Resource Hub
2467 hand-picked resources, updated every week. Search it, filter it, or just browse a collection and see what catches your eye. Want today’s headlines instead? Read the free AI news feed.
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Answers come only from resources in this hub, with the sources listed underneath.
12 resources
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.
Open-access academic publisher with more than 1,700 disciplines covered across its journals. Every published article is free to read and download in full, with no account needed.
Why I recommend it: Free for readers, but not free for authors: Frontiers charges researchers a publishing fee, and that model has drawn criticism over review quality. Read individual papers on their merits and check who funded the work.
A directory of open-access research repositories worldwide, browsable by country, year, repository type and software. It tells you where universities and institutions publish their own researchers' papers for free.
Why I recommend it: This is a map of where to look, not a search engine for papers. When a paper you want is paywalled, find the author's university repository here and check for the free accepted version.
IEEE's research library of journal articles, conference papers and standards across computing, electrical engineering, AI and robotics.
From the site: Search and browse IEEE journals, conference proceedings and standards; abstracts are free, full text usually requires a subscription or purchase.
Why I recommend it: Paywall warning: searching and reading titles, abstracts and citations is free, but most full papers need a subscription, an institutional login or a per-article purchase. Some papers are open access and free in full. Check your school or public library for access before paying, and look for the same paper on the author's own site or arXiv first.
Personal site of the philosopher behind Superintelligence and the simulation argument, with free full-text papers on existential risk, human enhancement, anthropics and the future of AI. Many of the ideas now standard in AI risk debates started here; his work is also widely criticised, so read it alongside its critics.
From the site: Oxford philosopher (videos, papers, interviews, bio, etc.)
Why I recommend it: Read the primary source rather than summaries of it — then read the critics, several of whom are already in the hub.
Microsoft's research division: published papers, open datasets and tools, plus its internship and residency programs.
From the site: Explore research at Microsoft, a site featuring the impact of research along with publications, products, downloads, and research careers.
Why I recommend it: The publications are free to read and the programs page lists real entry routes into research work. Both are more useful than the marketing pages.
Free search across academic papers, theses and citations, with links to full text where it is public.
From the site: Google Scholar provides a simple way to broadly search for scholarly literature. Search across a wide variety of disciplines and sources: articles, theses, books, abstracts and court opinions.
Why I recommend it: The fastest way to check whether a claim in a news article traces back to an actual paper. Set an alert on a topic and it will email you new work.
Deep learning pioneer and Turing Award winner, now focused on AI risk. His site holds papers, talks and written positions; his Google Scholar list has the full publication record, most-cited first.
From the site: Yoshua Bengio is Full Professor of Computer Science at Université de Montreal, Co-President and Scientific Director of LawZero, as well as the Founder and Scientific Advisor of Mila. He also holds a Canada CIFAR AI Chair.
Why I recommend it: One of the three people whose work made modern AI possible, who now spends much of his time arguing it needs guardrails. Read him alongside people who disagree.
Site of Oxford philosopher Toby Ord, author of "The Precipice", with free papers and essays on existential risk and how to weigh long-term outcomes.
Why I recommend it: Several of his papers are downloadable free. Read him for the reasoning about risk, not for AI specifics.
Google Scholar profile listing Geoffrey Hinton's papers in citation order — backpropagation, dropout, AlexNet, t-SNE and the rest of the deep learning canon.
From the site: Emeritus Prof. Computer Science, University of Toronto - Cited by 1.089.325 - machine learning - psychology - artificial intelligence - cognitive science - computer science
Why I recommend it: The single best index of the papers that made current AI work. Sort by year to see the ideas arrive. Scholar blocks automated visits, so the picture may be a screenshot.
The open-access preprint server for physics, mathematics, computer science, and related fields — a primary source for cutting-edge AI and machine-learning research papers.
Why I recommend it: The best place to read AI research before it hits journals or the press; search by tag or author to follow a specific line of work.
An AI research platform for finding papers, verifying citations, reviewing literature, managing knowledge, and creating scientific figures.
Why I recommend it: For anyone doing deep research, Bohrium helps cut through the paper flood and verify claims before you cite them. I recommend it to clients writing thought-leadership content.
