01:45:08 · Jordi Hays, Vineeta Agarwala
[01:45:08] S0: Can you give us the update on the drug pricing EO from, I don't know, was it six weeks ago, eight weeks ago? It feels like a year ago at this point. There's been a lot that happened. We had a bunch of people on the day of, and a lot of people were kind of saying that it wasn't going to be as impactful as it kind of felt in the moment, but what what's the update there? [01:45:30] S7: I don't think there's been a policy update. Like, you know, nothing has been enacted yet. That's still an EO. Yep. The the concept of it, of course, was to say was to use international trade as a backdrop for holistic negotiations inclusive of drug pricing to say, you know, as part of an overall tariff negotiation, why is it the case that The US pays two or three times or more for the same exact drug that another another country pays? And so that it is a logical question to ask, and, we know that CMS is continuing to ask that question. But the actual policy is gonna depend on quite a bit of, you know there are a number of moving parts and a holistic policy with respect to every other every other country. So it's important for us to retain huge incentives, and it's not gonna be as simple as cut the price, get great drugs. That's not how the market works. Yeah. But should the price be more equitably shared across countries, it's an absolutely reasonable perspective to have.
01:46:36 · John Coogan, Vineeta Agarwala, Jordi Hays
[01:46:36] S1: How popular is open source in the bio world? I feel like the Cursor for bio thing is very interesting. But when I think about the electronic lab notebooks that folks are using, like, if it's not open source, you can't fork it. And it feels like part of Cursor's ability to grow really fast was that they they sit on top of your code base and you can change IDEs very quickly. But if you're you if a researcher is using a closed source lab notebook that has a database built in, that company is gonna be like, no, no, no. Like, I do not want you just stealing all my customers or like migrating off. But are is open source popular? Are there opportunities? Like, what's the VS Code equivalent, I guess, would be the question? [01:47:23] S7: Yeah. I think there's a lot you know, in bio research, there's a lot more informatics and and less organized software. I think that will change. But historically historically, there is a lot of bespoke informatics, which is why some of the agentic adoption, like, for exploratory informatics research is happening on its own, and people are adopting open source agents for resources like that. You know, the structure the protein structure models like AlphaFold [01:47:53] S0: Sure.
01:47:53 · Jordi Hays, Vineeta Agarwala
[01:47:53] S0: Sure. [01:47:53] S7: Were followed by a number of models that were open sourced. And within a period of weeks, thousands of scientists, thousands of companies adopted, additional structure prediction models. Mhmm. Boltz two was a popular one. The Chai model. A number of startups put out open source models, and we saw really fast adoption, which is kinda cool. Right? It's like it's a scientist sitting in a company who says, I wanna try that, you know, and see if it would help my workflow. And, actually, I wanna benchmark it, and I wanna try three at the same time. So we didn't have that many great open source resources like that before we had datasets, but not necessarily models and APIs to those models that made them easy to use. So I think that that in that whole ecosystem is in its, like, square one infancy of growing and exploding, but you're gonna need a library of models. You want to be able to try all the models. You want your agents to be able to use the models without even a human interface. And so suddenly, the same thing that's happening in enterprise software in every vertical is gonna happen here too. You know? Agents on behalf of scientists will be able to select which models to use, try five models at once, and then incorporate the results and predictions of those models into a workflow, you know, that is deeply integrated with, you know, with other agentic automation. So it's none of that's built, I would say, for for the vast majority of the industry. And so it's a huge, huge opportunity for startups to build.
01:49:25 · Jordi Hays, Vineeta Agarwala, John Coogan, Casey Neistat
[01:49:25] S0: Yeah. Last quick question. Maybe if you could answer in in sixty seconds, that's the challenge. What what is the, what's the vibe on the Stanford campus right now? Are people dropping out of, you know, PhD programs to start companies in in bio? I'm sure we're seeing, people dropping out of PhDs to join meta and other AI research orgs broadly, but I'm curious if that's happening in in bio. [01:49:53] S7: There are a number of fast growing AI biotech startups, right, that are bringing AI and computational tools to model training. So we are seeing that. If you're asking, know, is it a response to federal funding changes? I think the you know, that's always been the case that a large fraction of trainees from university campuses end up in biotech and pharma companies, and that's great. It's a great outcome. I don't think you know, I do think there's probably, in the near term, going to be continued exploration of industry alternatives to federally funded research. And I really hope that there that the the, you know, federal grant funding is clarified and and and and that there's more stability on university campuses for federally funded research because some of that infrastructure is absolutely has been behind [01:50:45] S0: Shaking. [01:50:46] S7: A huge number of these of these innovations. [01:50:49] S0: Makes sense. Thank you so much for joining. [01:50:51] S1: Yeah. You [01:50:52] S0: so much. Great to chat. [01:50:53] S1: Talk to you soon. Cheers. [01:50:54] S6: Thank you.
01:50:54 · Casey Neistat, John Coogan, Micky Malka, Jordi Hays
[01:50:54] S6: Thank you. [01:50:55] S1: Next we have Mickey Malka, the founder of Ribbit Capital. Really quickly I will tell you about AdQuick. Out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising. Only ad quick combines technology out of home expertise and data to enable efficient seamless ad buying across the globe. And, we hopefully have Mickey Malka. How are doing Mickey? Good to meet you. [01:51:16] S8: Hi guys. Good to see you John and Jordi. How are you guys? [01:51:18] S1: Welcome to the stream. [01:51:19] S0: Great background. [01:51:20] S1: Yeah. What's going on background. Break it down for us. [01:51:23] S8: Those are some NFTs. Wonderful. From an artist called Bright Moments. They did a exhibition all over the world, and these are crypto citizens from the 10 cities around the world where they had their exhibitions. [01:51:35] S0: Amazing. Amazing. It's great to have you on the show. We've been excited for this. You guys have been on a absolutely crazy run and it's awesome that you're starting to talk about it a bit more. [01:51:46] S1: Yeah. I wanna start with like your background. I think that you might actually have a nontraditional path to venture or at least a very interesting entrepreneurial journey prior to launching a venture firm. So can you just give us a little bit of on your history and how you wound up running
01:51:46 · John Coogan, Micky Malka, Jordi Hays
[01:51:46] S1: Yeah. I wanna start with like your background. I think that you might actually have a nontraditional path to venture or at least a very interesting entrepreneurial journey prior to launching a venture firm. So can you just give us a little bit of on your history and how you wound up running [01:52:01] S8: Of course. Ribbit. So I'm an entrepreneur, and I'm still entrepreneur. It just happens that I started when I was 17 years old, and that's all I know how to do. And I started in financial services. Growing up in Venezuela in the early nineties, it was inflation, crises, bank failures, all the things that you need to learn in your life. I had them by the time I was 22 years old. [01:52:25] S0: Speedrun. [01:52:26] S8: Oh my god. Yes. Lightspeed through all of that. So I started four different companies around the world before the the word fintech or crypto even existed, always trying to do something in in around the Internet and making money better. Simply, that was the whole thing. [01:52:43] S0: And And what did and what did did some of those first companies look like? Were they specific to problems that you were having in in Venezuela, or were they global by nature? I I love some advice.