Moonshot AI

Latest AI news, models and releases from Moonshot AI. ['GLM 5.2', 'GLM-5.2', 'Hermes', 'K2', 'K2.6', 'K3', 'K3-mini', 'K3-MoE', 'Kimi', 'Kimi 2.6', 'Kimi-2.6', 'Kimi 3', 'Kimi 3T', 'Kimi Hosted Agent', 'Kimi k1.5', 'Kimi K1.5', 'kimi-k2', 'Kimi K2', 'kimi-k2-0711-preview', 'Kimi K2.5', 'Kimi-K2.5-1T-A32B', 'Kimi K2.6', 'Kimi K2.7', 'Kimi K2.7 Code', 'Kimi K2 Thinking', 'Kimi K3', 'Kimi-K3', 'Kimi K3.5', 'Kimi K4', 'Kimi K5', 'Kimi Linear', 'Kivine', 'Krea 2', 'Krea 2 Turbo', 'Mamba', 'Mamba-2', 'Mamba-3', 'MiniCPM-RobotManip', 'MiniCPM-RobotTrack', 'Minimax']

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Agents 🇷🇺

Deep Agents: Context Engineering for Long-Horizon Tasks in LangChain

The world of AI agents is evolving rapidly: from linear LangChain pipelines to LangGraph graphs and further to ready-made environments like Deep Agents. Deep Agents is a library that gathers middleware, tools, and prompts around the basic ReAct loop for managing context in multi-step tasks. It adds planning, file tools, subagents, history summarization, and other mechanisms, but at a cost — a steep increase in the system prompt (from 35 to 6215 tokens) on an empty request.

LangChain

Moonshot AI

Anthropic

Habr — хаб ИИ27.07 · 11:02

Open Source 🇺🇸

NVIDIA NeMo AutoModel Accelerates MoE Fine-Tuning 3.7x with Expert Parallelism and DeepEP

NVIDIA has introduced NeMo AutoModel, an open library that builds on Hugging Face Transformers v5, delivering 3.4-3.7x higher training throughput and 29-32% less GPU memory for MoE models via Expert Parallelism, DeepEP fused all-to-all dispatch, and TransformerEngine kernels—using the same from_pretrained() API with only an import change.

NVIDIA

Hugging Face

Moonshot AI

DeepSeek

Hugging Face blog27.07 · 10:04

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