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AI can now generate scientific ideas at scale. But we need to know if the current state of the art can bridge the gap to physical validation – the phase constrained by what can be tested, how fast, and at what cost. To find out, we have doubled our investment in the AI Scientist programme to £6m.
We're backing 12 projects to see if autonomous systems can reason, plan, and run experiments in the real world. These teams are testing the limits of automation on deliberately unforgiving problems: Alzheimer’s and cancer therapeutics, material discovery, and understanding the mechanisms behind battery degradation.
Instead of looking for best-case scenarios, we’re looking for limits. Can these systems recover when experiments fail? Can they reason across disciplines? Can they decide what not to try?
By doing this, we are learning what happens when machines are asked to do science, and exploring what that means for the future of discovery.
Discover the projects: link.aria.org.uk/AIscifpx

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