EPISODE · Oct 30, 2025 · 25 MIN
Season 4 Episode 3 | Bioptimus COO Mathilda Strom on AI, Compute, and the Future of Biological Foundation Models
from Humans In AI · host Nick Asbridge
Mathilda Strom, the Founding COO at Bioptimus, a company aiming to program biology from the ground upMathilda shares her journey from building startups across Africa, Asia, and Latin America to helping shape one of the most ambitious AI and biology projects on the planetWe explore: 💡 The true significance of building a multi-scale, multi-modal foundation model for biology🧬 Why training models on biological data is much more challenging than on text or language💰 The risks involved in investing millions in data that may become worthless within a year⚖️ How Bioptimus addresses ethics, diversity, and data integrity🤖 Why she’s establishing an agentic operations team and recruiting “AI Ops” specialists before most companies even know what they are🚀 Insights from scaling a deep tech startup, covering culture, onboarding, fundraising, and commercialisationAnd, for founders, Mathilda shares two lessons:- Choose your co-founders carefully; it can make or break your business.- And think hard about the capital you take. Bootstrap if you can.”This episode dives deep into the intersection of AI, biology, and entrepreneurship, and what it takes to lead when your mission is literally to understand how life worksSeason 4 of Humans in AI is here. This season, we’re switching things up. We’re still speaking with the brilliant founders and leaders driving innovation across AI, HPC, and GPU infrastructure, but this time, the focus is firmly on what’s happening right now. Tune in as we dive into the roles they’re in, the challenges they’re navigating, and the strategies that are actually working (and the ones that aren’t). Raw, relevant, and straight from the people building the AI ecosystem. New episodes of the Humans In AI podcast are released every Thursday, so make sure you tune in!
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Season 4 Episode 3 | Bioptimus COO Mathilda Strom on AI, Compute, and the Future of Biological Foundation Models
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