Resource Hub
3505 hand-picked resources for students, job seekers, career changers, founders, and AI learners — 100% free to browse with no account required.
Filtered by tag
Answers come only from resources in this hub, with the sources listed.
701 resources
Strada Education Foundation's state-by-state framework linking education to opportunity, with an interactive map, key findings, a downloadable full report and executive summary, technical appendices, and state comparisons of measures such as early-career earnings and job placement.
A State of AI page by Nathan Benaich of Air Street Capital, reviewed October 31, 2026, comparing separate estimates of AI adoption, spending and financial returns, and explaining who each source measured, when, and what it counted as adoption.
A Columbia University-hosted benchmark that tests AI agents on reverse engineering complex binary software. The page reports results from evaluations run with OpenAI, stating that GPT-6 Astra solves nearly all tasks while other evaluated models stay below 60%, and describes pilot evaluations of harder settings.
A Resume Now survey report on workplace values, stating that 70% of surveyed workers say leaders bend rules for favorites, with findings on fairness, favoritism and alignment between stated and practiced company values. Resume Now sells résumé-building services.
Artificial Analysis reports Muse Ember benchmark scores and task-cost estimates, including an Intelligence Index score of 36 and $0.14 per task in its evaluation. These are evaluator-specific results, not a verified Meta launch announcement or evidence of free model access.
Epoch AI explains an Inference Performance Index for estimating chip capacity across agentic workloads and output-speed requirements. Its modeled comparisons, expressed in GB300 equivalents, depend on workload and hardware assumptions and are not universal real-world performance guarantees.
OpenAI announces that organizations can purchase ChatGPT Enterprise through AWS Marketplace using existing procurement and billing arrangements. The announcement is freely readable; ChatGPT Enterprise is a paid service, not a free tool.
9to5Google reports a web settings view for seeing, editing and deleting Gemini's remembered information. The article is free to read; the reported feature requires eligible Google AI subscribers in US English, and the reporter had not observed Android or iOS availability.
OpenAI discusses educator support, AI literacy and education partnerships in EMEA, drawing on ThinkYoung research and early program experience. The freely readable company article describes context-specific findings; it does not establish that every partnership or product is freely available.
Anthropic announces a proposed IPO roadshow with 825 million shares at an expected $70–$78 range and an underwriter option for up to 123.75 million additional shares. The announcement is free to read; the offering remains proposed and the registration statement was not yet effective.
ActivTrak reports associations between AI use, longer workdays, app switching, and focus in its workplace data. The figures are the company’s own findings and do not establish that AI caused longer workdays; the report announcement is free to read.
Preprint, not yet peer-reviewed, by Anna Brandenberger, Hanna Mularczyk, and Dora Woodruff. The paper surveys more than 260 early-career mathematicians at nearly 60 institutions about their experiences and concerns around AI in mathematics.
Working paper, under review and not yet peer-reviewed, by Maximilian Kaiser and Christian Schulze. The authors examine ChatGPT’s advertising rollout using data from 1,898 websites over 60 weeks, comparing referrals, conversions, and advertising value.
A paid, fixed-term research program from Anthropic with placements of six weeks to six months, aimed at established technical leaders such as professors in quantitative fields, technical founders and staff-level engineers moving into AI safety work. A machine-learning background is not required. Applications for this round close November 22, 2026.
An interactive report showing small transformer networks whose weights were written directly by an AI agent, with no training, to solve toy tasks such as bit-string parity. Every weight matrix is displayed, and code, run logs and saved programs are published on GitHub.
A research blog post from MIT CSAIL researchers reporting that frontier language models can identify what a neural network was trained to do from its raw weights and can write small working networks directly. The post is not yet peer-reviewed; results are the authors' own.
Preprint examining whether psychological safety is associated with workplace AI adoption and usage, using survey data from 2,257 employees at a global consulting firm.
NPR report on teachers using AI for lesson plans and districts using chatbots for student feedback, and on how limited the research on AI and student learning remains.
The blog of cloud security company Wiz, with guides, vulnerability research, and announcements about cloud security.
A research organization studying how to navigate rapid AI progress, including a possible intelligence explosion, with research papers, open projects, a podcast, and a newsletter.
Barry Schwartz summarizes three studies on AI search visibility and search investment, including their stated limitations and conclusions.
Communications of the ACM research article synthesizing a 44-person workshop on AI, accessibility, and employment for disabled workers. It covers employment gaps, AI errors and hallucinations in situations where accuracy is critical, AI-scored video interviews that can screen out workers with non-normative speech or movement, accessibility overlays that may not work as advertised, and accountability gaps when inaccessible tools come from third-party vendors. Free to read.
Peer-reviewed ICML 2026 position paper by Joachim Baumann, Jiaxin Pei, Sanmi Koyejo, and Dirk Hovy, accepted for an oral presentation. Compares human and AI ICLR 2026 reviews and tests automated paper rewriting, reporting excessive reviewer agreement and susceptibility to stylistic changes. The authors argue for rigorous evaluation before automating peer review.
Shows that AI-generated article reviews scored better, by every measure the authors constructed, than reviews written by well-compensated human experts judged to be of unusually high quality, and discusses implications for journal policy. Working paper.
