This Week in Startups
00:04:39 · Lon Harris, Alex Wilhelm
[00:04:39] S2: So spoilers for her. Sorry, everybody. I feel like that's always the fictional narrative around AI, and I do feel like that has an impact on real world AI CEOs, and they're trying to be part of that narrative and play into that narrative because it's a helpful narrative for them. We're creating iconic, legendary, history shaping technology that's akin to the atomic bomb or the discovery of electricity. And I mean, like, it plays into a friendly narrative if you're the CEO of an AI company. [00:05:11] S1: That's absolutely true. No, you're not wrong. I just think that AI has put up enough in terms of real results, real progress, real products, real services, that to me, we're just talking about how correct they are versus how incorrect they are when they make those large pronouncements. But I do think the context here is that OpenAI is expected to release their open weights model, their kind of open source ish project sometime soon. And then GPT-five is anticipated, we think, sometime in August, which means that we're gonna get past the hype and more into the testing. So, you know, will GBT5 be as good as it's expected to be? Well, we're gonna have to find out pretty soon, and that's encouraging. [00:05:49] S2: Pretty soon. In fact, the media is sort of saying, you know, early August or sometime in August, the Sharps at Polymarket, of course. [00:05:58] S1: Yeah. Yeah. We were looking at this.
00:05:58 · Alex Wilhelm, Lon Harris, Jonathan Siddarth
[00:05:58] S1: Yeah. Yeah. We were looking at this. [00:06:00] S2: Yeah. Not content to wait, and see what happens. There's already, of course, wagering going on. There's already a market going on for this. 25% are betting that by August 5, which is early next week. That would be... We are right on the verge of GPT five being here. [00:06:17] S0: Yeah. [00:06:18] S2: One in four. [00:06:20] S1: Yeah. One in four chance. And then by by August 15, people think it's a two thirds chance that it's out. So I... My read of this line is that, basically, middle August is kind of the over under, and that after that will be a surprise. Earlier than that will be a surprise, but we're only a couple weeks away. That's what's exciting to me. That's the cool thing. Remember how exciting it was when x AI dropped Grok four, and they talked about Grok four heavy and then the Grok four coding? Then we got the Kimi k two family of models from Moonshot. Then we got the z dot ai. Mhmm. I forget. The GLM 4.5 series. It is... The point is it's been a flurry of models, and Alibaba's Quinn models are improving. [00:06:54] S2: Yeah. We're in the middle of that meme that you are here, the world's greatest AI model. Like, we're we're right in the middle of another cycle. Yeah.
00:06:54 · Lon Harris, Alex Wilhelm
[00:06:54] S2: Yeah. We're in the middle of that meme that you are here, the world's greatest AI model. Like, we're we're right in the middle of another cycle. Yeah. [00:07:03] S1: But the question is, will this be just another iterative improvement? And if so, OpenAI is going to take a lot of egg on its face, or is it as big of a jump as maybe GPT three to four was or larger? And if that's the case, it does change the entire fabric and and landscape that the technology world, plays on. But, Lon, let's talk to some founders. [00:07:23] S2: I love it. Let's do it.
00:07:25 · Alex Wilhelm
[00:07:25] S1: Alright. So we have three interviews for you today. One, Cortical, then we're gonna talk to Turing, and then we're gonna talk to Merkor. Each one of these was an absolute treat. Cortical is probably the most out there in that we're talking about, kind of, like, hybrid biologic and digital computers. It's, it... It's an interview I I chased on for a long time. It's super fun. And then turning to Merkur, a bit more traditional in the software space, but incredibly interesting founders, incredibly interesting companies. And especially, I think, the case of Merkur, a a a vision for a company that could become incredibly instrumental to how labor functions in the future. So these are a treat. I had a blast. Please enjoy them, and say hello to three of our founders from the Twist five hundred. Hey. Welcome back to Twist. This is Alex. Today, we have another Twist five hundred interview with a company that has been my white whale for several months, but I'm so glad to have them on the show. We're going to talk about cortical labs. Now here at Twist, we love chips. We love talking about what Grok is building to handle AI inference. We loved that Etched is building ASICs just for LLMs. We've talked to XTropic and their thermodynamic computing paradigm, but all that's entirely silicon based, more or less. Cortical wants to bring the world of biology to the world of computing in a way that when I first heard about it, I thought was science fiction, but they've taken it out of the lab, and they're commercializing it. So please join me in welcoming to the show. It's Cortical Labs CEO and cofounder, Han Wangchong. Han, how you doing?
00:08:51 · Hon Weng Chong, Alex Wilhelm
[00:08:51] S3: Hi. Good. Thanks. Thanks for having me on the show, Alex. [00:08:53] S1: I'm so excited. Okay. So you guys are fusing biology and, I would say, digital computing in a way that's really interesting. But I think to help everyone understand how you got to where you are today, we should go back to the earlier days of the company when you guys were experimenting with your technology, and you used it not to play Grand Theft Auto as everyone wants to do with generative AI, but instead to play Pong. So, Han, can you tell me about why you chose that and then how the experiment went to prove out what Cortical Labs wants to build? [00:09:24] S3: Yeah. So if you take a few steps back to, I guess, 2018... 2017, 2018, there was a... I guess the first AI boom that happened that was, I would call it the convolutional neural network reinforcement learning boom. I had just exited from my last business and as part of that, it was a med tech business that gathered a lot of data. And I was looking at using machine learning to do automated diagnostics and really got deep into the rabbit hole of machine learning and artificial intelligence. And I came across a paper written by Suru Demasuras Sabes from DeepMind, who wrote that the machine learning and AI community had to go back to its roots in neuroscience because that's where most of the initial discoveries were made.
00:10:23 · S4
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