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Poppy Crum on Huberman Lab: How AI Reshapes Learning

Crum explains cortical plasticity reshapes with every tool you use; AI sensor feedback and active encoding accelerate skill gain without losing cognitive depth.

Andrew HubermanhostPoppy Crumguest
Sep 29, 20252h 35mWatch on YouTube ↗

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  1. 0:00 – 2:22

    Poppy Crum

    1. AH

      Welcome to the Huberman Lab Podcast, where we discuss science and science-based tools for everyday life. (instrumental music plays) I'm Andrew Huberman, and I'm a professor of neurobiology and ophthalmology at Stanford School of Medicine. My guest today is Dr. Poppy Crum. Dr. Poppy Crum is a neuroscientist, a professor at Stanford, and the former chief scientist at Dolby Laboratories. Her work focuses on how technology can accelerate neuroplasticity and learning and generally enrich our life experience. You've no doubt heard about and perhaps use wearables and sleep technologies that can monitor your sleep, tell you how much slow wave sleep you're getting, how much REM sleep, and technologies that can control the temperature of your sleep environment and your room environment. Well, you can soon expect wearables and hearable technologies to be part of your life. Hearable technologies are, as the name suggests, technologies that can hear your voice and the voice of other people and deduce what is going to be best for your immediate health and your states of mind. Believe it or not, these technologies will understand your brain states, your goals, and it will make changes to your home and working and other environments so that you can focus better, relax more thoroughly, and connect with other people on a deeper level. As Poppy explains, all of this might seem kind of space age and maybe even a little aversive or scary now, but she explains how it will vastly improve life for both kids and adults, and indeed increase human-human empathy. During today's episode, you'll realize that Poppy is a true out of the box thinker and scientist. She has a really unique story. She discovered she has perfect pitch at a young age. She explains what that is and how that shaped her worldview and her work. Poppy also graciously built a zero-cost step-by-step protocol for all of you. It allows you to build a custom AI tool to improve at any skill you want and to build better health protocols and routines. I should point out that you don't need to know how to program in order to use this tool that she's built. Anyone can use it, and as you'll see, it's extremely useful. We provide a link to it in the show note captions. Today's conversation is unlike any that we've previously had on the podcast. It's a true glimpse into the future, and it also points you to new tools that you can use now to improve your life. Before we begin, I'd like to emphasize that this podcast is separate from my teaching and research roles at Stanford. It is however part of my desire and effort to bring zero-cost-to-consumer information about science and science-related tools to the general public. In keeping with that theme, today's episode does include sponsors. And now for my conversation with Dr. Poppy Crum.

  2. 2:22 – 8:06

    Neuroplasticity & Limits; Homunculus

    1. AH

      Dr. Poppy Crum, welcome.

    2. PC

      Thanks, Andy. It's great to be here.

    3. AH

      Great to see you again. We should let people know now, we were graduate students together. But that's not why you're here. You're here because you do incredibly original work, you've worked in so many different domains of technology, neuroscience, et cetera. Today, I want to talk about a lot of things, but I want to start off by talking about neuroplasticity, this incredible ability of our nervous systems to change in response to experience. I know how I think about neuroplasticity, but I want to know how you think about neuroplasticity. In particular, I want to know, do you think our brains are much more plastic than most of us believe? Like, can we change much more than we think and we just haven't accessed the ways to do that? Or do you think that our brains are pretty fixed, and in order to make progress as a species, we're going to have to, I don't know, create robots or something to- to do the work that we're not able to do because our brains are fixed? Let's start off by just getting your take on what neuroplasticity is and what you think the limits on it are.

    4. PC

      I do think we're much more plastic than- an- and- than we talk about or we realize in our daily lives. And- and just to your point about creating robots, the more we create robots, there's neuroplasticity that comes with- comes with using robots as humans-

    5. AH

      Mm-hmm.

    6. PC

      ... when we use them in partnerships or as, you know, tools to accelerate our capabilities. So neuroplasticity, the way that the... where I resonate with it a lot is, uh, trying to understand... And- and this is what I've done a lot of in my career, is thinking about building and developing technologies, but with an understanding of how they shape our brain. Everything we engage with in our daily lives, whether it's the statistics of our environments and our context or the technologies we use on a daily basis, are shaping our brains in ways, i- through neuroplasticity. Um, some more than others. Some, we know as we age, are very dependent on how attentive and engaged we are as opposed to passively just consuming and- and mode- and- and changing. But we are in a place where everyone, I believe, needs to be thinking more about how the technologies they're using, especially in the age of AI and immersive technologies, how they are shaping, you know, or architecting our brains as we move forward. You go to any Neuroscience 101 medical school textbook, and there's something... You'll- you'll see a few pages on something called the homunculus. Now, what is the homunculus? It's a data representation, but it- it'll be this sort of funny-looking creature when you see it. But that picture of this sort of distorted human that you're looking at is really just, um, a data representation of how many cells in your brain are helping, are re- coding and representing information for your sense of touch, right? And th- that- that image though, and this is where things get kind of funny, that image comes from Wilder Penfield back in the '40s. He recorded the som- he would... Somatosensory, uh, uh, i- e- cells of, uh, of patients just before they were to have, you know, surgery for epilepsy and such. And, you know, since we don't have pain receptors in our cortex, he could have this awake human and be able to touch different parts of their brain and ask them, you know, to report what sensation they felt on their bodies. And so he mapped that part of their- their cortex, and then that- that's how we ended up with the homunculus. And you'll see, you know, it'll have bigger lips, it'll have, you know, smaller parts of your back and the areas where you just don't have the same sensitivities.Well, fast-forward to today. When you look at that homunculus, one of the things I always will ask people to think about is, you know, wh- what's wrong with this image? You know, this is an image from 1940 that is still in every textbook. And, you know, a- any Stanford student will look at it and they'll immediately say, "Well, the thumbs should be bigger 'cause we do this all day long. And I've got more sensitivity in my fingers 'cause I'm always typing on my mobile device," which is absolutely true. Or, maybe they'll say something like, "Well, the, the ankles are the same size and, and we drive cars now a lot more than we did in the '40s. Or maybe if I live different part of the world, I drive on one side versus the other. And in, in a few years, you know, we probably won't be driving and those resources get optimized elsewhere." So, what the homunculus is, is it's a representation of how our brain has allocated resources to help us be successful, and those resources are the limited cells we have that support whatever we need to flourish in our world. And the, the beauty of that is, when you develop expertise, you develop more support, more resources go to helping you do that thing, but they also get more specific. They develop more specificity so that, you know, I might have suddenly a lot more cells in my brain devoted to helping me, y- you know, I'm a violinist, and my, you know, well, my left hand, my right hemisphere, I'm, on my somatosensory cortex, I'm gonna have a lot more cells that are helping me, you know, feel my fingers and, and the, the tips of everything so that I can, you know, be fluid and, and more virtuosic, but that means I have more cells, but they're more specified. They're giving me more sensitivity, they're giving me more data that's differentiated. And that's what my brain needs and that's what my brain's responding to. And so, when we think about that, you know, my practice as a musician versus my practice playing video games, all of these things influence our brain, um, in, and influence our, our plasticity. Now,

  3. 8:06 – 13:12

    Technology; Environment & Hearing Thresholds; Absolute Pitch

    1. PC

      where things get kind of interesting to me and sort of my obsession on that side is, every time we engage with the technology, it's going to shape our brain, right? It's both, you know, our environments, but our environments are changing. Those are shaping who we are. You know, I think you can look at, um, people's hearing thresholds and predict what city they live in. The noi-

    2. AH

      Really?

