Brendan Foody on Teaching AI and the Future of Knowledge Work

Conversations with Tyler is produced by the Mercatus Center at George Mason University bridging the gap between academic ideas and real world problems Learn more at mercatus.org. For a full transcript of every conversation enhanced with helpful links, visit conversationswithtyler.com. Hello, everyone, and welcome back to Conversations with Tyler. Today, I'm sitting here chatting with Brendan Fudi at the offices of Merkor. Merkor is an AI company, we'll get into more details soon enough, which dates from early twenty twenty three. Brendan is the CEO and cofounder. I believe he's the youngest unicorn founder ever. Mercor, by some estimates, is the fastest growing company ever. For instance, the quickest speed to $400,000,000. Brendan also at age 22 is the youngest Conversations with Tyler guest ever. My proudest achievement. There's more we'll get to soon enough. But, Brendan, welcome. Thank you so much for having me, Tyler. Excited to be here. Now I saw an ad online not too long ago from Aircor, and it said a $150 an hour for a poet. Why would you pay a poet a $150 an hour? That's a phenomenal place to start. I I think it's because so for background on what the company does, we hire all of the experts that teach the leading AI models. And so when one of the AI labs wants to teach their models how to be better at poetry, We'll find some of the best poets in the world that can help to measure success via creating evals and examples of how the model should behave. And one of the reasons that we're able to pay so well to attract the best talent is that when we have these phenomenal poets that teach the models how to do things once, they're then able to apply those skills and that knowledge across billions of users, hence, allowing us to pay a $150 an hour for some of the best poets in the world. So the poets grade the poetry of the models, or they grade the writing, or what is it they're grading? It could be some combination depending on the project. But an example might be similar to how a professor in English class would create a rubric to grade an essay or a poem that they might have for the students. We could have a poet that creates a rubric to grade, you know, how well is the model per creating whatever poetry you would like and a response that would be desirable to a given user. How do you know when you have a good poet or a great poet? It's that's so much of the challenge of it, especially with these very subjective domains in the liberal arts. Right? Is that so much of it is this question of taste, where you want some degree of consensus of, you know, different exceptional people believing that they're each doing a good job. But you probably don't want too much consensus because you also want to …