Madison Maxey

The frontier of AI demands frontier-grade tools. That’s why Black Flag is working with Anthropic to give founders free credits and direct access to Claude - Anthropic’s family of state-of-the-art frontier models. Whether you're building intelligent agents, reasoning engines, or high-volume AI pipelines, Claude delivers: Opus for advanced intelligence and code reasoning Sonnet for hybrid performance and scalability Haiku for ultra-fast, cost-effective tasks Founders also get priority support, instant Tier 4 API access (no waitlist), and access to credits applicable across Anthropic's tools like Claude Code and their API. For those shaping the future of aerospace, biology, defense, energy, robotics and more: the future of software will be built with Claude. Only 1 day left to apply to Black Flag’s July batch! Fly the flag. 🏴‍☠️🏴‍☠️🏴‍☠️

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Hear why I warn that regulators will be watching the NVIDIA-OpenAI deal very closely… On this TWiST highlight, I am eager to dig into the details on Nvidia and OpenAI’s blockbuster, reportedly $100 billion new datacenter partnership. Some big questions remain: How are these funds being paid out, and over what kind of a timeframe? Is this an example of “round-tripping,” a questionable financial practice in which companies essentially move cash around? What, if anything, will the SEC have to say about all this? Hear me and Lon Harris unpack all this and more in a This Week in Startups exclusive clip.

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The era of AI-driven drug discovery is no longer coming, it’s here. For decades, biology was the domain of biologists. But today, some of the most important breakthroughs in drug discovery are being led by physicists, engineers, and computer scientists. Read the full piece here: https://lnkd.in/gNyauxZp Isomorphic Labs (a Google DeepMind's spinout powered by AlphaFold) recently raised $600 million to push its first drug candidates into clinical trials. This is a big moment. Not just for them, but for the entire pharmaceutical industry. With AlphaFold’s protein-structure predictions, we now have a computational foundation for drug discovery at scale. But here’s the key: we’ve seen this playbook before. Healx, which we’ve backed early via Propelx, already has three AI-discovered drug candidates in Phase 2 trials. Others like Recursion, Exscientia, and Insilico Medicine are also proving that AI-first pharma is here. The shift underway is massive. An industry worth trillions is being reshaped. What excites me most is that this isn’t about “AI hype.” It’s about real therapies, entering real trials, with the potential to deliver faster, cheaper, and more effective treatments for patients. At Calculus Venture Capital, we’ve been watching this transition closely, and we believe the most important drug discovery breakthroughs of the next decade won’t come from traditional labs. They’ll emerge from AI-native platforms. The future of biotech is already here. Read the full piece here: https://lnkd.in/gNyauxZp Image Credits: Michał Parzuchowski on Unsplash

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The robotics boom is here—but the stack is broken. Everyone’s racing to build humanoids and embodied agents, but no one’s clearly mapped how it all fits together. So we did in our latest piece at Lux Capital. ‍In this piece, developed with significant research, analysis, and writing by our brilliant graduate associate Ghazwa K.halatbari, we explore why morphology-agnostic intelligence—not anthropomorphic form—is the real unlock. We also introduce a first-of-its-kind Robotics tech stack: a layered map from data collection to deployment, showing where intelligence meets embodiment and how this field will unbundle. We challenge the humanoid fallacy: the assumption that the best robots must look like us. The truth? The future isn’t C-3PO - it’s R2-D2. Useful doesn’t mean human-shaped. It’s time to flip the paradigm: Don’t build a robot, then teach it to think. Build generalizable intelligence, then let it act across any form. From Physical Intelligence’s π0.5 to Roller Graspers, teleop pipelines to VLA models, this is our thesis on embodied AI—and where we believe the next wave of robotics value will be built. Check it out below—and if you're building, training, or deploying at any layer, let’s talk! https://lnkd.in/gugCanwk

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💊 Where are all the AI drugs? 🧐 There’s been a lot of noise lately about AI “revolutionizing” drug discovery. A recent WIRED article by Veronique Greenwood captured the optimism well — suggesting that with tools like large-scale automation and generative models, we’re finally starting to see real traction. The article is an interesting and insightful take, I suggest you read it (link in the comments). However, two cents from me here. The reality is more sober. Despite the hype, very few companies have actually gotten AI-generated drug candidates into human trials. Fewer still into Phase II. In fact, the article only names two: Recursion and Insilico Medicine. ☝And here’s where it gets interesting. One of those programs mentioned, REC-994 from Recursion, was actually an in-licensed molecule that’s since been deprioritized after mixed clinical results, as far as I know. That’s not exactly an AI-born success story IMO. That leaves only Insilico’s ISM001-055, for idiopathic pulmonary fibrosis . Not only is it AI-designed, it’s still active in Phase II, with multiple other candidates moving through the pipeline — from target discovery to clinical testing, all driven by their end-to-end platform 🔥. That’s a critical distinction. There’s a difference between using AI to support R&D and building a platform that can consistently generate novel compounds and push them through real-world validation. So yes, AI is making progress in biotech — but we’re early, and success is still super rare. Which is why what Insilico is doing stands out, in my opinion, not because I am an investor in the company, but because it is the objective reality from what I see on the market at this moment. And by the way, since we touched AI drug discovery, Insilico also quietly rolled out a set of pretty serious upgrades and they explain them in their recent PharmaAI webinar (linking in the comments). There, things like faster physics-based modeling (Alchemistry 2.0), better tools for peptide screening and biologics design, and new features in PandaOmics and DORA that make omics analysis and research writing faster and more usable. They even opened up access to several aging clocks through an open-source package. Kudos to Alex Zhavoronkov and Alex Aliper and the team for pushing the boundaries! 👏

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Pablos Holman funds what shouldn’t be possible. Not in labs with neat rows of test tubes. Not in boardrooms with PowerPoints. He builds it in the chaos where ideas meet code, and technology meets the impossible. He helped start Blue Origin for Jeff Bezos and the Intellectual Ventures Lab for Nathan Myhrvold. He didn’t just follow instructions. He invented technologies no one had thought possible, tackling some of the biggest challenges facing humans. “Most people look at technology and see tools. I see superpowers,” he says. “If we push hard enough, we can change everything humans do.” Pablos is a hacker in the truest sense. Fluent in everything about computers. Obsessed with zero to one. He’s not satisfied with incremental progress. He wants breakthroughs. He shares his explorations and conversations on The Deep Future Podcast, giving listeners access to the same ideas and debates that shape his own thinking. It’s not just about technology. It’s about making the future as awesome as possible. If you want to understand the frontier of human innovation and how technology can solve the world’s biggest problems, you’ll want to pay attention to Pablos.

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