    3. PC

      (laughs) Absolutely. (laughs) Yes.

    4. AH

      Can you, uh, just briefly explain, explain-

    5. PC

      Why that would be?

    6. AH

      ... hearing thresholds and why that would be? I mean, I was visiting the City of Chicago a couple years ago. Beautiful city.

    7. PC

      Yeah.

    8. AH

      A- amazing food. Love the people. Very loud city.

    9. PC

      Mm-hmm.

    10. AH

      Wide downtown streets. Not a ton of trees compared to what I'm used to. And I was like, "Wow, it's really loud here." And I grew up in the suburbs, got out as quickly as I could.

    11. PC

      Yeah.

    12. AH

      Don't like the suburbs. Sorry. Suburb dwellers-

    13. PC

      (laughs)

    14. AH

      ... not for me. Um, (laughs) I like th- the wilderness and I like cities. Um, but you're telling me that you can actually predict people's hearing thresholds for loudness simply based on where they were raised or where they currently live?

    15. PC

      In part it can be both, right? Because cities have sonic imprints types of noise, things that are very, you know, very loud cities, but also w- what's creating that noise? Right? That's often unique, the, the, the inputs, the types of vehicles, the types of density, uh, people, or, uh, and, and, um, cons- you know, even the construction in those environments. It is changing what noise exists. That's shaping, you know, people's hearing thresholds. At the lowest level, it's also shaping their sensitivities. If you're used to hearing, you know, certain animals in your environment and they come with, you know ... Uh, y- you should be heightened to a certain response in that, you're going to develop increased sensitivity to that, right? Whereas if it's really abnormal, you know, to ... I hear chickens. I have a neighbor who has chickens in the city, but-

    16. AH

      Roosters too?

    17. PC

      Yes. Yes. (laughs)

    18. AH

      Okay.

    19. PC

      (laughs) In San Francisco.

    20. AH

      I grew up near a rooster.

    21. PC

      There you go. (laughs)

    22. AH

      I c- I can still hear that rooster.

    23. PC

      Yeah.

    24. AH

      Those, those sounds are embedded deeply in my mind.

    25. PC

      There's the semantic context and then just the sort of spectrum, right? And the intensity of that spectrum, and meaning, when I say spectrum, I mean the different frequency amplitudes and, and what that shaping's like, you know?

    26. AH

      High pitch, low pitch. This kind of thing.

    27. PC

      Yeah. Yeah. And that affects how your neural system is, is changing, even at the lowest level of what, you know ... What it's, your, your ear is, your brain, your cochlear is getting exposed to-

    28. AH

      Mm-hmm.

    29. PC

      ... but then also where, you know, so that would be the lower level, you know, what, what sort of noise damage might exist, what exposures, but then also then there's the amplification of, you know, coming from your higher level br- areas that are helping you know that these, uh, frequencies are more important in your context, in your environment. There's a, a funny, like this is kind of funny. Um, there was a film called, I think it's The Sound of Silence and it star- I, I love Peter Sarsgaard. He was one of the, the actors in it. And, um, it was sort of meant to be a bit fantastical, or is that a word? Is that the right word? (laughs)

    30. AH

      (laughs)

  4. 13:12 – 15:33

    Sponsors: David & Helix Sleep

    1. AH

      I'd like to take a quick break and acknowledge one of our sponsors, David. David makes a protein bar unlike any other. It has 28 grams of protein, only 150 calories, and zero grams of sugar. That's right, 28 grams of protein, and 75% of its calories come from protein. This is 50% higher than the next-closest protein bar. David protein bars also taste amazing. Even the texture is amazing. My favorite bar is the chocolate chip cookie dough, but then again, I also like the new chocolate peanut butter flavor and the chocolate brownie flavor. Basically, I like all the flavors a lot. They're all incredibly delicious. In fact, the toughest challenge is knowing which ones to eat on which days and how many times per day. I limit myself to two per day, but I absolutely love them. With David, I'm able to get 28 grams of protein in the calories of a snack, which makes it easy to hit my protein goals of one gram of protein per pound of body weight per day, and it allows me to do so without ingesting too many calories. I'll eat a David protein bar most afternoons as a snack, and I always keep one with me when I'm out of the house or traveling. They're incredibly delicious, and given that they have 28 grams of protein, they're really satisfying for having just 150 calories. If you'd like to try David, you can go to davidprotein.com/huberman. Again, that's davidprotein.com/huberman. Today's episode is also brought to us by Helix Sleep. Helix Sleep makes mattresses and pillows that are customized to your unique sleep needs. Now, I've spoken many times before on this and other podcasts about the fact that getting a great night's sleep is the foundation of mental health, physical health, and performance. Now, the mattress you sleep on makes a huge difference in the quality of sleep that you get each night. How soft it is or how firm it is all play into your comfort and need to be tailored to your unique sleep needs. If you go to the Helix website, you can take a brief two-minute quiz, and it will ask you questions such as, "Do you sleep on your back, your side, or your stomach? Do you tend to run hot or cold during the night?" Things of that sort. Maybe you know the answers to those questions, maybe you don't. Either way, Helix will match you to the ideal mattress for you. For me, that turned out to be the Dusk mattress. I started sleeping on a Dusk mattress about three and a half years ago, and it's been far and away the best sleep that I've ever had. If you'd like to try Helix Sleep, you can go to helixsleep.com/huberman, take that two-minute sleep quiz, and Helix will match you to a mattress that's customized to you. Right now, Helix is giving up to 27% off all mattress orders. Again, that's helixsleep.com/huberman to get up to 27% off.

  5. 15:33 – 23:06

    Texting, Homunculus, Mapping & Brain; Smartphones

    1. AH

      Okay, so our brains are customized to our experience.

    2. PC

      Yeah.

    3. AH

      Especially our childhood experience, but also our adult experience.

    4. PC

      Yes.

    5. AH

      You mentioned the homunculus.

    6. PC

      Yes.

    7. AH

      The s- uh, representation of the body surface, and you said something that I just have to pick up on and ask some questions about, which is that, um, this hypothetical Stanford student, could be any student anywhere-

    8. PC

      Mm-hmm.

    9. AH

      ... says, w- "Wait, nowadays, uh, we spend a lot of time writing with our thumbs and thinking as we write with our thumbs-"

    10. PC

      Mm-hmm.

    11. AH

      "... and emoting, right? I mean, when we text with our thumbs, we're sometimes involved in an emotional exchange."

    12. PC

      Yeah.

    13. AH

      My question is this. The last 15 years or so have represented an unprecedented time of n- new technology integration, right? I mean, the smartphone.

    14. PC

      Mm-hmm.

    15. AH

      Um, texting. And when I text, I realized that I'm hearing a voice in my head as I text, which is my voice, because if I'm texting outward, I'm sending a text. But then, I'm also internalizing the voice of the person writing to me if I know them.

    16. PC

      Mm-hmm.

