At last week's National Academy of Engineering Annual Meeting, experts discussed promising new opportunities for accelerating scientific discovery as well as the importance of considering how new technologies can affect society, often in unpredictable ways. DOE's Darío Gil discussed the newly launched Genesis Mission — an ambitious project that aims to harness AI, scientific data, and supercomputing to accelerate research and discovery — while historian Ruth Cowan drew on the history of the automobile to illustrate what she called the first law of the late historian Melvin Kranzberg: “Technology is neither good nor bad, nor is it neutral.” Explore these conversations and more takeaways from the meeting: https://ow.ly/IEbj50ZYuXE #ArtificialIntelligence #ScientificDiscovery #Engineering #Innovation
The National Academies of Sciences, Engineering, and Medicine’s Post
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Proud to see our Co-Founder David Brown in Mainz this week for the Nobel Turing Challenge Workshop, alongside Andrew Hopkins and Hermann Hauser, who backed Healx from the very beginning. The questions on the table are big ones: who owns a discovery made by AI, and what happens to the economics of science when discovery becomes an industrial process? I'm looking forward to hearing how the conversation unfolds. #AI #DrugDiscovery #RareDisease
Our Co-Founder and Board Member David Brown has been invited to the Nobel Turing Challenge Workshop being held in Mainz, Germany, from 5 - 7 October. Launched in 2020, the Challenge asks whether AI systems can make Nobel-level scientific discoveries autonomously by 2050. With rapid advances in scientific foundation models, agentic AI and self driving laboratories, the workshop will explore whether the timeline may be closer than originally anticipated. Today, Dave will join Andrew Hopkins for a session on commercialisation, chaired by Hermann Hauser on “Commercialisation: The Coming Scientific Gold Rush?”. Through Amadeus Capital Partners, Hermann led Healx’s £1.5m Series A funding round in 2016 and has been a longtime champion of our work. The discussion will explore some fundamental questions for the future of AI-driven discovery including: Who owns discoveries made substantially by AI? What should remain proprietary? And what happens to the economics of discovery when it becomes an industrial process? The workshop takes inspiration from the 1927 Solvay Conference, with short provocations followed by open discussion. Sessions will be recorded with participants' agreement to create a historical record of the conversations. #NobelTuringChallenge #AIforScience #DrugDiscovery #OpenScience
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Generative AI-designed catalysts Imagine a catalyst that designs itself—AI is turning that sci‑fi fantasy into lab reality! By harnessing generative AI, researchers can virtually explore millions of catalyst structures in days, pinpointing atoms that boost reaction speed. These AI‑crafted catalysts have already outperformed traditional metals in hydrogen production and CO₂ conversion, slashing energy costs. The approach accelerates discovery cycles, letting chemists move from trial‑and‑error to data‑driven design. #AI #Catalysis #GreenChem #Innovation #ScienceBuzz
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Generative AI-designed catalysts Imagine a catalyst that designs itself—AI is turning that sci‑fi fantasy into lab reality! By harnessing generative AI, researchers can virtually explore millions of catalyst structures in days, pinpointing atoms that boost reaction speed. These AI‑crafted catalysts have already outperformed traditional metals in hydrogen production and CO₂ conversion, slashing energy costs. The approach accelerates discovery cycles, letting chemists move from trial‑and‑error to data‑driven design. #AI #Catalysis #GreenChem #Innovation #ScienceBuzz
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Generative AI-designed catalysts Imagine a catalyst that designs itself—AI is turning that sci‑fi fantasy into lab reality! By harnessing generative AI, researchers can virtually explore millions of catalyst structures in days, pinpointing atoms that boost reaction speed. These AI‑crafted catalysts have already outperformed traditional metals in hydrogen production and CO₂ conversion, slashing energy costs. The approach accelerates discovery cycles, letting chemists move from trial‑and‑error to data‑driven design. #AI #Catalysis #GreenChem #Innovation #ScienceBuzz
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Generative AI-designed catalysts Imagine a catalyst that designs itself—AI is turning that sci‑fi fantasy into lab reality! By harnessing generative AI, researchers can virtually explore millions of catalyst structures in days, pinpointing atoms that boost reaction speed. These AI‑crafted catalysts have already outperformed traditional metals in hydrogen production and CO₂ conversion, slashing energy costs. The approach accelerates discovery cycles, letting chemists move from trial‑and‑error to data‑driven design. #AI #Catalysis #GreenChem #Innovation #ScienceBuzz
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The Genesis Mission framing is useful because the bottleneck in AI-accelerated science is often less the models than the data. Much of what federally funded labs generate sits in formats, repositories and access agreements that were never built to be pooled, and grant budgets rarely cover the curation work that would make it usable. If agencies want AI to speed discovery, data management plans need to be treated as real deliverables with funding behind them, not an attachment checked at submission. Kranzberg's point applies there too: shared datasets raise questions about consent, security and credit that are easier to settle up front than after the fact.