Merged timeline of 56 items — blog publish times and listing timestamps, cut at midnight . Page 2 of 2.
New York's groundbreaking AI disclosure law (S8420A) requires advertisers to label AI-generated synthetic performers starting June 2026.
For nearly 80 years, mathematicians believed square grids were optimal for maximizing unit-distance pairs. An OpenAI model just proved them wrong—using Golod-Shafarevich theory and infinite class field towers to construct configurations with n^(1+δ) pairs. First autonomous AI solution to a central math problem. Fields medalist Tim Gowers calls it 'a milestone in AI mathematics.'
World models represent a fundamental shift in AI—from systems that process text to ones that understand physics, space, and causality. This guide covers how they work, why they matter, and the leading examples shaping the field in 2026.
Tencent’s HY-World 2.0 frames world modeling as persistent 3D assets—Gaussian splats, meshes, point clouds—rather than disposable video. WorldMirror 2.0 already ships for multi-view/video reconstruction; the full text→navigable-world pipeline is partially open with a clear roadmap.
A concise read of what Google actually announced: specialized TPUs for the agentic era, an end-to-end enterprise agent stack with Oracle- and Salesforce-class partners, and hard numbers on internal coding and global API token volume. Plus how explainx.ai thinks about multicloud agent building.
Skills are reusable instruction packages for AI coding agents—not one-off prompts. Here is the full picture: anatomy, ecosystem map, token trade-offs, and backlinks to explainx.ai, the MCP directory, and official docs.
