01:07:31 · Mario Gabriele
[01:07:31] S1: my favorite activities to do with my my son is he loves to look at my bookcase and just pull out whatever covers he finds interesting. He's, you know, 15 old, so he's just doing it based on, you know, what interesting faces on the front or whatever. And he's gotten really interested in Oliver Sacks' biography called On the Move. Because, I don't know, it's a picture of Oliver Sacks. It's, you know, engaging. And I was just paging through it with him, like, last week, and I was already starting to think quite a lot about our conversation. And it lands on this page where Oliver Sacks talks about being obsessed with proprioception, and how this is, you know, the sixth sense, and it's actually the most important sense because, you know, you can strip humans of of all the other five, and they can more or less get a... Get along. But if you, you know, get rid of this sense of where your body is, life becomes extremely hard. And he talks about working with these patients who, you know, maybe have a virus and they lose this this sense of of their own their own body. And he has this one case, which made me think a lot about what you're doing and and maybe what the, final state of it might look like, which is this guy gets a virus, and he loses the sense of proprioception, but he compensates with visuals where, you know, if the lights go off in a room, he can no longer move. But as long as he can see where he is, he can sort of walk, but not walk and talk, etcetera, etcetera. And so it's it's basically the way that the the brain compensates for the loss of this sense. Is that sort of the stage we're at at the moment with physical intelligence where we don't have true proprioception, and so we're sort of compensating with these other senses. And is there a point in the future, do you think, where however a computer is able to emulate that, we have something that really feels equivalent to it. Yeah.
01:09:31 · Karol Hausman
[01:09:31] S0: There are many neuroscientific experiments showing something like this, how you can you can disable one sensing modality and then compensate for compensate for it with another one. I think in general, it's quite unclear what the right sensing modalities should be. I think our intuitions are often wrong about this because also these machine learning algorithms can extract the right level of information from signals that to us seem like insufficient. Like, a common question I get is, you know, about touch sensing on our robots. And instead, we put wrist cameras, and it turns out that they can compensate for the lack of touch just fine. And they probably find some kind of regularities in the data where maybe you see the deformation on the gripper or something like this that indicates to you how much pressure you're applying, and that's enough for it to to fully compensate for the sense of touch. It might be that we'll find some tests where that's not the case, and you really need some other sensing modality to tell you the the the... To to to to give you that signal. But so far, I think it's been quite surprising to the entire field how far you can push it with with just simple cameras. I think in general, though, a lot about intelligence is about compensating. It's... And what I mean by this is kinda like predicting what's going to happen and then trying to figure out if if what actually happened... How how different it is to what you predicted. And it doesn't just apply to sensing modalities. I think it also applies to precision. So for instance, as a as a human, you're very imprecise when it comes to movements. Right? Like, if I ask you to put your finger on a specific point 100 times in a row and I measure this exactly, there will be quite a bit quite a bit of variance, especially compared to modern industrial robots that can go to sub millimeter accuracy and very good repeatability. But if you compare our dexterity to dexterity of those robots, you know, it's night and day. We're way more dexterous even though we're way less precise of a machine. And I think the reason for this is that we have physical intelligence that's gonna compensate for it. We have enough feedback that if we just look where where our fingers are or if we just feel it, we can compensate for it immediately.
01:11:44 · Karol Hausman, Mario Gabriele
And I think we'll see that being translated to robot design as well, where maybe the the robots of the future don't need to be as precise as we had thought or, you know, they they can they can accommodate for a lot of things like a little bit of backlash in the motors or just noise because with the right intelligence, you can you can compensate for it. And that's what we've seen here at at Physical Intelligence. We show some of the most impressive demos ever on robots. But these robots are really bad robots. If you compare them to to any state of the art industrial machine, they're really, really bad. They're very imprecise, not very reliable, a lot of backlash and other problems, but it doesn't really matter because the right intelligence can compensate for it. [01:12:28] S1: Well, you're... That was a very interesting and gracious way of answering a very baggy question from me. So I'm glad I asked it because, yeah, that was that was fascinating. As a final wrap up question, I always like to ask folks that if they had the chance to assign a book to everyone on Earth to read and know that they would understand it, what is a book you would you would love to give everyone? I reread recently a book that I'm
01:12:28 · Mario Gabriele, Karol Hausman, Mario Gabriele
[01:12:28] S1: Well, you're... That was a very interesting and gracious way of answering a very baggy question from me. So I'm glad I asked it because, yeah, that was that was fascinating. As a final wrap up question, I always like to ask folks that if they had the chance to assign a book to everyone on Earth to read and know that they would understand it, what is a book you would you would love to give everyone? I reread recently a book that I'm [01:12:56] S0: a big fan of. I'm not sure if this is the the book I would recommend to everyone, but this is the book I think it's... That is really, really good. It's Why Greatness Cannot Be Planned by by Ken Stanley. Yes. Yeah. I think it's just a wonderful counterintuitive book that shows multiple examples of how we arrive at something really spectacular without planning for it. I find it quite inspiring and quite motivational in a way that is maybe a little less straightforward than than than usual. So I think it's just like a very insightful book that would that that would help a lot of people to to show... Shed a new light on how to think about innovation and achieving something spectacular. [01:13:41] S1: Well, that's a perfect place to end. Thank you so much, Karol. [01:13:45] S0: Thank you. [01:13:46] S2: That's it. Thank you for
01:13:46 · Mario Gabriele, Mario Gabriele
[01:13:46] S2: That's it. Thank you for [01:13:47] S1: listening to this episode of The Generalist Podcast. Please subscribe on Apple Podcasts, Spotify, or your preferred podcast app. Ratings and reviews help others discover these discussions. So if you enjoyed the conversation, I'd be grateful if you could take a moment to leave one. For all past episodes and more, visit us at the generalist.substack.com. See you next time as we continue to explore the future.