    17. AH

      But it's coming through filtered by my brain, right? So it's like, I'm not trying to micro-dissect something here for the sake of micro-dissection, but the conversation that we have by text, it's all happening in our own head. But there are two or more players, group text was too complicated to even consider right now, but what is that transformation really about? Previously, I would write you a letter, I would send you a letter, or I'd write you an email, I'd send you an email, and so the process was really slowed. Now, you can be in a conversation with somebody that's really fast back and forth.

    18. PC

      Hmm.

    19. AH

      Right? Some people can type fast. You can email fast, but nothing like what you can do with text, right? I can even know when you're thinking because it's dot, dot, dot, or you're writing, right? And I'm, I, and so, i- is it possible that we've now allocated an entire region of the homunculus, or of some other regional cortex-

    20. PC

      Yeah.

    21. AH

      ... brain to conversation that prior to 2010 or so, the brain just was not involved in conversations of any sort? In other words, we now have the integration of writing with thumbs, that's new-

    22. PC

      Mm-hmm.

    23. AH

      ... hearing our own voice, hearing the hypothetical voice of the other person at the other end, and doing that all at rapid speed. Are we talking about, like, a new brain area, or are we talking about using old brain areas and just trying to find and push the overlap in the Venn diagram? Because I remember all of this happening very quickly and very seamlessly. I remember, like, texting showed up, and it was like-All right, well, it's a little slow, a little clunky. Pretty soon it was autofill. Pretty soon it was learning us. Now we can do voice recognition and it's-

    24. PC

      Yeah.

    25. AH

      ... it's, it, you know, people pick this up very fast. So the question is, are we taking old brain areas and combining them in new ways? Or is it possible that we're actually changing the way that our brain works fundamentally in order to be able to carry out something as, what seems to be nowadays trivial, but as, uh, as basic to everyday life as texting?

    26. PC

      Mm.

    27. AH

      What's going on in our brain?

    28. PC

      W- we aren't developing new resources. We've got the same cells that our... or, I mean, there's neurogenesis, of course. But, um, it's how those are getting allocated and, uh, you know, just one, one quick comment from what we said before when we talked about the homunculus. The homunculus is an example of a map in the brain, a cortical map. And maps are important in the brain because they, you know, allow cells that need to interact to give a specificity, to make us fast, to have, you know, tight reaction times and things, you know, 'cause you got shorter distance (laughs) and, you know, things that belong together. And also, there's a lot of motility in terms of, you know, what those cells respond to, potentially dependent on our input. So the homunculus might be one map, but there are maps all over our brain, and those maps still have a lot of cross-input. So what you're talking about is, are you having areas where we didn't use to allocate and differentiate in, you know, w- the specificity of what those cells were doing that are now quite related to the different ways my brain is having to interpret a text message. And the subtly and the nuance of that, that actually now I'm, I get faster at, I have faster reaction times, I also have faster interpretations. So am I allocating cells that used to do something else to allow me to have it? Probably. But I'm also building, you know, where, like, think about me as a multi-sensory object that has, you know, uh, I have to integrate information across sight, sound, smell, to form a holistic, uh, you know, object experience. That same sort of, you know, integration and, and pattern is happening n- now when we communicate in ways that it didn't use to. So what does that mean? It means there's a lot more repeatability, a lot faster pattern matching, a lot more integration that is allowing us to go faster.

    29. AH

      I completely agree. I feel like there's an entire generation of people who grew up with smartphones-

    30. PC

      Mm.

  6. 23:06 – 30:32

    Technology, Data Compression, Communication, Smartphones & Acronyms

    1. AH

      So, I guess the question is, do you think that the technology is good, bad, neutral, or are you agnostic as to how the technologies are shaping our brain?

    2. PC

      It goes in lots of different directions. Um, o- one thing I did wanna say though with w- with smartphones specifically and sort of everything, you know, in, in audio, you know, the, our ability to have, you know, carry, uh, our lifetime of music w- and, and content with us has been because of, you know, huge advances in the last 25, 30 years, and maybe, maybe slightly more, around, um, compression algorithms that have enabled us to have really effective what we call perceptual compression, lossy perceptual algorithms, and things like MP3 and, and, you know, my, my past work with companies like Dolby. But whenever you're talking about what's the goal of content, uh, compression algorithms, it's to translate the entirety of the experience, the entirety of the signal in, you know, with, with a lot of the information removed, right? But in intelligent ways. When you look at the way someone is communicating with acronyms and the shorthand that the next generations use to communicate, it is such a rich communication, even though they might just say, "LOL." I mean, (laughs) it's like-

    3. AH

      (laughs)

    4. PC

      ... or they might, y- you know, it's, it's-It's actually a lossy compression that's triggering a huge cognitive experience, right?

    5. AH

      Can you explain lossy for people who might not be familiar with it?

    6. PC

      Lossy means that in your encoding and decoding of that information, there is actually information that's lost when you decode it. But hopefully, that information is not impacting the perceptual experience. Imagine I have, you know, a song and I want to represent that song. I could take out, to make my file smaller, I could take out every other, you know, every 500 milliseconds of that, and it would sound really horrible, right? Or, I could be a lot more intelligent and instead basically, you know, if you look at early models like MP3, they're, they're, they're kind of like computational models of the brain. They stop, you know, they might stop at, like, the auditory nerve, but they're trying to put a model of how our brain would deal with sound, what we would hear, what we wouldn't. If this sound's present and, and it's present at the same time as this sound, then this sound wouldn't be heard, but this sound would be, so we don't need to spend any of our, our bits coding this sound. Instead, we just need to code this one. And so, it becomes an intelligent way for the model and the algorithm of deciding what information needs to be represented and what doesn't to create the same, you know, the best ex- perceptual experience with which, "perceptual" meaning what we get to, you know, take home. I think one of the things that's important then, why I think it- it- whenever I had- used to have to teach some of, you know, what it means to represent a rich experience with minimal data, you think with minimal information, um, some of the acronyms that exist in, in, like, mobile texting, it- they've taken on a very rich life, in-

    7. AH

      LOL, OMG.

    8. PC

      ... internal life. Yeah, well, those are simplistic ones.

    9. AH

      Yeah.

    10. PC

      But I think people can have communication now that we can't understand entirely. (laughs)

    11. AH

      Is this because you have a 10-year-old daughter? Does she-

    12. PC

      Yes.

    13. AH

      ... does she have communication by acronym that to you is cryptic?

    14. PC

      Sometimes, but I, I have to figure it out then, but yes.

    15. AH

      Mm-hmm.

    16. PC

      But, but the point is, it- that is an example of a lossy compression algorithm that actually has a much richer perceptual experience, right? And it often needs context, but it's still, you know, you're using few bits of information to try to represent a much richer feeling and a much richer state, right? And, uh, you know, if you look at different people, they're going to have, you know, bigger physiological experience dependent on, you know, how, how they've grown up with that kind of context.

    17. AH

      It sounds to me-

    18. PC

      Yeah.

    19. AH

      ... uh, I, I don't want to, um, project here, but it sounds to me like you see the great opportunity of the- of data compression. Like, let's just stay with the use of acronyms in texting. That's a-

    20. PC

      Okay.

    21. AH

      ... that's a vast data compression compared to the kind of speech and direct exchange that people, uh, engaged in 30 years ago. So there's less data being exchanged, um, but the experience is just as rich, if not more rich, is what you're saying, which implies to me that you look at it as generally neutral to, to benevolent.

