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Google upgraded NotebookLM with Gemini 3.5, an isolated cloud computer, more than 100 agentic skills, and structured outputs including charts, spreadsheets, and slides.
Why it matters: Research assistants are evolving from source-grounded chat into artifact-producing agents with execution environments.
Google introduced three experimental Gemini for Science tools: Co-Scientist-based hypothesis tournaments, AlphaEvolve and ERA computational discovery, and NotebookLM literature analysis. It also released Science Skills connecting Antigravity to more than 30 life-science databases and tools; related ERA and Co-Scientist work appeared in Nature.
Why it matters: Research agents are moving beyond literature summaries into competing hypotheses, parallel computational experiments and structured evidence review.
Google's Gemini Notebooks now roll out to all Workspace customers, schools, organizations, Workspace Individual and personal accounts, with administrators controlling access. Google also added Expert Intelligence, allowing eligible users to ground notebooks in more than 100,000 licensed books they own through Google Play Books.
Why it matters: Persistent project context is now an organization-wide managed surface, and licensed books can become retrieval sources. Administrators need explicit service controls while users need to distinguish owned-source grounding from general model knowledge.
Google introduced an upgraded Gemini Deep Think mode for difficult science and engineering problems, then released Gemini 3.1 Pro in preview across developer, cloud and consumer surfaces. Deep Think targeted Google AI Ultra subscribers and select API users, while 3.1 Pro became the broadly testable foundation for complex reasoning and agent workflows.
Why it matters: Reasoning is becoming a configurable service tier. Teams can use a general model for most work and reserve expensive multi-path inference for problems where extra search and verification improve the answer.