Chips, Neoclouds, and the Quest for AI Dominance with SemiAnalysis Founder and CEO Dylan Patel

**Sarah Guo** (0:06)
Hi, listeners, welcome back to No Priors. Today, I'm here with Dylan Patel, the Chief Analyst at SemiAnalysis, a leading source for anyone interested in chips and AI infrastructure. We talk about open-source models, the bottlenecks to building a data center the size of Manhattan, geopolitics and poker as a tell for entrepreneurship. Welcome, Dylan. Dylan, thank you so much for being here.

**Dylan Patel** (0:26)
Thank you for having me.

**Sarah Guo** (0:27)
I've been really looking forward to this conversation. You're such a deep thinker about this space. And then also, it's very odd. You clearly have the Samsung watch.

**SPEAKER_3** (0:35)
Yeah, I got the bling, I got the bling, I got the laptop, the Fold.

**Sarah Guo** (0:40)
Tell me more.

**Dylan Patel** (0:41)
So part of the origin story is that I was moderating forms when I was a child. And my dad's first Android phone was the Droid, right? And for some reason, I was obsessed with like messing with it, like rooting it, like underclocking it, improving the battery life, all these things, because when we're on a road trip, there's nothing to do besides like mess around on this phone. So I posted so much about Android that I became a moderator of slash r slash Android on Reddit and like many other subreddits related to hardware and Nvidia and Intel and all this stuff. But because of that, I've just always had Android. Now I've had work iPhones before, but I just really love Android. And then it's like, if you're going to like technology, I'm not like someone who pushes it, but like get the best stuff. So I have like the Ultra Samsung watch, which I think looks cool. And the folding phone, right? It's fun. It's obviously different and weird. No iMessage is a travesty.

**Sarah Guo** (1:28)
What does it dominate at? What is it better at? Besides the openness of like the hackability.

**Dylan Patel** (1:33)
I don't even hack that much stuff anymore, right? It's like, what do you use your phone for?
I think the main thing is like you can have like Slack and an email up on two different parts of your phone. I think that's probably the main thing. Or like you can actually use like a spreadsheet on a folding phone. You cannot use a spreadsheet on a regular phone.
And that's not even an Android thing. Like Apple's folding phone next year will be able to do that just fine. And I'll have no argument then. But I just like it. You know, people have their preferences. People are creatures of habit.

**Sarah Guo** (2:00)
You got to look at the GPU purchasing forecast on a sheet on your phone.

**Dylan Patel** (2:04)
Yes, I do. I do know. It's like someone's telling you numbers. You're like, wait, this is like slightly different than my number, right?

**Sarah Guo** (2:10)
OK, so we have a week of big rumored announcements coming up. Tell me your reaction to the OpenAI open source model.

**Dylan Patel** (2:18)
In theory, it's going to be amazing, right? Like I assume this is releasing after it's released or?

**SPEAKER_3** (2:24)
Yes.

**Dylan Patel** (2:25)
So that's OK. The open source model is amazing, guys. Like, I think the world is going to be really like shocked and excited. It's the first time America has had the best open source model in six months, nine months, a year. Llama 3.1 405B was the last time we had the best model. And then Mishra took over for a little bit. And I fired a car correctly, and then the Chinese labs have been dominating for the last like six, nine months. Right. So it'll be interesting. It'll also be funny because like the open source model probably won't be the best for just regular chat because it is like more reasoning focused and all these things. But it'll be really good at code. And it's I'm excited for that. Yeah. Like tool use, although that's like going to be confusing. Like, how do you use the tools if you don't have access to OpenAI's tool use stuff, but the model is trained to do so? That'll be interesting for people to figure out. I think the last thing is like the way they're rolling it out is really interesting. They accidentally leaked all the weights, but no one in the open source has figured out how to actually run inference on it because there's just some weird stuff in the model with the architecture, like for bed and like the biases and all this other stuff. But what's interesting is other companies drop the model weights and say, go make your own inference implementation. But OpenAI is like actually like dropping the model weights and like all these custom kernels for people to implement in inference. So everyone has a very optimized inference stack day one.