Google/DeepMind

Latest AI news, models and releases from Google/DeepMind. ['A2UI v0.9', 'AI Co-Scientist', 'AI Evaluator', 'AI Mode', 'AI Overviews', 'AlphaEvolve', 'AlphaFold', 'AlphaGenome', 'AlphaQubit', 'Antigravity', 'Auto frame', 'BERT', 'Chinchilla', 'Computational Discovery', 'Confidential GKE Nodes', 'Co-Scientist', 'Empirical Research Assistance', 'Era', 'ERA', 'Executive LLM', 'Farmscapes 2020', 'Flood Hub', 'frontier AI', 'Frozen v2', 'FunctionGemma', 'Gemini', 'Gemini 1.5 Flash', 'Gemini-1.5-pro', 'Gemini 1.5 Pro', 'Gemini 2.0 Flash', 'Gemini 2.5', 'Gemini 2.5 Flash', 'Gemini-2.5 Flash', 'Gemini-2.5-Flash', 'gemini-2.5-flash-image', 'Gemini 2.5 Pro', 'Gemini-2.5 Pro', 'Gemini-2.5-Pro', 'Gemini 3.1 Flash', 'gemini-3.1-flash-image']

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Research 🇺🇸

Simula: A Framework for Designing Synthetic Datasets Based on Mechanisms and Reasoning

Google Research introduces Simula, a framework that reframes synthetic data generation as dataset-level mechanism design. It uses reasoning-first methodology to construct entire datasets from first principles, enabling fine-grained control over coverage, complexity, and quality. Simula has been a key enabler for the Gemma ecosystem and safety classifiers at Google.

Google/DeepMind

Google Research27.07 · 15:05

Research 🇺🇸

ReasoningBank: A Memory Framework for AI Agents Learning from Successes and Failures

Google researchers propose ReasoningBank, a novel agent memory framework that distills generalizable reasoning strategies from both successful and failed experiences, enabling continuous learning after deployment. Evaluated on web browsing and software engineering benchmarks, it improves agent effectiveness and efficiency. The framework uses memory-aware test-time scaling (MaTTS) to leverage exploration trajectories.

Google/DeepMind

Google Research27.07 · 15:05

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