Invest with AI
00:49:25 · Doug Clinton
[00:49:25] S0: Yeah. I think just like in investing, right, you wanna look six, twelve, eighteen months out what you think the world is gonna look like then. Because, ultimately, if you're right about your prediction about the world, hopefully, you're you're right about what stocks you buy ahead of that. And thinking about building with these models, we're always trying to figure out, okay. We know they're going to get better. I think that's a given. If anybody is following the AI space in twelve months, these models would be more capable. But, like, what are the bottlenecks today that we think will be unleashed with additional capabilities? How can we prepare ourselves to be ready to sort of take advantage of those things that get unlocked as soon as possible and stay at the forefront? Because I think to the extent you can stay at the forefront... Mean, there's this great quote that I I say all the time internally from Paul Bookheit, who was at Google and then Y Combinator. He said, if you're in the lead, if you just keep running faster than everybody else, no one could ever catch you. I think that's true no matter what you're trying to do with these models. If you can really stay on the edge and keep experimenting, don't worry about perfection, even though that's really hard to say in the investment world, but just keep iterating. I think that that will put you in a really good place to find ways to generate alpha with these models over time.
00:50:43 · Brett Caughran, Khe Hy
[00:50:43] S2: Yeah. I've been a hater on a lot of these things or at least trying to provide some skeptical reasoned empirical push pushback. And one of my friends says, Brett, evidence is a lagging indicator in AI, right? You sort of have to operate and build the system on faith that the thing you can't do today will be possible in three months or six months. So I'm trying to take that to heart as I think about you where we could be in the spring of twenty seven. It's also becoming easier because the evidence of where we're at today versus six or nine months ago, if I sort of pull up my outputs of what I could do in summer twenty five versus summer twenty six, it's a fundamentally different different human, fundamentally different sort of intelligence source today. So where we're at next summer kind of hurts my brain a little bit to think about. Any thoughts, any sort of closing thoughts or comments, K? [00:51:39] S1: Yeah, I think that the ability to be uncomfortable with uncertainty, right, and kind of like leaning into it versus kind of holding on to the determinism. But, you know, what I got from our talk with Doug today is just it's messy, right? And I think a lot of the conversation it's an industry that doesn't like to be messy for the right reasons. Like, are significant penalties for being messy in this industry. But to the extent that you can kind of bring in that experimentation, which is like what the three of us on this episode and many of our clients are doing, you know, again, those pockets will lead you to kind of stay, skate to where the puck is going.
00:51:39 · Khe Hy, Brett Caughran
[00:51:39] S1: Yeah, I think that the ability to be uncomfortable with uncertainty, right, and kind of like leaning into it versus kind of holding on to the determinism. But, you know, what I got from our talk with Doug today is just it's messy, right? And I think a lot of the conversation it's an industry that doesn't like to be messy for the right reasons. Like, are significant penalties for being messy in this industry. But to the extent that you can kind of bring in that experimentation, which is like what the three of us on this episode and many of our clients are doing, you know, again, those pockets will lead you to kind of stay, skate to where the puck is going. [00:52:27] S2: Yeah. Yeah. One of the hardest questions I get is almost a simple one. It's like, Hey, Brett, I want to set this up. What do I do? What vendor should I use? I'm like, I don't know. It's kind of like still three years in or almost four years into the ChatGPT moment. It's still kind of a hard question. There's not yet an obvious answer. It's a little bit more of a process, a journey of experimentation and learning, which is a little bit unsatisfying. But the comfort with uncertainty is probably the exact right thing. Nailed it. Nailed it. Nailed Nailed it. Okay, what say you dug?
00:53:03 · Doug Clinton
[00:53:03] S0: Yeah. I think on that on that point, Brett, the the best way I always try to tell people to get involved with these models for any purpose, whether it's finance or otherwise, is you have to find something that you're really curious about, and you just get lost in the models doing. And that could be designing a new clothing line. It could be writing some piece of content. It could be trying to pick, you know, some super aggressive AI related stock portfolio. Whatever it is, the more that you can just get lost using the models and then understanding, like, the intricacies of how they work, understanding where you can push the limits and the edges and what you can have it actually build for you, that's the best thing you can do is just kind of learn it by feel by doing something that's really fun for you. And then you can take that curiosity, all those learnings that you have, and apply them to something that might be a little bit more structured and intentional. But until you kinda get through that and you just experience the models, you know, unfettered, right, and just let them go wild, I think it's really hard to kind of think about the structured thing because you just don't even really know what they're capable of yet. Yeah.
00:54:08 · Brett Caughran, Doug Clinton, Khe Hy
[00:54:08] S2: Well, thank you so much for joining us today. This has been really fascinating, and I'm super excited to see where you're at on this in six months or nine months or twelve months. Maybe we'll come back in. It's like, we got the keys. We figured it out now. So thank you so much for being with us, Doug. This was really fun and interesting time in an interesting space. [00:54:31] S0: Absolutely. Thank you guys too. [00:54:32] S1: Thanks, Doug.