Transcription
So, Sam Altman just made an appearance on the Sequoia Capital AI Ascent. Here's some interesting things that kind of jumped out at me.
First of all, how do younger people use AI that's different from older people? Usually, when a new technology emerges, kind of the younger people that don't have preconceived notions tend to use it in a more natural way. They tend to get better with it. The interesting thing here is that the younger people seem to be using it as an operating system. Kind of an interesting insight. Take a listen.
What are the cool use cases that you're seeing young people using with TouchBT that might surprise us? They really do use it like an operating system. Um, they have like complex ways to set it up to connect it to like a bunch of files, and they have like fairly complex prompts memorized in their head, or like, you know, in something where they paste in and out, and um, the—I mean, that stuff I think is all cool and impressive, and there's this other thing where like they don't really make life decisions without asking like chbt what they should do. Um, and it has like the full context on every person in their life and what they've talked about, and you know, that like the memory thing has been a real change there. But, but yeah, I think it's a gross oversimplification, but like older people use CHBT as a Google replacement. Maybe people in their 20s and 30s use it as like a life advisor, something, and then like people in college use it as an operating system.
Next, they discuss where AI is going in terms of coding. Number one, how does OpenAI use these coding tools internally? And number two, how does it think of it in terms of the product offering? Are AI coding assistance just another sort of product thing to offer to the customers, or is it a more integral part of what Chad GPT needs to be? Take a listen.
How do you use it inside of OpenAI? Um, I mean, it writes a lot of our code. How much? I don't know the number. And also, when people say the number, I think is always this very dumb thing because like you said, Microsoft code is 30, 20, 30%—measuring by lines of code is just such an insane way to like, I don't—I—I maybe the meaningful thing I could—maybe the thing I could say is it's writing meaningful code; like it's writing—I don't know how much, but it's like writing the—the—the parts that actually matter.
A question about coding. I'm curious, is coding just another vertical application, or is it more central to the future of open AI? That one's more central to the future of OpenAI. Um, coding, I think, will be how these models kind of—right now, if you ask chatbt a response, you get text back; maybe you get an image—you would like to get a whole program back; you would like, you know, custom-rendered code for every response, or at least I would—you would like the ability for these models to go make things happen in the world, and writing code I think will be very central to how you actuate the world and call a bunch of APIs or whatever. So, I—I would say coding will be more in a central category. We'll obviously expose it through our API on our platform as well. Um, but you know, chat GBT should be excellent at writing code.
Next is, where will the most sort of value creation happen in the next 12 months? What are the most exciting things that we expect to see over the course of the next 12 months? He mentions AI agents, robots, and code.
Where do you think most of the value creation will come from in the next 12 months? Would it be maybe advanced memory capabilities or maybe security or protocols that allow agents to do more stuff and interact with the real world? Um, I mean, in some sense, the value will continue to come from really three things: like building out more infrastructure, smarter models, and building the kind of scaffolding to integrate this stuff into society, and if you push on those, I think the rest will sort itself out. Um, at a higher level of detail, I kind of think 2025 will be a year of sort of agents doing work. Coding in particular, I would expect to be a dominant category. I think there'll be a few others too. Um, next year is a year where I would expect more like, uh, sort of AI discovering new stuff, and maybe we have AIs make some very large scientific discoveries or assist humans in doing that. And you know, I'm—I am kind of a believer that most of the sort of real sustainable economic growth in human history comes from—once you've like kind of spread out and colonized the earth, most of it comes from just better scientific knowledge and and then implementing that for the world. And then 27, I—I would guess is the year where like that all moves from the sort of intellectual realm to the physical world and robots go from a curiosity to like a serious economic creator of value. But that was like an off the top of my head kind of guess right now.
Next up, we have a question about why bigger companies tend to be slower and why startups tend to succeed more. This also applies to how people use technology in our current world where technology just keeps getting faster and faster. This is an important thing to kind of understand. Certain types of people and companies will be left behind, and certain types will be propelled forward. Which type are you?
Smaller companies are clearly just beating the crap out of—out of larger ones when it comes to innovation here. I—I think this basically happens every major tech revolution. Um, there's nothing to me surprising about it. The thing that they're getting wrong is the same thing they always get wrong, which is like people get incredibly stuck in their ways. Organizations get incredibly stuck in their ways. If things are changing a lot every quarter or two and you have like an information security council that meets once a year to decide what applications are going to allow and what it means to like put data into a system, like, I—it's just—it's so painful to watch what happens here. But like, you know, this is—this is creative destruction. This is why startups win. This is like how the industry moves forward. Um, I am—I'd say I feel like disappointed but not surprised at the rate that big companies are willing to do this. Um, they will—my kind of prediction would be that there's another like couple of years of fighting, pretending like this isn't going to reshape everything, and then there's like a capitulation and a last-minute scramble, and it's sort of too late, and in general, startups just sort of like blow past people doing it the old way. Um, I mean, this happens to people too, like watching—watching like a—you know, someone who started—maybe you like talk to an average 20-year-old and watch how they use chat GBT and then you go talk to like an average 35-year-old and how they—they use it or some other service, and like the difference is unbelievable. It reminds me of like, you know, when the smartphone came out and like every kid was able to use it super well and older people just like took like 3 years to figure out how to do basic stuff. And then, of course, people integrate, but—but the—the sort of like generational divide on AI tools right now is crazy. And I think companies are just another symptom of that.
And finally, he briefly talks about adversity. What happens when in life or in business you get hit really, really hard? How do you navigate the immediate fallout? But he also brings up a part about kind of looking past that a little bit down the road, which is an interesting point that doesn't get talked about quite as often.
It gets easier over time. I think like you will face a lot of adversity in your journey as a founder, and the—the kind of challenges get harder and higher stakes, but the emotional toll gets easier as you kind of go through more bad things. So, it's—uh, you know, in some sense, like it does it. Yeah. Even though like abstractly the challenges get bigger and harder, the—your ability to deal with them, the sort of resilience you build up gets easier like with each one you—you kind of go through. Um, and then I—like I—I think the—the hardest thing about the big challenges that come as a founder is not the moment when they happen. Uh, like a lot of things go wrong in the history of a company. Um, in the acute thing, you can kind of like, you know, you get a lot of support, you function on a lot of adrenaline. Like that's, you know, you kind of like—e—even the really big stuff, like your company runs out of money and fails, like a lot of people will come and support you. Um, and you kind of get through it and go on to the new thing. The thing that I think is harder to sort of manage your own psychology through is the sort of like fallout after. Um, and I think if there's, you know, people focus a lot about how to work in that one moment during the crisis. And the really valuable thing to learn is how you like pick up the pieces. There's much less talk about that. I think there's—I've never actually found something good to point founders to to go read about, you know, not how you deal with the real crisis on day zero or day one or day two, but on day 60 as you're just trying to like rebuild after it. Um, and that's—that's the area that I think you can like practice and get better at.