4 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
A free, open platform where machine-learning researchers submit and peer-review papers in public. Much of the field's conference review (including major AI venues) runs on it, and anyone can read the papers, reviews and rebuttals.
Free service that gathers public expert evaluations and reviews of preprints in one place, so you can see what other researchers said about a study before it was formally published.
Why I recommend it: Use it as a sanity check on a preprint someone is quoting at you. No evaluation on Sciety means nobody independent has publicly assessed it yet — which is not the same as the study being wrong.
A free, open platform from the non-profit Center for Open Science for managing research projects, sharing data and materials, registering studies in advance and hosting preprints. You can browse public projects without signing up.
Why I recommend it: The most useful part for a non-researcher: when a study makes headlines, its OSF page often holds the data and the pre-registered plan, so you can see whether the researchers found what they said they would look for.
Official news from CERN, the European particle physics laboratory: accelerator and experiment updates, computing and engineering write-ups, and knowledge-sharing pieces, filterable by topic and audience (general public, students, educators, policymakers). Free to read, no account.
Why I recommend it: Worth following if you want technology news written by the people doing the work rather than by a tech press cycle. The Computing and Knowledge sharing topics are the useful filters for a career audience — CERN publishes plainly about large-scale computing, data handling and open-source work, and the writing is aimed at non-specialists.
