Max Welling @wellingmax
Joined November 2009-
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New episode of The Information Bottleneck is out 🥳🥳🥳 with Max Welling (@wellingmax ) Max is a legend and a personal hero of mine, so this one meant a lot. We got into which scientific problems ML can actually touch right now vs what's still too early, what the loop looks like when simulators, wet labs, and real experiments all feed back into each other, where the field is way too optimistic about generalization, and how you handle uncertainty when being wrong costs you a month in the lab. Also the academia → CuspAI shift and what it changed for him. One of my favorite conversations we've done.
There's more to our interview with @cusp_ai co-founder @wellingmax. Check out the full episode with AoT hosts Autria Godfrey, @stephenjhorn, and @Laila_Rizvi: youtu.be/QWjzHJHh_fw
@SuryaGanguli They will probably find something to complain about. The infinite retreat.
Beautiful work (and illustration) on super fast weather prediction by @maxxxzdn
🌍Today we release Mosaic, a probabilistic weather model that shifts the Pareto frontier of ML weather forecasting. It matches the skill of state-of-the-art models while generating a 24-member, 10-day global forecast in under 12 s on a single H100. Thread!
The candidates are now advancing to further development and testing. I am proud of the @cusp_ai team and excited by what this says about the future of materials discovery!
Today @cusp_ai and @KemiraGroup announce a milestone in AI-driven materials discovery. We have used generative AI to design new materials targeting PFAS removal from drinking and process water at trace concentrations.
Will AI Superintelligence Solve All the Problems in Materials Science? Not according to AI pioneer and @cusp_ai co-founder @wellingmax. He tells hosts Autria Godfrey, @stephenjhorn, and @Laila_Rizvi that he thinks human intuition and knowledge will remain very useful in creating new materials using AI. What do you think? Are you skeptical about what artificial superintelligence will mean for science? Tell us in the comments. Watch this short excerpt now, then check out the entire episode via the link in the first comment. #MaterialsScience #AISuperintelligence #AGI #FutureofAI #AIvsHuman
This is too funny not to share.
We put the paper online that provides further details (beyond my ICLR keynote) on the role of spontaneous symmetry breaking and Goldstone modes in deep learning. Enjoy! (w/ Nabil Iqbal, Thomas Andy Keller, Takeru Miyato and Yue Song.) arxiv.org/abs/2605.14685
@t_andy_keller @hansenlillemark @huskydogewoof Read this. It is deep and equivariant!
@FEijkelboom @jwvdm @osclsd @daan_roos_ @mmbronstein @ismaililkanc @LucaAmb And another brilliant paper by Floor!
@maxxxzdn Max (the other one) is on a roll!
@Sam_Duffield @HoldijkLars @iclr_conf @mmbronstein I am still thinking about that key equation too!
Watch the whole interview with Martin, a valued member of the @cusp_ai advisory board, on YouTube now: youtube.com/watch?v=iPKlc7…
He shares my belief that AI can help significantly reduce these learning cycles.
Introducing new materials into industrial processes can be a revolution for customers across industries. In the semiconductor space for example, a new, gamechanging material is introduced about once in a generation...
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