device right now being used to hack brains. But I think these concepts are being considered now. It's early, I think. We're developing a tool for paralyzed people to live higher quality of life. But over time, I think these issues will certainly emerge. And the FDA has actually taken a very proactive role in helping define the regulatory regime, not just for today, but for tomorrow as well.

1:02:49They've helped create something called a collaborative community, which they've done in a few different areas of emerging medical technology. And it's a way to convene a lot of the different stakeholders into one place to map out clinical practice guidelines, reimbursement, as well as some of the ethical considerations, which are different depending on the technology. So this is academics. These are the patient advocates. This is industry. This is clinicians. These are hospital administrators. These are payers like insurance companies. And so one of the work streams of this collaborative community, it's called the Implantable Brain Computer Interface Collaborative Community.

1:03:33It's a little bit of a mouthful, but is specifically focused on data privacy, data security, and ethical considerations. And so I think that's an incredibly powerful sort of forum in which to start mapping out what this looks like in coming years. I mean, let me take that in a different direction, just because, I mean, as you can tell, as futuristic as brain and computer interfaces are, we're pretty practical-minded as a company, really, really trying to bring this technology into the real world to impact people and become part of the standard of care. But having said that, you know, I think we're profoundly influenced by the science fiction of our childhood and of modern times.

1:04:19And there's a long track record of, you know, the science fiction of today helping to influence the science reality of tomorrow. So we take these, we take our responsibility in this regard very seriously. And we take these thought experiments very seriously. and as Michael mentioned I think we and others in the space are trying to ensure that this all develops in as responsible a way as possible understanding that it can be hard to predict what happens and it can certainly be hard to legislate around you know all future eventualities but we definitely have our eye on it okay let me end with this on the theme of science fiction We talked today a lot about transposing the brain into compute, taking thoughts from the brain and bringing it into technology.

1:05:12What about the other way around? So I'm curious if you think there is a way for AI in some way to merge with the human brain. And then I guess as a corollary to that, knowing what you know about human consciousness, do you think it's possible at all for AI to achieve consciousness or self-awareness? Yes. Say more. Yes, you should have us back on the show for another episode on whole brain interfaces merging with artificial intelligence and AI consciousness. I mean, that's a whole another couple of hours. But you're a neurosurgeon. you believe AI can achieve consciousness? I do, yeah. How? I mean, I don't think that, to me, it's not even such a, I don't even see that as such a, I don't even see that as such a difficult or troubling question.

1:06:07Okay. So we will have to do another hour then, is what you're saying. And then what about this idea of AI and human brains merging? Any thoughts on that? It's already happening, right? I mean, in some ways, that's exactly what we're developing. And we see the brain-computer interfaces today, as you alluded to and as Michael mentioned, as kind of like the, in some ways, the foundational layer of, you know, a merger between the brain and artificial intelligence. Right now, it has some very practical manifestations, which is effectively to become a different kind of user interface. You know, as Michael mentioned, we have ways today that we've become accustomed to of how we interact with the digital world.

1:06:51And it's usually with voice or hand control. But the technology that we're building is to enable direct brain to digital world control. And right now, actually, what we're doing almost of necessity because so much technology is just built around voice and gestural and hand motor control is kind of a two-step bridge between neural intent and a conversion to what would be, for example, typing on a keyboard or moving a cursor or speaking some commands to a computer. But that's just kind of an artifact of the way the user interfaces of today are built. We already know, actually, that the latency between your brain and your hand and the ability to think something and type it is around 25 milliseconds.

1:07:50So that actually puts a biological hard limit on how fast you can interact with the digital world, even though you're thinking faster than that, right? In a brain-computer interface, the latency of the system is right now in the single-digit milliseconds will be even faster than that. That's why Nolan said he's kind of like a superhuman ability when he plays videos. Exactly, right. So many participants in these clinical trials have described it in similar terms, kind of like the neural interfaces predicting what they're thinking. This gets to your question earlier about decision making and where and when is the decision made and when can a neural interface infer that or predict it.

1:08:32But I'm using this specifically to just point you in the direction of what the user interface of the future, where brain-computer interfaces are pervasive, looks like. It looks like not a keyboard or voice activation or gestural control. It looks like something that almost is predicting or intuiting what you're thinking. And it's actually counterintuitive to how we interact with the world because we're built and wired and have an intuition around actually interactions with the world that are built around this 25 or so millisecond latency. Anything that happens faster than that, you don't realize that it has that latency.

1:09:13And so when you see it happen faster, it almost seems like magic. But that's what an inherent brain-computer interface, user interface looks like. That's happening. And that's just the first step in what, you know, a kind of a merger with artificial intelligence looks like. Okay, Michael, let's give you the last word. I want you to just give us like a realistic timeline of like what the next couple of years are going to look like in this technology and then what size of a business that could be if it works according to plan. Yeah, and just to – I'll answer both those questions. Thank you. But just to follow up on what Ben was saying, just in layman's terms, we already are augmented by AI.

1:09:48It's just slow. We have to type. And I think that there will be an ability to access information much more quickly and also much more intuitively with context, which is part of the reason that companies like Meta and Google or developing wearables, context is going to really improve the functionality of these systems and how we use them. And I think that that's going to be part of brain-computer interfaces as well. In terms of timelines and market size, I think that there is growing recognition that this is going to be a big industry. Morgan Stanley wrote a report last year that estimated a$400 billion TAM.

1:10:24And that will build first in some of the medical applications that we described. We expect within five years there to be precision system on the market and maybe one or two others that are making a big clinical impact for people who are severely paralyzed and then expanding from the sort of$2.5 billion a year market that the severe paralysis represents to something that's 10 to 15 times that as the applications for the technology become wider. I think what we have at Precision that's unique within the context of brain-computer interfaces is the ability to commercialize a temporary version of the system.

1:11:08Ben mentioned that we have our first FDA clearance, which is a tremendous milestone for Precision, but it's also just a sign of the progress of this industry towards real commercial and clinical impact. That is not instead of our permanent implant. That is in addition to and parallel to our permanent implant. The constraint to a temporary implant is that it can be implanted up to 30 days, but there are a number of applications for a 30-day implant, some of which been described in the disorders of consciousness, which we think are actually going to create businesses that are several hundred million dollars in annual revenue and which do a tremendous amount of good in terms of human health.

1:11:51all right well folks if you stayed till the end i promised you we were going to get into some weird and good stuff and i and i think that we delivered so thank you for staying with us all the way until this late moment in the interview i called brain computer interfaces the uh this that i said that 2025 was going to be the year of brain computer interfaces and i think the conversation that you just heard really shows that it is unfolding exactly that way so michael and ben so great to see you. It's always fun to talk. And I hope you do come back and give us that extra hour on whole brain mapping and whether AI and the human brain can merge.

1:12:26Sounds good. All right. Thank you so much for being here. And thank you everybody for listening and for watching. We'll see you next time on Big Technology Podcast.

1:12:48You