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AI for drug discovery has learned almost everything the existing experimental record can teach it. The next leap needs new data, and the laws of physics can supply it.

Potential Sciences is out of stealth to solve this problem, backed by @UKSovereignAI and @Twinpathvc.
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A deep, technical chat between Hatem and @CorinWagen: simulated data at coupled-cluster accuracy, lead optimisation, the hardware lottery and building in the UK with @UKSovereignAI.

Thanks @RowanSci for having us!
Yesterday, Potential Sciences came out of stealth to build a UK frontier lab for chemistry.

I spoke with Hatem Helal, Potential's CEO, about what they're building and why their simulation-first approach complements other AI-for-science teams.

rowansci.com/blog/a-convers…
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Our GPU-native engine runs CCSD(T), the gold standard of quantum chemistry, at 100x lower cost than traditional implementations.

We've raised eight figures in capital and compute to scale our dataset and train our first foundation models. In Wired: wired.com/story/finding-…
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