We’ve optimized kUPS specifically for GPU in collaboration with @nvidia , achieving up to 49× throughput over widely used software like RASPA for specific simulations.
@wellingmax
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Computational Scientists Face Workflow Friction in Molecular Modeling
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Whether it’s screening semiconductor materials or exploring drug-protein interactions, computational scientists hit the same wall: workflow friction and inefficiency. But modelling complex molecular phenomena shouldn't feel like a battle.
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Streamlining AI Workflows: GPU Efficiency and Integration Challenges
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Real-world applications usually require a clunky, fragmented workflow: Chaining disparate, complex packages
Writing hundreds of lines of configuration
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kUPS: Molecular Simulation Engine for AI Workflows
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Today at @iclr_conf 2026, I was excited to announce kUPS: a molecular simulation engine built for the AI era, optimized for GPU in collaboration with NVIDIA. kUPS is a plug-and-play, Python-native toolkit designed to integrate seamlessly with modern ML workflows.
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Max Welling AMA: AI and Materials Science Intersection
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Counting down until my
@Reddit #AMA later today with r/MachineLearning on the intersection of AI and materials science. I’ll be answering from 17.00 CET/16.00 BST/11.00 ET/08.00 PT. Start adding questions here: https://
reddit.com/r/MachineLearn
ing/comments/1skil2g/n_ama_announcement_max_welling_vaes_gnns/
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Machine Learning AMA on Reddit April 15th
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Excited to announce I’ll be on Reddit for an AMA r/MachineLearning on 15th April at 17:00 CEST/16:00 BST/11:00 ET/08:00 PT.
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ASML’s EUV Bet: Innovation Before AI Necessity
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Hindsight is a luxury, but the biggest innovations are rarely obvious at the start.
— Max Welling (@wellingmax) 1 avril 2026
I sat down with former @ASMLcompany President Martin van den Brink to discuss how they bet the company on EUV technology long before the AI boom made it essential. pic.twitter.com/vPR8fhX7Z9Hindsight is a luxury, but the biggest innovations are rarely obvious at the start. I sat down with former @ASMLcompany President Martin van den Brink to discuss how they bet the company on EUV technology long before the AI boom made it essential.
→ View original post on X — @wellingmax, 2026-04-01 11:32 UTC
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ASML’s Journey to Europe’s Most Valuable Tech Company
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Key takeaways: The science was clear, but the market justification took years. Despite delays, they never lost hope in a project that was win or die for the company. ASML is now Europe’s most valuable tech co ($525B+).
→ View original post on X — @wellingmax, 2026-04-01 11:32 UTC
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Physical Intelligence: Scientific Agents Accelerate Discovery at Software Speed
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Atoms (not bits) are the building blocks of our world.
— Chad Edwards (@ac_edwards_1) 23 mars 2026
We’ve moved past the digital frontier with physical intelligence.@cusp_ai's scientific agents now orchestrate entire discovery loops from initial query to physical realisation. Science is now moving at the speed of… pic.twitter.com/GucrKCUqBZAtoms (not bits) are the building blocks of our world. We’ve moved past the digital frontier with physical intelligence. @cusp_ai's scientific agents now orchestrate entire discovery loops from initial query to physical realisation. Science is now moving at the speed of software. Huge news incoming. The physical world is about to get a lot more intelligent.
→ View original post on X — @wellingmax, 2026-03-23 09:13 UTC
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Materials Science and Generative AI Revolutionize Scientific Discovery
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This was a very nice interview by Latent Space in sunny San Diego at Neurips. https://t.co/lHUta2ezG9
— Max Welling (@wellingmax) 26 février 2026This was a very nice interview by Latent Space in sunny San Diego at Neurips. Latent.Space (@latentspacepod) 🔬 New Science pod with @cusp_ai! We are entering a new era where materials science and discovery is transitioning from slow, manual experimentation, to a high-speed search problem powered by generative AI and "physics processing units." @wellingmax argues that the foundation of all modern technology—from GPUs to climate solutions—is a materials problem, and that unifying the mathematics of stochastic thermodynamics with generative AI will unlock a new paradigm of automated scientific discovery. — https://nitter.net/latentspacepod/status/2026716448626978955#m
→ View original post on X — @wellingmax, 2026-02-26 10:18 UTC