00:10:31 · John Coogan
[00:10:31] S0: Yeah. Pricing pressure. So they could limit these to state approved customers or Chinese government priorities, which at a certain level might just be the most important thing to do. The RSI loop, of course, you want all of the GPUs that you have focusing on advancing the frontier internally as opposed to sending it off to America. The talks come as The US is also moving toward tighter control of frontier AI. The Trump administration recently restricted access to Anthropics' most advanced models, Fable five and Mythos five, before later lifting some of those controls after additional safety mitigations. OpenAI has also reportedly faced government pressure around the rollout of its next frontier models. The issue has become more urgent because Chinese open weight models are increasingly competitive. Z dot ai's GLM 5.2, in particular, recently impressed Silicon Valley by performing close to leading U. S. Models at a much lower cost. The Quan family of models from Alibaba has also become one of the most important open model ecosystems in the world, while ByteDance's Daobao is one of China's most widely used domestic AI systems. I didn't know about that. If China places export controls on future frontier models, it could raise costs for American AI users and companies because it's obviously very beneficial to have a great open source model available to you and use them for lower stakes tasks while reserving expensive U. S. Frontier models for their most important workloads. If the best Chinese models are no longer freely available abroad, some of that cheap model supply disappears, but you have to ask what happens to Meta. Do other labs start piling back into the open source ecosystem and more? Or will all the demand just go straight back to the frontier labs?
00:12:14 · Jordi Hays, John Coogan, Alex Hormozi
[00:12:14] S1: It really sucks. [00:12:14] S0: That's the question. It really does. It really does. We should play some clips because [00:12:18] S1: We need to be thinking about podcast safety because this is an addictive [00:12:22] S0: There should be export controls on this. It should be only available to American citizens. [00:12:26] S1: They should Patrick even though [00:12:27] S0: I see. [00:12:28] S1: Even though one of the one of the the of the guys over [00:12:32] S3: there is [00:12:33] S1: is Canadian. [00:12:33] S0: Yes. But maybe maybe North America. Let's pull up a clip from this. I wanna I wanna hear Jeremy chat about all sorts of things. They they go all over. Where in the timeline is [00:12:44] S1: Well, should we talk about SK Hynix's new listing? [00:12:48] S0: Yes. We can run through that and then we can pull up [00:12:51] S1: SK Hynix is set to raise around 28,000,000,000 in a Nasdaq share sale this week, potentially one of the largest ever New York listings by an Asian company. The South Korean memory chipmaker is already public in Seoul, where its stock is up more than 750% over the past year. But The US listing gives American investors an easier way in. The story is big on the timeline because situational awareness, the hedge fund run by Leopold Aschenbrenner may participate alongside Bally, Gifford, and Co too. Together, the firms could take as much as 7,000,000,000 of the deal. SK Hynix has become one of the purest AI infrastructure plays because it leads in HBM, has become a key NVIDIA partner, and now has a market cap around 1,100,000,000,000.
00:12:51 · Jordi Hays, John Coogan, Tyler
[00:12:51] S1: SK Hynix is set to raise around 28,000,000,000 in a Nasdaq share sale this week, potentially one of the largest ever New York listings by an Asian company. The South Korean memory chipmaker is already public in Seoul, where its stock is up more than 750% over the past year. But The US listing gives American investors an easier way in. The story is big on the timeline because situational awareness, the hedge fund run by Leopold Aschenbrenner may participate alongside Bally, Gifford, and Co too. Together, the firms could take as much as 7,000,000,000 of the deal. SK Hynix has become one of the purest AI infrastructure plays because it leads in HBM, has become a key NVIDIA partner, and now has a market cap around 1,100,000,000,000. [00:13:35] S0: Which is like a quadrillion won. [00:13:37] S1: Yeah. That's a lot. [00:13:38] S0: When you look it up, it's very confusing, [00:13:39] S2: I think. [00:13:39] S1: It's a lot.
