Alibaba/Qwen

Latest AI news, models and releases from Alibaba/Qwen. ['CodeQwen1.5', 'Cotype Light 3', 'Cotype Pro 3', 'Fun-Realtime-TTS', 'Hanguang', 'Hanguang 800', 'HappyOyster 1.0', 'ICN Switch 1.0', 'not specified', 'Panjiu', 'Qianwen', 'Qoder Security', 'QVQ-72B-Preview', 'QVQ-Max', 'Qwen', 'Qwen 2', 'Qwen2.5', 'Qwen2.5-0.5B', 'Qwen2.5-14B', 'Qwen2.5-14B-Instruct-1M', 'Qwen2.5-1.5B', 'Qwen2.5-32B', 'Qwen2.5-3B', 'Qwen-2.5 72B', 'Qwen2.5-72B', 'Qwen2.5-7B', 'Qwen2.5-7B-Instruct-1M', 'Qwen2.5-Coder', 'Qwen2.5-Coder-0.5B', 'Qwen2.5-Coder-0.5B-Instruct', 'Qwen2.5-Coder-14B', 'Qwen2.5-Coder-1.5B', 'Qwen2.5-Coder-1.5B-Instruct', 'Qwen2.5-Coder-32B', 'Qwen2.5-Coder-32B-Instruct', 'Qwen2.5-Coder-3B', 'Qwen2.5-Coder-3B-Instruct', 'Qwen2.5-Coder-7B', 'Qwen2.5-Coder-7B-Instruct', 'Qwen2.5-Coder-Instruct']

Official site ↗

Agents 🇷🇺

MCP for Agent Commerce: What Could Go Wrong

Tutu and Alexander Polyakov released an MCP server for agent-based commerce, enabling AI agents to search real travel data. The article shares seven practical lessons from development, including landing page handling, context optimization (74% reduction), authorization support, and legal considerations.

Moonshot AI

OpenAI

Alibaba/Qwen

Anthropic

Habr — хаб ИИ28.07 · 16:01

Research 🇺🇸

A Visual Guide to Attention Variants in Modern LLMs

This article provides a visual overview of attention mechanisms in modern large language models, covering from standard multi-head attention (MHA) to grouped-query attention (GQA), multi-head latent attention (MLA), sparse attention, and hybrid architectures. It is accompanied by an LLM architecture gallery with 45 entries and poster versions.

OpenAI

Allen Institute for AI