The Ledger, every show

“Like I would never hire data scientists when the first three people in a company. And I say that because I used to be a data scientist. Like data scientists are great when you want to optimize your product by two percent or five percent, but that's definitely …”

“Product managers are great when your company gets big enough. But at the beginning, you should be thinking about yourself about what product you want to build. And your engineer should be hands-on. They should be having great ideas as well.”

“I think one of the things that people really underestimate is how it is, how complicated it is that you can't just synthetically generate it.”

“So I would bet on XAI. I think they're just very hungry and mission-oriented in a way that gives them a lot of really unique advantages.”

“So I actually see more and more frontier models opening up over time because I actually don't think that the models will be commodities.”

“At these bigger companies, a lot of your priorities, a lot of the things that you're building, they're simply, you're simply building them to impress someone. Like, hey, I need to impress my VP. I need to impress my manager. I need to impress my director so th…”

“So like I, for example, personally, I actually have no one-on-one meetings and it's kind of funny because oftentimes people will ask me, well, How often do you meet with your reports? How often do you set aside for, like, for these meetings? I just don't have …”

“And already you have a lot of these single person startups that are already doing ten million revenue.”

“Yeah, for a 90% of companies, no. Like, sure, there are some companies where you actually do need a lot of capital in order to build hardware or, like, whatever it is for a couple years. Like you really need a lot of investment before, before you before you ca…”

“So every now and then, if something is important enough, like maybe there's some big new product is actually really cool, or there's some really, really interesting new research paper. It'll be like big enough that even though I'm not monitoring Twitter every …”

“I think 80% of the computer science PhDs I know, they write shitty code because they're only good at math and algorithms.”

“If all you're kind of doing is throwing PhDs as a problem, all you're doing is teaching models how to hack Silly benchmarks and get good at basically the equivalent of SAT problems.”

“I think a lot of people do confuse working hard with creating value. Like again, I mean, it's maybe a trope to say, but you have to work smart and not just hard. Like, if I think about a lot of what I'm doing, oftentimes the best ideas come to me when I'm just…”

“I don't think models today can write 50% of the code and, you know, come up with 50% of the ideas that, that people are, that are actually going to be meaningful to your company.”

“And we're about a hundred, a little over a hundred people.”

“So there's a very, very low ceiling on the bar of quality, but then take something like writing poetry. Well, I suck at writing poetry. Hemingway's definitely want to write a much better poem than I am. Or imagine, I don't know, a VC pitch deck. You're going t…”

“Like, I don't think our environments alone will suffice just because, I mean, it depends on how you think about our environments, but oftentimes these are very, very rich trajectories are very, very long. And so it's almost like inconceivable that a single rew…”

“Like we use it like a ton ourselves in order to supplement what the humans do.”

“So internally we do a lot of work actually today with working with all the frontier labs to help them understand their models. So again, we're constantly evaluating them. We're constantly surfacing loss areas for them to improve on and so on and so on.”

“Like, I think it is really interesting in that a lot of the, like for obvious reasons, a lot of the frontier labs, they're just not publishing anymore.”

“I think a big part of it actually just boils down to the kinds of questions they ask me. Like some people, when I interview them, they will ask really interesting questions about our product. They will brainstorm about ideas to make our product even better. Th…”

“Once you optimize for clicks, the most click-baity content starts rising up to the top. You get lots of racy content, lots of girls in bikinis, lots of listicles about 10 horrifying skin diseases, and so on.”

“Historically, a lot of ML engineers, they kind of just don't take the time to look at the data.”

“We were very lucky to be profitable from month one.”

“One of the things that I think is actually really important is that you want customers who Especially early on. You want customers who believe in your product and not people who are simply giving you a little bit of money. Like, because your early customers wi…”

“We work really closely with the XAI team and it's actually just incredibly refreshing to see how they operate.”

“I mean, I have felt That maybe 50% of the things I used to Google search, they are replaced by ChatGPT, or they're even better with ChatGPT.”

“I think we were very, very lucky to be profitable from the start. So we didn't need the money. It always felt weird to give up control.”

“Things definitely hit an excellent point with ChatGPT because I think people just saw how Incredibly valuable human data and RHF was. So definitely chat CPT was an inflection point for us, but even before that we were, we had very strong growth.”

“We have hundreds of thousands, millions of people working on our platform.”

“You have a thousand projects, like 10,000 projects that are literally running in any given week.”