For centuries, the scientific method has been our best tool for progress.
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For centuries, the scientific method has been our best tool for progress. But today, there’s so much data out there that it’s impossible for any one researcher to connect all the dots. We want to fix that: Introducing Gemini for Science, a collection of science tools and experiments designed to accelerate the speed and scale of scientific exploration. Read on to learn more about each announcement in this inaugural set 🧵👇
We’re rolling out 3 new experimental tools to help scientists skip the busywork and focus on big ideas: 💡 Hypothesis Generation built with Co-Scientist: to discover & refine new ideas 💻 Computational Discovery built with AlphaEvolve and ERA: to test novel modeling approaches by running thousands of code variations at once 📚 Literature Insights built with @NotebookLM: to identify research gaps and opportunities by quickly synthesizing scientific papers If you're a researcher, you can sign up to try them here: https://t.co/mtuwE8kYdT
We are also launching Science Skills, a specialized bundle that integrates insights from 30+ major life science models and databases with agentic platforms like @Antigravity to allow researchers to perform complex, manual workflows in minutes. To learn more on how to use Science Skills visit: https://t.co/1r9vxWaFdi
We're building Gemini for Science with and for the scientific community. In collaboration with 100+ institutions and a trusted tester community that ranges from PhD students to Nobel laureates, we want to make sure this tech is responsible and rigorous enough to tackle real-world problems. Read the full update here: https://t.co/lEZ5MBhgdJ
Context
Gemini for Science includes an experimental tool for exploring more computational approaches to a research problem. As Google AI describes it, Computational Discovery combines AlphaEvolve and ERA to generate and score thousands of code variations in parallel. Researchers can use that search to investigate alternative modeling approaches, including in fields such as solar forecasting and epidemiology. Primary explanation.
Its intended contribution is to expand the computational experiments a researcher can examine. The announcement presents it as a prototype with gradually opening access, so its useful promise is broader exploration under a researcher's direction.
- AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
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