    22. PC

      Yeah.

    23. AH

      Like, it's good.

    24. PC

      It's just different.

    25. AH

      I'm coming up on 50 in a couple months, and as opposed to somebody saying, "Well, you know, when I was younger, we'd write our boyfriend or girlfriend a letter. Uh, you know, I would, um, I would actually write out a birthday card. I would, um, go ... You'd have a face-to-face conversation," and you've got this younger generation that are saying, "Yeah, whatever." You know, this is like what we heard about, "I used to trudge to school in the snow," kind of thing.

    26. PC

      Yeah.

    27. AH

      It's like, "Well, we have heated school buses now, and we've got, uh, uh, you know, driverless cars." So, um, I think this is important and useful for people of all ages to hear that the richness of an experience can be maintained even though the- there are data or some elements of the exchange are being completely removed.

    28. PC

      Absolutely, but it's maintained because of the neural connections that are built in those individuals, right, and that generation.

    29. AH

      I, I always think of, okay, and the nervous system likes to code, um, along a continuum, but, like, yum, yuck, or meh. Like, do you think that, that, that, uh, technology is kind of neutral? Like, yeah, you lose some things, you gain some things. Or, do you think, like, this is bad? These days we hear a lot of AI fear. We'll talk about that. Um, or you hear also people who are super excited about what AI can do, what smartphones can do. I mean, some people, uh, like my sister and her daughter love smartphones because they can communicate. It gives a feeling of safety at a distance. Like, quick communications are easier. It's hard to sit down and write, write a letter. Um, she's going off to college soon, so the question is like, "How often will you be in touch?" It raises expectations about frequency, but it reduce it- of contact, but it reduces expectations of depth.

    30. PC

      Mm.

  7. 30:32 – 40:51

    Sensory Data & Bayesian Priors; Video Games & Closed Loop Training

    1. PC

      any case, I am a h- huge advocate for integration of technology, but it's, for me, the world is data. And, and, I, I do think that way. It's, you know, and, and, I, I look at what, the way my daughter behaves, I'm like, "Okay, well, what data's coming in?" (laughs) And it's like, you know? And, and why did she, you know, respond that way? And, you know, there's this, an example I, I can give, but, you know, you think, we were talking about neuroplasticity, it's like we are the creatures of sort of three things. One is, uh, you know, our sensory systems, how they've evolved, and be it tr- by, you know, the intrinsic noise that is, you know, cau- degrading our sensory receptors, or the extern ... straight, you know, I ... my brain is going to have access to, uh, about the same amount of information as someone with hearing loss if I'm in a very noisy environment. And so, suddenly you've induced, you know, you've compromised the data I have access to. And then, also our sort of experientially esp- established priors, right? Our priors being, if you think about the brain as sort of a Bayesian model, you-th-things aren't always deterministic for us like they are for some creatures. Our brain's having to take data and make decisions about it, and respond to it.

    2. AH

      Which is Bayesian. We should just explain for people.

    3. PC

      Yes.

    4. AH

      Deterministic would be input A leads to output B.

    5. PC

      Yeah.

    6. AH

      Bayesian is, it depends on the statistics of what's happening externally and internally.

    7. PC

      Yeah.

    8. AH

      These are probabilistic models.

    9. PC

      Yes.

    10. AH

      Like, there's a likelihood of A becoming B, or there's a likelihood of A driving B, but there's also a probability that A will drive C, D, or F.

    11. PC

      Absolutely. And, you know, for e- and we should get into, I mean, some of the things that make us the most effective in our environments and just in interacting in the world is how f-fast and effective we are with dealing with those probabilistic, you know, situations. Those things where your brain ... It's, it's like probabilistic inference is a great indicator of success in an environment. And, you know, be it a work environment, be it just, you know, walking down the street. And, um, how, that's how do we deal with this? Like, data that doesn't just tell us we have to go right or left, but there's a lot of different inputs, and it's our sort of situational intelligence in the world. And, there, you know, we can break that down into a lot of different ways. In any case, we are the products of our, you know, our sensory systems, our experi- our priors, which are the statistics that, and data we've had up until that moment that our brain's using to weight how it's going to behave and the decisions it makes, but also then our expectations, the context of that, you know, that have shaped where we are.

    12. AH

      Mm-hmm.

    13. PC

      And so, there's this funny story. Like, my daughter, when she was two and a half, we're in the planetarium at the Smithsonian, and we're watching, I think one a- typical film you might watch in a planetarium. We started in LA, zoom out on our way to the sun and we pass that sort of, you know, quintessential NASA image of the earth. And, it's totally dark and silent, and my daughter, as loud as she possibly could, yells, "Minions." And, I'm like, "What?" (laughs) "What's going on?" (laughs) You know?

    14. AH

      (laughs)

    15. PC

      And I'm like, "Oh, yes. Of course." Her experiencedly established prior of that image is coming from the Universal logo. (laughs) And, you know, she never ... You know, that says, "Universal." It's like-

    16. AH

      Yeah. No, I love it.

    17. PC

      It was totally valid. But it was this very, uh, you know, honest and true part of what it is to be human. Like, each of us is experiencing very different, you know, ex- having d- very different experiences of the same physical information, and we need to recognize that. But, it is driven by our exposures, and our priors, and our sensory systems, it's sort of that trifecta, and our expectations of the moment. And, once you unpack that, you really start to rep-understand and, and appreciate the influence of technology. Now, I am a huge advocate for technology improving us as humans, but also improving the data we have to make better decisions, and the sort of insights that drive us. At the same time, I think sometimes we're penny wise, pound foolish with how we use technology. And, the quick things that make us faster can also make us dumber, and take away our cognitive capabilities. And, you know, where you'll end up with those that are using the technologies might be to, to, s- you know, to, to write papers all the time, or maybe, well, and we, we, we can talk about that more, are putting themselves in a place where they are going to be compromised trying to do anything without that technology, and also in terms of their, uh, their learning of that data, that information. And so, you start even ending up with bigger differentiations in cognitive capabilities by whether y- how you use a tool, a, a, a technology tool to make you better or faster or not. One of my sort of things I've always done is teach at Stanford that does, we also have that in common. (laughs) And, um-

    18. AH

      Mm-hmm. I need to sit in on one of your lectures.

    19. PC

      And, you know, but my, my class there has been, is called Neuroplasticity and Video Gaming. And, um, I'm a neurophysiologist, but I'm, uh, I'm really a technologist. I like buildings. I like, you know, innovation across many domains. And, while that class says video gaming, it's really more a, uh, well, video games are powerful in the sense that there's this sort of closed loop environment. You give feedback, you get data on your performance, but you get to control that and know what you randomize, how you build. And, what our aim is in that class is to build technology and games with an understanding of the neural circuits you're impacting, and how you want to, what you want to train. I'll have, um, students that are musicians, I'll have students that are computer scientists, I'll have students that are, you know, some of Stanford's top athletes. I've had a number of their top athletes go through my, my course. And, um, it's always focused on, okay, there's some aspect of human performance I want to dissect and I want to really amplify the sensitivity or the, the access to that type of learning in a closed loop way. Just for anyone that isn't familiar with the role, uh, the history of gaming in the neuroscience space, you know, there's been some great papers in the past. Um, take a gamer versus a non-gamer, just to start with, someone self-identified. A, a typical gamer, um, actually has what we would call, um, more sensitive c- and this is your domain, so you can counter me on this anytime. But, you know, s- contrast sensitivity functions.

