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', 'BioBERT', 'Chinchilla', 'ClinicalBERT', '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']

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Research 🇺🇸

Linear Elastic Caching: A New Approach to Cache Management Optimizes Cloud Costs

Google Research and Google Cloud have introduced linear elastic caching, a method that dynamically adjusts cache size to minimize total cost. By framing page eviction as a ski rental problem and using a lightweight machine learning model, the approach reduced memory use by up to 30% in Spanner production servers with only a 0.5% increase in I/O costs.

Google/DeepMind

Google Research27.07 · 09:06

Harnesses 🇷🇺

Context Engineering: What It Is, How to Work with LLM Agent Context, and Why You Get Paid for It

Context engineering is a set of techniques for collecting and maintaining optimal context when working with LLMs. It differs from prompt engineering (which only handles instructions) and complements RAG (knowledge delivery) and MCP (tool integration). The article breaks down the layers of an agent's context, four typical failure scenarios (poisoning, distraction, confusion, conflict), and a context management approach through write, select, compress, isolate.

Anthropic

OpenAI

Google/DeepMind

Alibaba/Qwen

LangChain

Habr — хаб NLP27.07 · 09:05

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