00:13:39 · Jordi Hays, John Coogan
[00:13:39] S1: It's a lot. [00:13:40] S0: The business ripping 2025 revenue grew 47% to 63,000,000,000. Profit more than doubled 28,000,000,000 in profit. Q one revenue tripled year over year. But interestingly, the stock only trades at seven x forward earnings because memory is brutally cyclical, and there's still a lot of people that are wondering what happens if there's another leg up in the AI demand and the AI build out. Will that mean more competitive pressure? Will it be a bottleneck where they do stagnate? How much can they actually grow? And so many investors that are just in memory have seen booms and busts from cloud or smartphone or crypto, and they say, like, I don't know that this one's gonna last forever. I'm pattern matching to previous cycles, not thinking about this as a different technology cycle. So I think that's what's going on with SK Hynix. But it should be a blockbuster IPO, nevertheless. Very interesting to see an Asian company listed [00:14:38] S1: And in America. Most, you know, notable Yeah. Part of this deal is is obviously situational awareness Yeah. And and their participation They in they cover They do. Best like the best, the billion dollar PDF Yes. Idea that that Jeremy and Patrick have talked about before. But situational awareness is turning out to be more of a maybe a ten or a hundred billion dollar PDF. [00:15:00] S0: Yeah. Seriously. And a whole investing thesis built around that. It's just a PDF. I I don't know. Is it an essay, a thesis?
00:15:00 · John Coogan, Tyler, Jordi Hays
[00:15:00] S0: Yeah. Seriously. And a whole investing thesis built around that. It's just a PDF. I I don't know. Is it an essay, a thesis? [00:15:07] S2: If if so, if the PDF was worth a billion or or more than that, what was the Door Cash episode worth? Oh. It's gotta be some percentage of it. Right? [00:15:14] S0: Yeah. Definitely. Because a lot of people watch the podcast, watch the clips, scroll through the PDF. It's also watching [00:15:19] S1: news. Meta unveils Muse Image. It's first image generation model from MSL. [00:15:24] S0: Waiting for this. Let's pull up some images of this and see the results. It should be good given that they have all the Instagram and Facebook data to train on. While we pull up some images of the new Muse image model for Meta, let me tell you about Figma. Agents meet the canvas. Your AI agents can now create and modify your Figma files with design system context. Do we have any of this or should we click over to Jeremy Gaffan? [00:15:53] S1: I am working on pulling up Muse Image. Let's Here we go. Go through Alex Wang as a host. Cool. Let's pull this up.
00:15:53 · Jordi Hays, John Coogan, Tyler
[00:15:53] S1: I am working on pulling up Muse Image. Let's Here we go. Go through Alex Wang as a host. Cool. Let's pull this up. [00:16:02] S0: Okay. Muse image, Muse video, Muse image, whole bunch of very detailed badges printed all in one image. He says releasing Muse image today, the first image generation model from MSL. It is crazy that they didn't have any, like back when it was fair, did they do anything with Image? Did they because they had that amazing model segment anything, so they were doing work on images, and, obviously, they processed a ton of images. It pairs with Muse Spark to reason through your prompts, search the web, and plan before it generates. People get what they mean on the first try live now in the Meta AI app. Very, very fun. Even puts a realistic QR code in there and can do infographics and old Polaroids as well. Big Sur, August 1983. Looks great. Three things Alex Wang is excited about under the hood. Self refinement. The model improves its own output within its chain of thought, emerged during RRL, not by design. Multi reference composition. Many images blended into one coherent generation. Multi turn editing. Iterate without losing coherence or starting over. Make an image of this person riding a bike, this bike, and wearing this suit while passing by these people on a park bench. Make it look like a drawing in this style. That's cool. So you can upload multiple images and sort of drop them in in his various prompts. What you got, Tyler? [00:17:28] S2: Yes. So Meta Fair did release a number of image models. [00:17:31] S0: Oh, really?