@GoogleDeepMind: Computational Discovery An agentic prototype built with AlphaEvolve and Empirical Research Assistance to develop and sc…
Summary
Google DeepMind introduces a computational discovery prototype that uses AlphaEvolve and Empirical Research Assistance to develop and score thousands of code variations in parallel, enabling faster testing of modelling approaches for epidemiology.
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3️⃣ Computational Discovery
An agentic prototype built with AlphaEvolve and Empirical Research Assistance to develop and score thousands of code variations in parallel.
This can enable testing of new modelling approaches for complex fields like epidemiology in a fraction of the https://t.co/aGdZAetmri
We want to help scientists discover their next breakthrough with AI.
Gemini for Science is our new suite of experimental tools to help them explore more hypotheses, validate work at scale, unpack literature with ease, and more
We’re first rolling out 3 new experimental tools in @GoogleLabs to help scientists discover new research directions.
Literature Insights
Built with @NotebookLM, it searches scientific papers, organises everything into custom tables, and lets researchers chat with curated data to create slide decks, audio overviews, and more in minutes.
Hypothesis Generation
Built with Co-Scientist, this system can help brainstorm and evaluate novel research ideas for open challenges.
Using a multi-agent “idea tournament”, the system generates, debates and evaluates hypotheses to show what works, what doesn’t, and why.
Computational Discovery
An agentic prototype built with AlphaEvolve and Empirical Research Assistance to develop and score thousands of code variations in parallel.
This can enable testing of new modelling approaches for complex fields like epidemiology in a fraction of the usual time.
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