Powering scientific discovery with AI
Accelerate your research with AI tools and resources built to support scientific endeavors. From literature synthesis to hypothesis generation and computational discovery, Gemini for Science helps researchers tackle complex questions faster and with stronger evidence.
Gemini for Science is purpose-built for researchers who need grounded evidence, testable plans, and repeatable workflows — not generic chat. The stack combines frontier models with science-specific tools that map claims back to sources and score ideas against real metrics.
Synthesize scholarly literature and extract paper data into queryable tables mapped directly to source evidence, so every insight stays traceable.
Simulate the scientific method with agents that identify knowledge gaps and propose testable research plans instead of open-ended speculation.
Generate and score code variations against your optimization metrics to discover models and algorithms that accelerate experimental work.
Orchestrate frontier models and unified scientific resources to condense multi-step analysis pipelines that normally take hours into minutes.
Literature review, gap analysis, hypothesis drafting, experiment design, and computational scoring connect in one research loop — so teams spend less time stitching tools and more time validating ideas.
Science experimental tools on Google Labs explore how frontier AI can support real research workflows. Each experiment targets a distinct phase of discovery — from reading the literature to proposing and testing new ideas.
Identify new research opportunities, create grounded research artifacts, and extract paper data into queryable tables mapped directly to source evidence.
Use a multi-agent system that simulates the scientific method to identify knowledge gaps and propose testable research plans for breakthrough discoveries.
Leverage an agentic research engine that generates and scores code variations based on your optimization metrics to accelerate your research.
Turn Google Antigravity into a workbench by orchestrating frontier models and unified scientific resources for complex multi-step analysis.
Gemini for Science keeps the research cycle legible: one clear question, grounded sources, scored hypotheses, and reproducible computational steps — so teams can compare ideas under the same constraints.
Start with a well-scoped scientific problem and define what evidence or metrics will count as progress.
Use Literature Insights to map prior work, surface gaps, and build queryable tables tied to primary sources.
Run multi-agent hypothesis generation to propose testable directions and prioritize plans with the strongest support.
Score code and model variations against your metrics, keep winning approaches, and iterate with Antigravity orchestration.
We believe AI can empower researchers to tackle some of the world's most pressing challenges. Gemini for Science turns research judgment into something repeatable — proposing ideas, grounding them in evidence, and testing them under consistent constraints.
Claims stay linked to papers and datasets so teams can audit reasoning before committing lab time.
Multi-agent workflows favor plans you can measure, not vague suggestions that never reach experiment design.
Agentic engines rank code and model candidates against your metrics so improvements are comparable run to run.
Antigravity science skills condense hours of manual orchestration into minutes for complex analyses.
These tools are already assisting in real-world discovery. From combating antimicrobial resistance to optimizing fabrication methods for crystal growth, leading experts use AI to accelerate a new era of discovery.
Co-Scientist helps leading experts develop new hypotheses and tackle some of the hardest problems in modern research.
Ben Luisi's lab uses a suite of AI tools to target two essential bacterial processes at once, creating a powerful new way to fight superbugs without triggering further resistance.
Deep Think mode helped solve a complex materials challenge: optimizing fabrication methods for crystal growth in 2D semiconductors.
Lisa Carbone used Deep Think mode to review a specialized paper in high-energy physics and infinite-dimensional algebra.
Anupam Pathak tested Deep Think mode to accelerate the design and prototyping of complex physical components.
Scale your research and sharpen your reasoning with modes built for depth — from long-form literature review to rigorous scientific and engineering problem solving.
Save hours of work with Deep Research as your assistant for synthesizing sources, comparing findings, and producing structured reports.
By blending deep scientific knowledge with everyday engineering utility, Deep Think mode moves beyond abstract theory to drive practical applications.
Gemini for Science is Google's initiative to power scientific discovery with AI. It includes experimental tools on Google Labs — Literature Insights, Hypothesis Generation, and Computational Discovery — plus specialized Gemini modes like Deep Research and Deep Think for researchers.
They are a collection of experiments exploring AI-powered scientific discovery: Literature Insights for synthesizing papers, Hypothesis Generation for testable research plans, and Computational Discovery for scoring code and model variations against your metrics.
Literature Insights synthesizes scholarly literature to identify new research opportunities, creates grounded research artifacts, and extracts paper data into queryable tables mapped directly to source evidence so claims remain auditable.
Hypothesis Generation uses a multi-agent system that simulates the scientific method to identify knowledge gaps and propose testable research plans — helping teams move from open questions to experiment-ready directions.
Computational Discovery is an agentic research engine that generates and scores code variations based on your optimization metrics, helping you discover models and algorithms that accelerate research.
Co-Scientist puts advanced AI into the hands of real scientists to help experts develop new hypotheses and tackle some of the hardest problems in fields from biology to materials science and mathematics.
Gemini Deep Research acts as a personal research assistant for synthesizing literature and producing structured reports. Gemini Deep Think blends deep scientific knowledge with engineering utility to solve rigorous technical problems and drive practical applications.
Science skills in Google Antigravity turn the platform into a professional scientific workbench by orchestrating frontier models and unified scientific resources, condensing complex multi-step analysis pipelines that normally take hours into minutes.
Explore experimental science tools and specialized Gemini capabilities built for discovery.
Explore Science Experimental ToolsEvery major claim on this page reflects publicly described Gemini for Science capabilities from Google AI.
Official overview of science tools, case studies, and specialized Gemini modes.
Literature Insights, Hypothesis Generation, and Computational Discovery experiments.
Turn Antigravity into a scientific workbench for multi-step analysis pipelines.