Entrepreneurial Thought Leaders (ETL)
00:20:55 · Emily Ma, Brendan Foody, S3
[00:20:55] S1: Yeah. Yeah. Okay. This is a fun one. We talk about artificial general intelligence. I know there's AISI, AGI. There's many ways of going about it. When that day comes, what will you be doing? [00:21:06] S2: Well, I think I'll be doing the same thing. But but I do think there is such a large nuance between, I guess, AGI people define usually as models being able to do most economically valuable work versus a 100% of economically valuable work. And a great proxy for this is that the Bureau of Labor Statistics analyzed that over the last two hundred twenty five years, we've made the average, person 20 times more productive. So that's equivalent to automating 95% of what you do in your job. Yet, at the same time, we have more jobs in the economy than ever before. [00:21:45] S3: That's right. [00:21:46] S2: And I think that that will continue where so long as we don't automate a 100% and we just automate 95% of what everyone does, we're not gonna run out of things to do as a society. We're gonna have so much more work. We'll build a thousand times more software. We'll build rockets. We'll cure cancer, go to Mars, etcetera. And I think there's gonna be immense human involvement in all of those processes.
00:21:46 · Brendan Foody, Emily Ma
[00:21:46] S2: And I think that that will continue where so long as we don't automate a 100% and we just automate 95% of what everyone does, we're not gonna run out of things to do as a society. We're gonna have so much more work. We'll build a thousand times more software. We'll build rockets. We'll cure cancer, go to Mars, etcetera. And I think there's gonna be immense human involvement in all of those processes. [00:22:09] S1: You know, it's funny. We're experiencing these moments. The one that comes to mind for me is always the ATM. I think the banking industry was having a moment, thinking all these tellers would lose their jobs, but actually, financial industry evolved and became much broader and stronger as a result of... I mean, ATMs were just one thing in in innovation in that field. So we're seeing that widespread now, and it's helping people through this transition. [00:22:34] S2: I totally agree. Yeah. And I think there's also enormous job creation associated with people building data centers, people training agents for deployed engineers that need to go deep with every Fortune 500 to implement agents. And so with every revolution, there's been some degree of creative destruction that happens, and ultimately, humans always have and always will, play a meaningful part of the economy. [00:23:00] S1: Let me zoom out a little bit. What is the role of policy and government in a transition like this?
00:23:00 · Emily Ma, Brendan Foody
[00:23:00] S1: Let me zoom out a little bit. What is the role of policy and government in a transition like this? [00:23:09] S2: I think that there can be a lot of value to regulators helping to internalize the externalities to markets. And what I mean by that is sometimes markets don't price in that there are certain, you know, negative, things that happen because of business outcomes. Like, the most common example is carbon, from burning fossil fuel. And, like, how could we price in that externality via a carbon tax? I think similarly, probably the externality that's, like, most top of mind for the average American right now is jobs. Yes. While jobs are, like, the largest positive thing for everyone's lives in the economy, they're also the largest thing that regulators disincentivize. And so I think figuring out how regulators can invest and set... Through, like, payroll taxes, income taxes, especially at the low end, I think those are are not great. But figuring out how regulators can better incentivize all these positive things that we want more of, like new job creation, I think is, one of the most important things. [00:24:21] S1: Amazing. Okay. So, in the next year, we'll end with this question, and then we'll hand it to students. Actually, we'll have one more question after this. What are you most excited about? You don't have to disclose anything, but, like, what what are you excited about in terms of where AI is going? [00:24:39] S2: I'm really excited about how it gets applied to the rest of the economy. [00:24:43] S1: Yeah.
00:24:43 · Emily Ma, Brendan Foody, S6
[00:24:43] S1: Yeah. [00:24:43] S2: Because I think it's easy to be in these, like, echo chambers in Silicon Valley where [00:24:48] S1: you think [00:24:49] S2: that, you know, AI has a 100% adoption when we talk with the average company in the Midwest. They, you know, just started using ChatGPT a few months ago. Mhmm. And I think that that getting, like, really permeated throughout every business workflow in addition to every consumer is gonna be really exciting. I think in the context of Merkur, that's expanding from just serving the frontier model companies to serving every enterprise in the world and helping them build, the evals that correspond to their value chain so that they're able to implement and apply agents throughout everything that they do. [00:25:31] S1: Alright. So final, final question, which is the classic question we always ask at the end of these chats, is from Tina Selig, who started the series about thirty years ago. She wrote a book called What I Wish I Knew When I Was 20. I know that wasn't that long ago for you. That was... You know, you just turned 23. Happy birthday. If you could go back to three years ago, I've actually... I have, like, two questions here. What would you tell yourself, and what would you tell your mom? [00:26:01] S6: What would
00:26:01 · S6, Brendan Foody, Emily Ma, S3
[00:26:01] S6: What would [00:26:02] S2: I tell my mom? I'll I'll think about that one, but I think one of the most important things people don't talk about is focusing on leading indicators when markets are moving really fast. Like, if I had to distill what we did strategically into one thing, it would be that. And that we saw, hey. The cutting edge Frontier Labs see this thing in the markets where we can learn from them about, you know, how the entire economy is gonna change shape. And if we just focus on those leading indicators, that gives us a window into the future. And so I I would encourage all of you to try to see, like, what are those leading indicators and how all of these markets, whether it's data or compute or modeling, are changing extremely quickly. And, how do you use that as a window into the future? In terms of what I would tell my mom, I'm not sure. I I think I would tell her probably something similar. Don't don't worry. It'll it'll all work out. [00:27:04] S1: Yeah. Truly, it has. Truly, it has. [00:27:06] S3: Okay. So we're going to organize ourselves to do Q and A. Maybe to add to the thing you said before about kind of automating jobs and automating tasks, what is something that you kind of saw or see that is not really easy to automate or what is something that makes, like, the human human and not... Cannot be automated through AI?
00:27:06 · S3, Brendan Foody, S7
[00:27:06] S3: Okay. So we're going to organize ourselves to do Q and A. Maybe to add to the thing you said before about kind of automating jobs and automating tasks, what is something that you kind of saw or see that is not really easy to automate or what is something that makes, like, the human human and not... Cannot be automated through AI? [00:27:27] S2: One thing that I think everyone is over... Overestimating progress on is the physical world. Like, the majority of work that happens in terms of dollars is in the physical world, whether it's electricians or mechanical engineers, or all of the physical world services. And I think building out the distribution of data for how agents will learn how to do all of that is gonna take an extremely long time. And so I think understanding, yeah, what are all the opportunities to accelerate that, what are the things that are gonna take a lot longer to do, and how that shapes markets is gonna be really important. [00:28:06] S7: Hi. Thanks for being here, Brendan. I have two quick questions. Firstly, how does it feel to be, the youngest billionaire in the world? And, secondly, I was curious, what are sort of the blocks of constancy throughout your day? What are the key habits you do every day that has made you into who you are today?