Chairman and CEO at Microsoft
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Our team's work in Nature this week. A great example of how AI is helping to accelerate molecular discovery.
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Custom-made molecules are advancing medicine, materials, and agriculture, but producing them is slow and expensive. A new Nature paper highlights RetroChimera, a predictive model that helps accelerate chemical synthesis, helping researchers explore a wide range of molecules.: https://msft.it/6045a5Odf
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Accélérer la découverte moléculaire, c’est explorer vite sans perdre la rigueur. Selon vous, quel est le premier signe qu’une IA comprend une molécule plutôt que de simplement la prédire ?
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Nature rivals nurture. That’s why we used nature to aid the the design of the Neural Forest paradigm.
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The "custom-made molecules are advancing medicine, materials, and agriculture, but producing them is slow and expensive" is the constraint that matters — the synthesis bottleneck is what limits how fast new molecules can get from design to application. The RetroChimera predictive model addresses the retrosynthesis problem, which is the planning step that currently takes expert chemists significant time. The Nature publication is the peer-review signal. Good to see the AI-for-science application with real validation.
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The slow, expensive part of a new medicine is often just working out how to make the molecule in the first place, so it's good to see that get easier. And expert chemists preferred its routes over the known ones, which isn't easy to pull off.
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Using machine learning to solve bottleneck problems in molecular discovery is where AI delivers its highest high-impact value. Reducing the time and expense of custom molecular design opens up massive potential for commercial R&D across healthcare and clean tech
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A brilliant demonstration of AI moving beyond software to tackle fundamental challenges in the physical world. Accelerating molecular synthesis from years to days will completely reshape drug discovery, materials engineering, and sustainable agriculture. Huge milestone for the Microsoft Research team
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The synthesis bottleneck is often what decides whether a promising molecule ever leaves the lab, so speeding up that step could matter a lot for costs downstream.
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It is refreshing to see how stepping away from the usual work environment can create space for reflection and fresh ideas. Moments in nature can strengthen creativity, perspective, and connection, which are valuable for teams navigating constant technological change.
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Worth noting where the work itself moves here. Retrosynthesis planning has been a step where expert judgment was the bottleneck, so compressing it doesn't remove the chemist - it shifts them from generating routes to evaluating and validating them. That migration of expertise from production to judgment is showing up across a lot of professions right now, and it's the pattern we track most closely at Work Futures Report.
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The real constraint is validation, so faster discovery still needs rigorous downstream testing.
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