Transcription
So let's let's get into AI a little bit. Um, you asking you the questions. I don't know.
So actually, um, not many people remember, but you were one of the first people to key in on Chad as a as a tool for business, and I remember some of your early videos. It was like three, three, almost two, three years ago.
Yeah. It was a lot. Yeah. It was like a couple weeks after Chach was launched, right? In like, um, was it November '22 or something like that? December '22. Yeah.
Um, so, uh, and I was very interested because I, I always watch your world and I watch the Silicon Valley world and I see like what is hopping over. And when I saw that, I was like, "Okay, this is going to be huge."
Uh, um, so so what, what, what like what sparked the interest for, for chat? What, what, what vision did it create for you?
I mean, I, I think that there's there's fun questions of like, what is it? So, I'm such a, such a like, what do I geek out on? Like, what do I really enjoy a lot? Um, is studying learning and behavior. And you can hear it through all my, my definitions, my business books. Like that's the through line that that marries everything.
Um, and so then then I mean, AI obviously begs the larger question of like, what does it mean to be human? And I think, and I have this philosophical slant in my own interest. And I think that's probably why I was drawn to it disproportionately. I also am a writer, and so language is a natural thing for me. And so the kind of the, the confluence of multiple of these things together, um, made chat really interesting.
Um, but just in like, we, we as humans tend to be very romantic about our ourselves and thinking that like, no one can do what we can do. And like, we've been proven time and again that we're, we're not as special as we think we are.
Um, that fits in your world.
Yeah. So it's totally a lot of my worldview. Um, a lot of people are very upset by that. But but with with each thing that it proves it can do, because if if artificial intelligence learns almost exactly the same way that humans do through reinforcement training. And so you have you do a thing and you get an outcome. Yay or nay. And I believe at the most foundational level, when you ask the question like, why, why are you so driven? Or why are founders so driven? We have gone through some reinforcement training, which we may have been aware or not aware of, that reinforced this set of behaviors that when you know stacked together. So you see a skill as a behavior chain of multiple adaptive skills that are put in sequence, uh, to create an outcome that's maybe, you know, ideal.
Or that adaptive chain becomes a more complex set of, uh, behaviors that becomes a skill. Sorry.
Um, and so to the same degree, AI basically learns the same way humans do.
And so if it learns the same way humans do, then it will be able to do what humans do. Okay, that's the very first principles kind of thinking, especially watching Tach. It kind of sucked back then, but like being able to key on that.
It just keeps tweaking. And so, um, it, it, it obviously starts with with just, you know, language, but then it just continues to move, move out. And I'm curious what you think about like Tesla, as because, you know, it trying to us trying to clean data sets to train on larger and larger, you know, you know, big data that it's that it's working off of.
Um, obviously that will limits and then creating high quality data will become the constraint of the learning. And so then it, it will have to learn from first principles itself, which is going to be experimentation in the world. Which means it has to have some sort of link to the real physical world, which is exactly how we learn.
Yes. Right. And so we're able like we have a so everyone who feels like, you know, AI is not as smart as humans, it's like, well, because we've had a learning advantage.
Yes. Because we take 10,000 inputs a day or whatever the number is.
Um, if we take all of our senses times, you know, hours and whatever we can take in. Um, as soon as we have robo babies, and I say that not a like not a weird way, but like, um, where it can experiment and touch and taste and do all that stuff in the world. I think the reinforcement loops will happen so quickly. And the other part of it that will happen is that it doesn't forget. And I think that's the that's the crazy part.
So we've, you know, we've obviously trained AI for different functions within our business, um, and business use cases. And one of the things that was astonishing to me is that we were trying to train a, um, an SDR, um, so a sales development rep who would, you know, do outreach or do follow-up.
Um, and what was really interesting to me was that, um, hallucinations are still a problem right now with it. And I think will always be a problem. I'm sure I don't know the French guy, but the guy who Google listens to and he's some, you know,
French special, right?
Might be. Yeah.
Um, but he basically was saying that like LLMs will never truly get into API because if you have 3% error, it gets expounded, you know, uh, at infinite.
And so, uh, he did moderate his view, but I'll tell.
Oh, yeah, please. Yeah, tell me. Um, but one of the things that, uh, I found so cool for me though, is that like, you know, it would it would make a mistake. And I would, you know, we like, hey, do this next time. And immediate and every time it would do that. And I was like, man, I've trained a lot of sales people. Like scary in a cool way of just how quick you can learn. And it just doesn't make a mistake after that. Obviously, there's hallucinations, but in terms of following the directions, it would follow, right?
And so if if you. It's funny because there's there's a lot of like really cute isms and in Silicon Valley, like, you know, being a master is something that like some skills cannot be taught and only learned. Like there are these very cute like rhetorical devices, but they're just not they'd make no sense.
Yeah. Like if you learned it, you learned it, which means someone could teach it. It's just not structured.
And we didn't know how we taught it because there's multiple factors, but like if we if you control the conditions, you can control the outcome. At least that's my viewpoint in the world. And so.
It just means that there's more complex environments in order to learn. And so, um, I think I've just taken a lot of interest in that because, you know, the obvious of like, chat GPT enters Optimus, or, you know, Grock enters Optimus world, it's like.
Oh, okay, well, it can interact with all the tools that we've already made around the world to to interact with as humans and never make a mistake after that. And then that just gets into lots of questions around existence, that concept, which I.