    20. AH

      Mm-hmm.

    21. PC

      And like, a contrast sensitivity function is, um, you know, ability to see, uh, edges and differentiation, um, in a visual landscape. Okay? They can see ...... uh, faster and, uh, you know, more, they're more sensitive to that sort of differentiation, so, than someone who says, "I'm not a video game player," or, or self-identifies that way.

    22. AH

      Because they've trained it.

    23. PC

      They, they've trained it.

    24. AH

      Right? Like, like a first person shooter game-

    25. PC

      Yeah.

    26. AH

      ... which I've played occasionally-

    27. PC

      Yeah.

    28. AH

      ... in an arcade or something like that.

    29. PC

      Yeah.

    30. AH

      Uh, I didn't play a lot of video games growing up. I don't, uh, these days e- either. But, um, yeah, a lot of it is based on contrast sensitivity, knowing are-

  8. 40:51 – 46:17

    Improve Swim Stroke, Analytics & Enhancing Performance, Digital Twin

    1. PC

    2. AH

      I'd love for you to, uh, share the story about your daughter, um, improving her swimming stroke, right? 'Cause she's not a D1 athlete yet. Maybe she will be someday, but she's a swimmer, right?

    3. PC

      Yes.

    4. AH

      And in the past, if you wanted to get better at swimming, you needed a swimming coach, and if you wanted to get really good at swimming, you'd have to find a really good swimming coach and you'd have to work with them repeatedly. Uh, you took a slightly different direction that really points to just how beneficial and inexpensive this technology can potentially be-

    5. PC

      Yeah.

    6. AH

      ... or relatively inexpensive.

    7. PC

      Well, uh, first I'll say this. Number one is having good swimming coaches. (laughs)

    8. AH

      Okay. (laughs) Sure, I'm not trying to do away-

    9. PC

      Parents-

    10. AH

      ... with swimming coaches.

    11. PC

      Parents, parents who are, uh, data centric and, and really like building technologies are sometimes maybe m- can be red herring distractions, but (laughs) hopefully not.

    12. AH

      Okay. All right. Well, uh, yes.

    13. PC

      That's one of them.

    14. AH

      Yeah.

    15. PC

      But, um-

    16. AH

      Let, let's keep the swimming coaches, uh, ha- happy.

    17. PC

      Yeah, so for example, like you, you, you go and train with the lead athletes, and, and if you go to a lot of, um, swimming camps where you're, you know, or c- training programs, it's always about under, you know, work with cameras and, and, you know, what, what they're, they're recording you. They're, you know, assessing your strokes. But the point is what, I mean, I, you can use, and I did this, uh, you know, knowing the things that the coaches, you know, or frankly, you can go online and learn some of those things that matter to different strokes. You can use, you know, use Perplexity Labs, use Repli- use some of these-

    18. AH

      These are online resources?

    19. PC

      Yeah, yeah, and you can build, quickly build a computer vision app that is giving you data analytics on your strokes and in real time.

    20. AH

      So how's that work? You, you're taking the phone underwater, analyzing the stroke?

    21. PC

      In this case, I'm using mobile phone, so I'm doing everything above. You know, um...

    22. AH

      Okay, so you're, you're filming. If you could walk us through this. So y- you film your daughter doing freestyle stroke for-

    23. PC

      Right.

    24. AH

      ... you know, one.

    25. PC

      Right. Or breaststroke or butterfly.

    26. AH

      Sure.

    27. PC

      There's a lot of core things that, you know, maybe you wanna care about backstroke and freestyle. What's there, uh, you know, and I am not a, I was com- we used to run. Like, I know you're a good runner. (laughs) Um, but I'm a runner, I'm a rock climber, n- less a swimmer. But, um, you know, things like the roll or how high they're coming above the water. What's your, you know, what, what's your velocity on a p- you know, you can get actually very sophisticated once you have the data, right? And, you know, what's your velocity on entrance? How much, you know, where, how far in front of your, your head is your arm coming in? How, you know, what is, um-Maybe there's, again, maybe there are things that you, you know, are obvious, which is you want to know, you know, how consistent, uh, are your strokes and your cadence across, you know, the pool. Um, so you don't just have your speed. You suddenly have access to what I would call, and, and you'll hear me use this a lot, uh, better resolution, but also a lot more analytics that can give you insight. Now, important thing here is, y- y- you know, my 10-year-old is not going to resp-, I'm not going to go tell my 10-year-old that she needs to change her, her velocity on this, (laughs) you know, head or stroke. But it gives me information that I can at least understand and help her know how something is going and how consistent she is on certain things that her coaches have told her to do. Um, you know, and, and what I love about the idea is, look, this isn't just for the ease of getting access to the type of data and information that would previously... And I mean, I do code in, in a lot of areas, but you don't have to do that anymore to build these apps. In fact, you shouldn't. You should leverage, you know, AI for development of these types of tools.

    28. AH

      You t- you tell AI to write a code so that it would analyze, you know, trajectory jumping into the pool, how that could be improved if the goal is to swim faster.

    29. PC

      Y- you'd use AI to build an app that would allow you to do that so that you would have then access to that, whatever the data is that you want to do. Yeah, so in that case, you're trying to do better stroke analytics and, and understand things as you move forward. Um, you could do the same thing for running, for gait, for, uh, you could do, you, you know, in a work environment, you can understand a lot more about where vulnerabilities are, where weaknesses are. There are sort of two different places where I see this type of, um, AI acceleration and tool building really having major impact. It's on sort of democratizing data analytics and information that would normally be reserved for the elite to everyone that's really engaged. And that has a huge impact on improving performance because that kind of data is really, you know, useful in understanding, um, learning.

    30. AH

      Mm-hmm.

  9. 46:17 – 49:08

    Sponsors: AGZ by AG1 & Rorra

    1. PC

    2. AH

      We've known for a long time that there are things that we can do to improve our sleep, and that includes things that we can take, things like magnesium threonate, theanine, chamomile extract, and glycine, along with lesser known things like saffron and valerian root. These are all clinically supported ingredients that can help you fall asleep, stay asleep, and wake up feeling more refreshed. I'm excited to share that our longtime sponsor AG1 just created a new product called AGZ, a nightly drink designed to help you get better sleep and have you wake up feeling super refreshed. Over the past few years, I've worked with the team at AG1 to help create this new AGZ formula. It has the best sleep-supporting compounds in exactly the right ratios in one easy-to-drink mix. This removes all the complexity of trying to forage the vast landscape of supplements focused on sleep and figuring out the right dosages and which ones to take for you. AGZ is, to my knowledge, the most comprehensive sleep supplement on the market. I take it 30 to 60 minutes before sleep, it's delicious by the way, and it dramatically increases both the quality and the depth of my sleep. I know that both from my subjective experience of my sleep and because I track my sleep. I'm excited for everyone to try this new AGZ formulation and to enjoy the benefits of better sleep. AGZ is available in chocolate, chocolate mint, and mixed berry flavors. And as I mentioned before, they're all extremely delicious. My favorite of the three has to be, I think, chocolate mint, but I really like them all. If you'd like to try AGZ, go to drinkagz.com/huberman to get a special offer. Again, that's drinkagz.com/huberman. Today's episode is also brought to us by RORA. RORA makes what I believe are the best water filters on the market. It's an unfortunate reality, but tap water often contains contaminants that negatively impact our health. In fact, a 2020 study by the Environmental Working Group estimated that more than 200 million Americans are exposed to PFAS chemicals, also known as forever chemicals, through drinking of tap water. These forever chemicals are linked to serious health issues such as hormone disruption, gut microbiome disruption, fertility issues, and many other health problems. The Environmental Working Group has also shown that over 122 million Americans drink tap water with high levels of chemicals known to cause cancer. It's for all these reasons that I'm thrilled to have RORA as a sponsor of this podcast. RORA makes what I believe are the best water filters on the market. I've been using the RORA countertop system for almost a year now. RORA's filtration technology removes harmful substances, including endocrine disruptors and disinfection byproducts, while preserving beneficial minerals like magnesium and calcium. It requires no installation or plumbing. It's built from medical-grade stainless steel. And its sleek design fits beautifully on your countertop. In fact, I consider it a welcome addition to my kitchen. It looks great, and the water is delicious. If you'd like to try RORA, you can go to rora.com/huberman and get an exclusive discount. Again, that's RORA, R-O-R-R-A, .com/huberman.

