What 80,000 People Actually Want From AI

Last December, Anthropic asked 80,508 Claude users across 159 countries what they actually want from AI. The findings are both clarifying and unsettling - and reveal a design brief most AI labs aren't executing against.

Moonshot AI's Attention Residuals Challenge a Core Assumption of Modern LLMs

Moonshot AI's Kimi team proposes replacing transformer residual connections with a lightweight attention mechanism over prior layer outputs. The result: equivalent training performance at 1.25 times less compute, with gains confirmed across model sizes. It is the cleanest architectural challenge to a foundational LLM assumption in years.

Microsoft Bets on Model Diversity, Bringing Claude Into the Heart of Copilot

Transformers Explained: The Architecture Behind Modern AI

OpenAI Buys Astral, the Team Behind Python's Most Essential Tools

OpenAI has agreed to acquire Astral, the team behind Python's uv, Ruff, and ty tools, folding them into its Codex coding-agent division. The deal is the third developer-tooling acquisition OpenAI has made in three months, raising questions about open-source stewardship and competitive intent.

States vs. Washington: The AI Regulation Showdown Taking Shape Across 50 Legislatures

In the absence of federal AI legislation, states have spent three years building their own frameworks - and the results are now colliding with a coordinated White House counteroffensive. From Utah's nine-bill sprint to the DOJ's new AI Litigation Task Force, the battle over who governs artificial intelligence in America is entering its most consequential phase.