The AI resources actually worth following

Product launches, research and company announcements from OpenAI.

Claude releases, research and safety work straight from Anthropic.

Research breakthroughs and Gemini updates from Google DeepMind.

How Google ships AI across Search, Workspace and Android.

Llama models, open research and AI products from Meta.

Copilot, Azure AI and enterprise AI news from Microsoft.

The hardware side of AI — GPUs, inference and industry deployments.

Open-source models, datasets and hands-on ML engineering posts.

Releases from Europe's leading open-weight model lab.

Image, video and audio generation model releases.

Andrew Ng's weekly — the clearest plain-English AI digest there is.

Daily 5-minute rundown of AI product news and launches.

Daily AI news and practical how-to guides for work.

AI research, products and engineering in five minutes a day.

Daily newsletter on using AI to be more productive at work.

Jack Clark's weekly deep read on AI research and policy.

Weekly digest of the most important AI news, with a podcast.

The AI engineer's newsletter and podcast — agents, evals, infra.

Ethan Mollick on the practical, human side of working with AI.

Nathan Lambert's technical read on frontier models and RLHF.

Hands-on notes on LLMs, prompts and tools, posted almost daily.

Ben Thompson's strategy analysis of tech and AI business moves.

Curated morning briefing on AI developments and research.

Deep, trustworthy reporting on where AI is actually heading.

Consumer-angle coverage of AI products and industry news.

Startup funding, launches and AI industry moves.

Enterprise AI adoption, tooling and platform coverage.

Culture, security and society angles on the AI wave.

Technically literate reporting and analysis on AI.

The engineering profession's view of AI progress.

Global wire coverage of AI business, policy and regulation.

The preprint firehose — where new AI research appears first.

Machine-learning preprints, updated daily.

Research papers paired with code and leaderboards.

Interpretability, alignment and frontier-model research.

Research publications behind the GPT model family.

Beautifully visual explanations of ML concepts — an evergreen archive.

Accessible essays and perspectives on AI research.

Joyful short explainers of new AI research papers.

Long-form conversations with the people building AI.

Careful, fast coverage of frontier model releases and evals.

Weekly tours of new AI tools you can actually use.

High-speed, high-humor takes on AI and developer tech.

The New York Times' weekly podcast on AI and the future of tech.

Investor-side interviews with AI founders and researchers.

Nathan Labenz's interviews on how AI changes every industry.

Where AI news breaks and gets argued about first.

The research-grade machine-learning community on Reddit.

General AI news and discussion for a broad audience.

Practical help with open-source models and libraries.

Long-form community writing on AI progress and alignment.