  10. 49:08 – 53:00

    Digital Twin; Tool: Learning, AI & Self-Testing

    1. AH

      We will definitely talk more about digital twins and, but what I'm hearing is that it can be very, um, this is nerd speak, but-

    2. PC

      Yeah, yeah.

    3. AH

      ... do- domain-specific. I mean, like, the lowest level example I can think of, which would actually be very useful to me would be a digital twin of my refrigerator that would...... place an order for the things that I need, not for the things I don't need. Um, eliminate the- the need for a shopping list. Um, it would just keep track of like, hey, like you usually run out of strawberries on this day and this day. And it would just keep track of it in the background, and the stuff would just arrive, and it would just be there. And like eliminate what seemed like- like, well, gosh, isn't going to the store nice? Yeah, this morning, I wo- walked to the corner store and bought some produce. I had the time to do that, the- the eight minutes to do that. But really, I- uh, I would like the fridge to be stocked with the things that I like and need, and I could hire someone to do that, but that's expensive. This could be done trivially-

    4. PC

      Yeah.

    5. AH

      ... and probably will be done trivially soon, and I don't necessarily need to even build an app into my phone.

    6. PC

      Yeah.

    7. AH

      So, I like to think in terms of kind of lowest level, but highly useful and easily available now-

    8. PC

      Mm-hmm.

    9. AH

      ... type technologies. There are a couple of areas, like when it comes to students' learning information, we've heard that, you know, AI, we- we've heard of AI generally as like this really bad thing. Like, oh, they're just going to use AI to write essays and things like that. But there's a use of AI for learning. I know this 'cause I'm still learning. I teach and learn all the time for the podcast, which is, I've been using AI to take large volumes of text from papers. So, this isn't AI hallucinating. Just take, like just take large volumes of text verbatim from- from papers.

    10. PC

      Yes.

    11. AH

      I've read those papers, literally printed them out, taken notes, et cetera, and then I've been using AI to design tests for me of what's in those papers because I learned, uh, you know, about eight- eight months ago when researching a podcast on how to study and learn best, the data all point to the fact that when we self-test-

    12. PC

      Yes.

    13. AH

      ... especially when we self-test away from the material, like when we're being- when we're thinking, "Oh, yeah, like what- what is the cascade of hormones driving the cortisol, uh, negative feedback loop?" When I have to think about that on a walk-

    14. PC

      Yes.

    15. AH

      ... as opposed to just looking it up, it's the te- it's the self-testing that is really most impactful for memory, because most of memory is anti-forgetting. This is kind of one way to think about it. So, what I've been doing is, is having AI build tests for me and having it ask me questions like, you know, uh, "What is the- the- the, you know, the signal between the pituitary and the adrenals, uh, that drives the release of cortisol? And- and what layer of the adrenals does cortisol come from?" You know?

    16. PC

      And I love this.

    17. AH

      And- and so, it's- it's I'm sure that the information it's drawing from is- is accurate, at least to the best of science and medicine's knowledge now.

    18. PC

      Yes.

    19. AH

      And it's just testing me and it's learning. This is what's so incredible about AI, and I don't consider myself like extreme on AI technology at all. It's learning where I'm weak and where I'm strong at remembering things because I'm asking it, "Where am I weak and where am I strong?"

    20. PC

      Mm-hmm.

    21. AH

      And they'll say, "Oh, like- like naming and this," and like con- like thr- like third order conceptual links here need a little bit of work. And I go, "Test me on it." And it starts testing me on it. It's amazing. Like, I'm blown away that the technology can do this. And I'm not building apps with AI or anything. I'm just using it to try and learn better.

    22. PC

      Whether you're building apps or you're building a tool, you're b- you're using it as a tool-

    23. AH

      Mm-hmm.

    24. PC

      ... that's helping you optimize your cognition and find your weaknesses, but also give you feedback on your performance and- and- and accelerate your learning in this, right? Because it's-

    25. AH

      That, well, that's the goal.

    26. PC

      But you're still putting in the effort to learn, and I think even the- the ways that I'm using it to y- with, you know, computer vision with mobile devices, AI is a huge oppor- opportunity and tool that I- like using the cameras and the data that you've collected to, you know, have much more sophisticated input is- is huge.

  11. 53:00 – 1:02:07

    AI: Increase Efficacy or Replace Task?, AI & Germane Cognitive Load

    1. PC

      Um, but in both of those cases, you're shaping cognition. You're shaping, you're using data to enrich what you can know.

    2. AH

      Mm-hmm.

    3. PC

      And AI is just, you know, incredibly powerful and, uh, a great opportunity in those spaces. You know, uh, the- the place where I think it is, um, and I- I sort of separate it into literally just two categories. Maybe that's too simplistic. It's am I using... And- and this is true for any tool, not just AI, but am I using the tool, am I using the technology in a way to make me smarter about, you know, and- and let me have more information and make me more effective, but also cognitively more effective, gain different insights? Or am I using it to replace- re- replace a cognitive skill I've done before to be faster? And it doesn't mean you don't want to do those things. I mean, GPS in our car is a perfect example of a place where we're replacing a cognitive tool of, you know, to make me faster and more effective, and frankly, you know, you take away your GPS in- in a city you drive around in, and we're not very good. And-

    4. AH

      I remember paper maps. I remember the early studies of the hippocampus were based on-

    5. PC

      Yeah.

    6. AH

      ... London taxi drivers that had mental maps of the city.

    7. PC

      Absolutely.

    8. AH

      That, you know, uh, with all due respect to London taxi drivers up until GPS, like that, those mental maps are not necessary anymore.

    9. PC

      No. And I mean, they had more gray matter in their hippocampus, and we know that, and you look at them today and they- they don't have to have that because the people in their backseats have more data, have more information, have eyes from the sky. I mean, satellite data is so huge in our success in the future. And, you know, it- it can anticipate the things that locally you can't. And so, it's been replaced, but it- it still means when you lose that data, you don't- don't expect yourself to have the same spatial navigation of that environment-

    10. AH

      Mm-hmm.

