The Exchanges

Q What was your first story? How did you, how did you get started covering?

A Yeah, I mean, I think, I mean, I'm sure that my first story was probably just, like, some silly, like, write-up of, like, a report or something, but I think the first story I remember doing about AI was during summer, 22. I, I live in New York, so every couple months I go visit SF, and specifically on that trip I went, and everyone was like, oh my god, let me show you this, like, funny app called Dolly, and, like, we're gonna make pictures of, like, cats floating in space, and it's, like, so funny and cool, and then it just started to come up in so many conversations that I was like, huh, like, this is, like, a fun Little trend. Like, maybe I should write something about it. So then I ended up doing a piece that was, like, why VCs are obsessed with, like, this new area called generative AI. And then obviously, like, three months later, it was, like, blown up and Chat TVT was, was released. Um, but yeah, I remember that was my, like, first generative AI-specific piece that I did, which was, like, honestly kind of just, like, an accident. Like, I just happened to talk with a bunch of VCs who were excited about it. Um, but yeah, and then ever since then, I've been, been covering the space, so.

AI assessment note: “I think the first story I remember doing about AI was during summer, 22.”

Q What's the high level take for people kind of out of the loop?

A Yes. The high level take. So yes, basically sure. A lot of your listeners already know this, but these inference providers are companies that are, you know, helping developers like run and train and, Customize open source AI models more easily than they would be able to otherwise. And so, yeah, there's just so many companies in the space. You mentioned some of them, Fireworks, Modal, there's Together, there's Base 10. There's just a ton of these companies in the space. And so, yeah, FAL is another one. Yes. Um, and so, yeah, it's, it's very interesting because a lot of these companies have gotten so much funding, but there's still a lot of like skepticism around this space and like whether these companies are actually going to end up being like, you know, like Billions or trillions of dollars, like trillion dollar company. Um, so I think a lot of people like think, basically just call these companies like GPU resellers. So they're just like, oh, all you're doing is just being like a cloud basically. You know, helping developers get access to chips to run models on. So you're like a knockoff Amazon or like a knockoff like Azure or Google cloud, um, which is like a bit derogatory. But I think that's kind of like what the con argument, that's like the argument against them. Um, because also unlike software companies, they have to like spend so much money getting the, you know, get…

AI assessment note: “these inference providers are companies that are, you know, helping developers like run and train”

Q Okay, cool. Before we move on from meta, I just want to, you know, leave the door open. Any other themes that you're watching, uh, on, on the meta side?

A Yeah, I mean, I think we definitely covered a lot of the really interesting ones. I think, I mean, one thing that I think, like, Mark has even kind of touched on recently is whether they'll continue open sourcing models, whether they're going to start closed sourcing stuff, and, like, what does that mean for its business model? Because obviously, like, like right now, you know, Meta doesn't make money from an API the way that, like, OpenAI and Anthropet does, but if they start closed sourcing models, maybe that might change, or That could change kind of the shape of the way that they think about how to make money from this, and so, yeah, I think that's very interesting, and I don't know, I think for me as a consumer, like, I'm always really interested in, like, consumer AI, because I feel like there's not really as much coverage on it as I would like, and, like, I personally, I use a lot of AI stuff, but nothing that's, like, truly kind of transformed my, like, non-work-related life, so I'm very curious, like, what meta will come out with, with consumer AI.

AI assessment note: “whether they'll continue open sourcing models, whether they're going to start closed sourcing stuff”

Q at, um, at Google, but like, you know, there was some kind of revesting thing going on. Uh, yeah, cool. Any other sort of, uh, uh, coding agents commentaries while we're still on the sort of coding topic? Anything else you're watching? How do you cover Uh, I, I guess like coding in general, if, if you're, you know, out in, in New York and, you know, we're over here.

A Yeah. If I'm not, if I'm not like a developer and I'm like trying to understand what the heck is going on with coding startups. Yeah. Yeah. I mean, I think a lot of it is just like finding sources and developers that I really trust and like being very straight up with them and being like, Hey, I, like, I'm not a developer, but, like, show me a couple examples of things that you built with this, like, tell me your opinions about what they're good for or not good for. I think, like, one thing I'm interested in is, like, the rise of some of these, like, open source coding assistants, like Klein, which I, I know was on your podcast.

AI assessment note: “finding sources and developers that I really trust and like being very straight up”

Q hits that you're, um, that, you know, you, you want to talk about? Like, I don't get a sense of like what your biggest hit is or your general sort of Thematic overview, if that, if that makes sense. You know, there's like robots, there's XAI, there's perplexity, there's all these other things. Uh, what, what stands out to you as something that you really want to, uh, chat about?

A Yeah. I mean, I guess two things. I think first, like, the first thing is like, I think this is what I'm most interested in, but, um, I did kind of touch on it with like our conversation about GPT-Five, but just like the trajectory of AI progress and kind of like, you know, First, there was, like, pre-training scaling, and then now there's, like, reasoning models and reinforcement learning. Then, like, what comes after that? Like, is it RL environments for agents? Is it something that's different than the transformer? Like, I think we're always curious just, like, what is coming next? And I mean, I like, I think that's why I'd love to talk to more people at the big AI labs, because I feel like they're really on the forefront of that.

AI assessment note: “just like the trajectory of AI progress and kind of like, you know”

Q a coding oriented lab? They, you know, they, they, they made some movements on financial services and, and, uh, you know, other, other verticals, like maybe defense, but I think coding is obviously a very key battlegrounds. Like we just talked about how GPT-V is maybe opening eyes and pushing back on cloud code and Sonnet and Opus. But is that a big part of the conversations that you're having?

A Yeah, definitely. I mean, it definitely feels like Anthropic has decided that coding is kind of their, like, battleground, and I mean, so far they've been doing really well. I think, like, one thing I've heard, and I'd be curious, like, I think, like, I'm not a developer, obviously, so I'd be curious if this is your opinion as well, but, like, I think one thing that developers have told me is that, like, one reason why they, like, clawed for coding so much is because it's not only good at, kind of, like, competitive or academic programming tasks, but it's also, like, These more, like, soft skill type things, or not, not soft skills, but more, like, more practical everyday things that they're good at, like working with, you know, huge code bases that have lots of, like, old legacy code in them, or just even being, like, persistent with solving a coding problem, and realizing, like, hey, I've tried x thing, like, three times, and it hasn't worked, so, like, let me try something different. So it kind of feels, like, as scientific as, like, code feels, like, it seems, like, behind the scenes at Anthropic, there's a lot of, like, It's like a like more kind of like art than science. Like there's a lot of like shaping of the model that is happening to help with kind of what engineers deal with during their day to day versus more like academic, you know, competitive programming questio…

AI assessment note: “Yeah, definitely. I mean, it definitely feels like Anthropic has decided that coding is kind of their”