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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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

Hardware & Inference 🇺🇸

Google Accelerates Gemini Nano Models on Pixel with Frozen Multi-Token Prediction

Google has introduced a method to retrofit Multi-Token Prediction (MTP) onto frozen production models like Gemini Nano v3, enabling faster on-device inference on Pixel 9 and 10 devices. The MTP head attaches to the main model's final layers, leveraging its hidden states and KV cache to generate multiple tokens per inference pass without separate drafting models, achieving speedups of 50% or more and reducing memory consumption by 130MB per instance.

Google/DeepMind

Google DeepMind

Google Research27.07 · 05:05

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