    11. PC

      ... without it, right?

    12. AH

      I love your two- y- your two batches, right? You're either using it to make you cognitively better or you're using it to speed you up, but you have to be... Here's where I think people-

    13. PC

      Cognitively or physically.

    14. AH

      Cognitively or physically.

    15. PC

      Like, but you're still trying to gain-

    16. AH

      Right.

    17. PC

      ... insight and data and the information that's making me a more effective human.

    18. AH

      Right. And I think that the- the place where people are concerned-

    19. PC

      Yes.

    20. AH

      ... including myself, is when we use these technologies that eliminate steps, make things faster-

    21. PC

      Yeah.

    22. AH

      ... but we fill in the additional time or mental space with things that are neutral to detrimental.It's sort of like saying, okay, I can get all the nutrients I need from a drink that's eight ounces. This is not true, but then the question is like, how do I make up the rest of my calories, right? Am I making it up with also nutritious food?

    23. PC

      (laughs)

    24. AH

      Right? Um, let's just say that it keeps me at a neutral health status, or am I eating stuff that, because I need calories, that I'm not necessarily gaining weight, but I'm bringing in a bunch of bad stuff with those calories. And so in the mental version of this, um, things are sped up, but people are filling the space with things that are making them dumber in some cases.

    25. PC

      There was a recent paper from MIT that I, I actually... it, it was, it, it was very much what I spend a lot of my time talking about but, and, and thinking about, but, um...

    26. AH

      Yeah, could you describe that study?

    27. PC

      The upshot of the paper first was that people... there's a lot less, uh, me- mental process or cognitive process that goes on for people when they use LLMs to write papers, and they have, they don't have the same transfer and they don't really learn the information. Surprise, surprise. (laughs)

    28. AH

      So, so, to- just to briefly describe the study, even though it got a lot of popular press, it's, you know, um, MIT students writing papers using AI-

    29. PC

      Yeah.

    30. AH

      ... versus writing papers the old-fashioned way where you think and write.

  12. 1:02:07 – 1:09:43

    Bread, Process & Appreciation; AI to Optimize Physical Environments

    1. PC

    2. AH

      I'm gonna try and present two parallel scenarios-

    3. PC

      Mm-hmm.

    4. AH

      ... in order to go further into this question of how to use AI to our best advantage to enrich our brains as opposed to diminish our brains.

    5. PC

      Mm-hmm.

    6. AH

      So, I could imagine a world, because we already live in it, where there's this notion of slow food. Like, you, you cook your food, you get great ingredients from the farmer's market, like, like a peach that, quote unquote, really tastes like a peach, this kind of thing. You, um, you, you make your own food, you, you cook it and you taste it and it's, it's just delicious. And, and, um, I can also imagine a world where you order a peach pie online and it shows up and you take a slice and you eat it. And you could take two different generations of people, maybe people that are currently now 50 or older, and people that are 15 or younger. And the older generation would say, "Oh, isn't the, the peach pie that you made so much better? Like, these peaches are amazing." And I could imagine a real scenario where the younger person, 15 to 30 let's say, would say, like, "I don't know, I actually really like the other pie. I like it just as well." And the older generation is like, "This," like, "What are you talking about?" Like, "This is how it's done." What's different? Well, sure, experience is different, et cetera, but from a neural standpoint, from a neuroscience standpoint, it very well could be that it tastes equally good to the two of them, it just differs based on their experience. Would- meaning that the person isn't lying. It's not like this kid, um, i- uh, you know, isn't as fine-tuned to taste, it's that their neurons acclimated to, like, what sweetness is and what contrast between s- sweet and saltiness is, and what a peach should taste like. 'Cause damn it, they had peach gummies and that tastes like a peach, you know? And so we can be disparaging of the kind of what we would call the lower level or diminished sensory input.

    7. PC

      Yeah.

    8. AH

      But it depends a lot on the neural, what those neural circuits were weaned on.

    9. PC

      Couple of comments. I love the peach pie example. Making bread is another example of that. And in the '90s, everyone I knew when they graduated from high school got a bread maker that was shaped like a box and, you know, created-

    10. AH

      I remember this.

    11. PC

      ... this-

    12. AH

      Yep.

    13. PC

      ... like, loaf of bread with a giant, you know, rod through it, and it was just, it was the graduation gift for many years.

    14. AH

      (laughs)

    15. PC

      And, um, you know, you don't see those anymore. And, you know, if you even look at what happened with, like, the millennial generation in the la- you know, i- in the last five years, especially during the pandemic, suddenly bread-making and sourdough, that became a thing. What's the difference, you know? You've got bread. It's warm. It's, you know, uh, with the bread maker, it's fresh, and it is not at all desired relative to bread that takes a long period of time and is tactile and in the process in the making of it, and, you know, is clearly much more onerous than the other in its process of development. I think the key part is it's, in, in the appreciation of the bread, it, the process is part of it, and that process is development of sort of the germane knowledge and the commitment and connection-

    16. AH

      Mm-hmm.

    17. PC

      ... to that humanness of development, but also the tactile, uh, commitment, the work that went into it is really appreciated in the same way that that peach pie, for one, comes with that whole time series of data that wasn't just about my taste, but was also smell, also physical, also visual, and saw the process ev- you know, evolve, and build a different prior going into that experience. And that is, I think, part of richness of human experience. Will it be part of the richness of how humans interact with AI? Absolutely. Or interact with robots? Absolutely. So it's what are the relationships we're building and how are they, you know, how integrated are these tools, these, you know, companions, whatever they may be, in our existence will shape us in different ways. What I am particularly, I guess, bullish on and excited for is the robot that optimizes my health, my comfort, my intent in my environment, in my, you know, be it in the cabin of a car, be it in the, my, my rooms, my spaces.

    18. AH

      So what would that look like? If you, uh, could you give me the lowest level example? Um, like, what, like, would it be an assistant that helps you travel today when you head back to the Bay Area? Would it, like, w- what, what is this, uh, nonphysical robot?

    19. PC

      And I think we already have some of these. Like, it's the, the, the point where HVAC systems actually get sexy, right? Not sexy in that sense, but they're actually really interesting-

    20. AH

      Mm-hmm.

    21. PC

      ... because they are the heart of, you know-

    22. AH

      HVAC systems?

    23. PC

      Heating, ventilation (laughs) system in a way, see?

    24. AH

      Yeah.

    25. PC

      But you think about a thermostat, you know, a, a thermostat right now is optimizing for, an AI thermostat optimizing for my behavior, but it's trying to save me resources, trying to save me money, but it's not, doesn't know if I'm hot or cold. It doesn't know, to your point, it, my intent, what I'm trying to do at that moment, where, and this i- you know, speaks more to a lot of the, the things you've studied in the past. You know, it doesn't know what my optimal state is for my goal in that moment in time. But it can very easily, frankly-

    26. AH

      Mm-hmm. Okay.

    27. PC

      ... you know, can talk to me, but it can also know how, my state of my body right now-

    28. AH

      Mm-hmm.

    29. PC

      ... and what is going, you know, it's, if it's 1:00 AM and I really w- need to work on a paper, you, you know, my house should not get cold, but it also should be very, it should, for me, it shouldn't, I know.

    30. AH

      Mm-hmm.

