AI is moving fast enough that any single source's coverage is partial. WeSearch's AI hub mixes lab blogs, dedicated AI press, generalist tech publishers covering AI, AI-policy reporting, and AI-application coverage — so the most-recent OpenAI release sits next to the Information's deep dive on the same release next to a Stratechery analysis of the strategic implications.
What's in this hub
Lab blogs. OpenAI Blog, Anthropic Blog, DeepMind Blog, Google Research Blog, Meta AI Blog, NVIDIA Blog, Hugging Face Blog, Mistral AI, Cohere, Perplexity Blog.
AI-focused press. MIT Technology Review, the Information AI desk, Stratechery (when AI), Platformer, Import AI, Ben's Bites, the Batch (Andrew Ng), the Algorithmic Bridge.
Generalist tech on AI. The Verge AI, Wired AI, the Atlantic AI, NYT AI, Washington Post AI, FT AI, Bloomberg AI.
AI research and academic. arXiv (selected categories), AI papers via Hacker News, Distill.pub, Lesswrong AI, the Gradient.
AI policy. Lawfare AI, Tech Policy Press, AI Policy Magazine, the Brookings AI section.
AI applied. A16Z AI Newsletter, MIT Sloan AI, HBR AI, Pinecone Blog, LangChain Blog, Sequoia AI, the Diff (when AI), Stratechery (when AI).
What you'll find here
- Lab releases and benchmark updates
- Major paper coverage
- Industry deals, funding, M&A
- AI policy and regulation (EU AI Act, US executive orders, China standards)
- Safety and alignment research
- Applied-AI use cases and case studies
- Tooling and infrastructure coverage (vector DBs, orchestrators, fine-tuning frameworks)
- Open-source model releases (with weights, evals, license details)
- Compute and infrastructure (GPU supply, energy, data-center buildout)
- Training data and copyright disputes
How we balance AI coverage
AI is unusually polarized in 2026. The press splits along axes that don't always line up: pro-acceleration vs. cautious; pro-open-source vs. closed; pro-capability vs. pro-safety; pro-incumbent labs vs. pro-startup; AGI-soon vs. AGI-skeptical. We don't pick a side; we include named publishers across these axes (Anthropic and OpenAI for the labs, Lesswrong and the Algorithmic Bridge for the safety-leaning, Import AI and Stratechery for the industry-analysis, the Verge and the Atlantic for the consumer-press skeptical-friendly takes).
The hub does not include obvious AI hype-cycle content (uncritical product launches with no analysis, prompt-engineering listicles, "we just disrupted X with AI" press releases). The bar is original analysis or original reporting.
How to use the AI hub well
- For lab releases, read the lab post AND a piece of independent analysis. The lab post is marketing; the analysis catches what the lab is leaving out (eval-set leakage, cherry-picked benchmarks, capability-vs-deployment gaps).
- Subscribe to push for specific labs. Settings → Notifications → Watches → Sources. Add OpenAI, Anthropic, DeepMind, Meta AI, the labs you care about.
- The discussion threads under AI stories are unusually substantive. Working ML engineers and researchers post often. Skim them.
- Use the daily editorial. The /daily briefing often connects AI stories to the broader news cycle (e.g., AI policy + tech earnings + content-creator strikes).
What we don't cover well yet
Chinese AI press (we pull a few translated pieces but not enough). AI in non-English non-Chinese contexts (Indian, Japanese, Korean AI labs and applications). The deeply-technical end of mechanistic interpretability research (we surface high-level coverage but not the original Anthropic/OpenAI safety papers in depth — those are better read on the lab blogs directly).