How AI News Hub works
A transparent pipeline that turns the firehose of AI news into a clean, trustworthy daily read — and always links back to the people who did the reporting.
Ingest from primary sources
We pull continuously from official AI lab blogs (OpenAI, DeepMind, Anthropic, Google, Hugging Face), top journalism (TechCrunch, The Verge, Ars Technica, VentureBeat), research feeds (arXiv), and community signal (Hacker News, Reddit). Everything is filtered for AI relevance.
Dedupe & cluster across outlets
Near-duplicate syndication is collapsed with SimHash; the same story reported by different outlets is grouped using lexical and named-entity similarity within a rolling 72-hour window.
Corroborate before publishing
A story is only turned into a brief once it clears our publishing rule: multiple independent outlets, or a single highly-authoritative primary source. This is what kills single-source rumors and hallucinations.
Summarize with care
An editor model writes each brief: a factual summary, a distinct ‘why it matters’, and key points — using only claims supported by the linked sources. Headlines are constrained to entities and numbers that actually appear.
Rank & surface
Each brief gets an importance score from source authority, cross-outlet corroboration, and recency — so the lead story is genuinely the biggest thing in AI right now.
Our stance on attribution
AI News Hub is a referrer, not a replacement. Every brief is a short, transformative summary that credits and links the original publishers, and is designed to send readers to the source for the full story. We honor publisher feeds and never bypass paywalls.