  13. 1:09:43 – 1:16:37

    Awake States & AI; Measure & Modify

    1. AH

      (sighs) H- here's where I'm- I get stuck, and I've been wanting to have a conversation about this with someone, ideally a neuroscientist who's interested in building technologies for a very long time. So I feel like this moment is a moment I've been waiting for, for a very long time, which is the following.

    2. PC

      (laughs)

    3. AH

      I'm hoping you can solve this for all of us-

    4. PC

      (laughs)

    5. AH

      ... Bobby. We're talking about sleep, and we know a lot about sleep. You've got slow wave sleep, deep sleep, growth hormone release at the beginning of the night. You have less metabolic need then. Then you have rapid eye movement sleep, which consolidates learning from the previous day. It, uh, removes the emotional load of previous day experiences. We can make temperature adjustments. We do all these things, avoid caffeine too late in the day. Lots of things to optimize these known states that occupy this thing that we call sleep. And AI and technology is, I would say is doing a really great job, as is pharmacology, to try and enhance sleep. Sleep's getting better. We're getting better at sleeping despite more forces, um, uh, potentially disrupting our sleep-

    6. PC

      Mm-hmm.

    7. AH

      ... like smartphones and noise and city noise, et cetera. Okay. Here's the big problem in my mind, is that we have very little understanding or even names for different awake states.

    8. PC

      Mm.

    9. AH

      We have names for the goal, like, I wanna be able to work. Okay, what's work? What kind of work? Uh, I wanna write a chapter of a book. What kind of book? A non-fiction book based on what? But, like, we don't... We talk about alpha, beta waves, theta waves, but I feel like as neuroscientists, we have done a pretty poor job as a field of defining different states of wakefulness. And so the, like, the technology, AI and other technologies are, don't really have, they don't know what to- to shoot for. They don't know what to help us optimize for, whereas with slow wave sleep and REM sleep, like, we've got it. I ask questions of myself all the time, like, "Is my brain and what it requires in the first three hours of the day anything like what my brain requires in the last three hours of the day if I want to work in each one of those three-hour compartments?" Like, and so I think, like, we don't really understand what to try and, uh, adjust to. So here's my question. Do you think AI could help us understand the different states that our brain and body go through during the daytime, give us some understanding of what those are in terms of body temperature, focus ability, et cetera, and then help us optimize for those the same way that we optimize for sleep? Because whether it's a conversation with your therapist, whether or not it's a podcast, whether or not it's playing with your kids, whether or not it's Netflix and chill, whatever it is, the- the goal and what people have spent so much time, energy, money, et cetera, on, whether or not they're drinking alcohol, caffeine, taking Ritalin or Adderall or running or what... Like, humans have- have spent their entire existence trying to build technologies to get better at doing the things th- that they need to do, and yet we still don't really understand waking states. So can AI teach it to us? Can AI teach- teach us a goal that we don't even know we have?

    10. PC

      Can AI teach it to us? I would say AI is part of the story, but before we get AI, we need better, more data. Not just me, right? So maybe I am very focused right now, but without my belief, and this is my perspective, is imagine I- I'm very focused right now. I need to know the context of my environment that's driving that, like what are, what- what's in that environment? Is it internal focus that's gotten me there? What- what is my environment? What is that external environment? So the, understanding my awake state for me is very dependent on the data and interactions that happen from these different environments. Let me give an example. Like, if I'm in my home or I'm in a, say I'm in a vehicle, all right? And you are measuring information about me and you know I'm under stress or you know I'm, uh, experiencing joy or I'm, or heightened attention right now. Some different states you may want to-... uh, have my home, or my system react to mitigate.

    11. AH

      Well, like, if you get sleepy in a self-driving c- i- in a smart vehicle-

    12. PC

      Mm-hmm.

    13. AH

      ... it will make adjustments.

    14. PC

      Potentially, it will make adjustments, but not necessarily right for you.

    15. AH

      Mm-hmm.

    16. PC

      That's an important part, is optimizing for, you know, personalization and how a system responds. And, you know, it can make adj- any home, uh, an H- HVAC system or the, the internal state of a vehicle is gonna adjust, you know, sound, background sound, music. It's going to adjust, you know, whatever weather it can... haptic feedback, temperature, lighting. You know, any number of, you know, position of your, you know, your chair, dynamics of what's in your space. All of these different systems in my home or my, my other, you know, what it, what it... my vehicle, if it... or, uh, some other system can react, right? But the important thing is how you react is going to shift me. And the goal is to not measure me, but to actually intersect with my state-

    17. AH

      Mm-hmm.

    18. PC

      ... and move it in some direction.

    19. AH

      Mm-hmm.

    20. PC

      Right? Some...

    21. AH

      Yeah, I always think-

    22. PC

      Yeah.

    23. AH

      ... of devices as good at measurement or, uh, modification.

    24. PC

      Right.

    25. AH

      Mm-hmm.

    26. PC

      Mea- measurement or modification. Measurement is critical. And that's, yeah, measur- but measurement not just of my- me, m- but also of, like, my environment, and understanding of the external environment. And this is where, like, things like Earth observation and understanding, you know, we're getting to a place where we're getting, uh, image... you know, really good image quality data from sa- the, the satellites that are going in the sky at, at much lower, um, uh, (coughs) l- lower distances so that you now have, you know, faster reaction times between technologies and the information they have to understand and be dynamic with them, right?

    27. AH

      Can you give me an example where that impacts everyday life? Are we talking about, like, weather analysis?

    28. PC

      Sure.

    29. AH

      Huh?

    30. PC

      Weather predictions, uh, car envir- you know, things happening.

  14. 1:16:37 – 1:23:58

    Wearables, Sensors & Measure Internal State; Pupil Size (Pupillometry)

    1. PC

      right now, we think about wearables a lot. Wearables track us. You have smart mattresses, um, which are wonderful for understanding. So, there's so much you learn while, you know, from a smart mattress and-

    2. AH

      Mm-hmm.

    3. PC

      ... ways of also both measuring as well as intervening to-

    4. AH

      Mm-hmm.

    5. PC

      ... optimize your sleep which is the beauty. Uh, and it's this nice incredible period of time where you can measure so many things. Um, but, you know, in our homes... so I was... I used the example of a thermostat, right? It- it's pretty, you know, frankly dumb about what my goals are or what I'm trying to do at that moment in time, but it doesn't have to be, and there are co-... you know, there's a company, Passive Logic. I love them. Uh, they actually have, I think, some of the smartest, uh, digital twin HVAC systems (laughs) but, you know, their sensors measure things like sound. They measure carbon dioxide, uh, your carbon... your CO2 levels. Like, when, when we breathe, we give off CO2, you know. So imagine, you know, there's a dynamic mixture of acetone, Isoprene, and carbon dioxide that's constantly exchanging when my... you know, when I get stressed or when I'm feeling, you know, happiness or suspense in my, my, in my state. And that dynamic sort of cocktail mixture that's in my breath is both an indicator of my state but it's also something that, you know... it's just the spaces around me, you know, have more information to contribute about how I'm feeling and can also be part of that solution in ways that don't... I don't have to have things on my body, right? So, I have sensors now that can measure CO2. You can watch my TED Talk. I have given examples. We brought people in when I, when I was at Dolby and had, um, had them watching Free Solo, you know, the Alex Honnold movie where they're climbing El Cap-

Episode duration: 2:35:50

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