🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

The Stanford HAI #AIIndex2025 report launches April 7. Packed with rigorously vetted data, it provides an independent lens on AI’s progress, its adoption across various sectors, and its far-reaching impact. Be among the first to receive the report: hai.stanford.edu/ai-index

Want to join the conversation on AI—and be heard? Use trusted insights from the Stanford HAI #AIIndex2025 to spark smarter dialogue and back your ideas with data that matters. Stay informed with the AI Index, coming April 7: hai.stanford.edu/ai-index

📣 We’re thrilled to announce the first workshop on Technical AI Governance (TAIG) at #ICML2025 this July in Vancouver! Join us (& this stellar list of speakers) in bringing together technical & policy experts to shape the future of AI governance!

An LLM generates an article verbatim—did it “train on” the article? It’s complicated: under n-gram definitions of train-set inclusion, LLMs can complete “unseen” texts—both after data deletion and adding “gibberish” data. Our results impact unlearning, MIAs & data transparency🧵

Thank you for featuring our work! Great collaboration with Declan Grabb, MD and the team. We created a dataset that goes beyond medical exam-style questions and studies the impact of patient demographic on clinical decision-making in psychiatric care on fifteen language models

📢Introducing #AIIndex2025: This year's report highlights the most critical trends in AI – from shifting geopolitical landscape and rapid technological evolution, to AI’s expanding role in science and medicine, business, and public life. Read more: hai.stanford.edu/ai-index/2025-…

🚨 Call for Reviewers! If you're interested in reviewing 2–3 short papers in May for the First Workshop on Technical AI Governance at #ICML2025, please fill out our quick expression of interest form (takes <2 mins!) ✍️

Exciting news! Open Problems in Technical AI Governance was published at TMLR! This is a good time to mention that we're organizing a workshop on TAIG at #ICML2025. Papers are due May 7th and we're also looking for PC members Check out Technical AI Governance @ ICML 2025 for more details!

🚨New paper: Current reports on AI audits/evals often omit crucial details, and there are huge disparities between the thoroughness of different reports. Even technically rigorous evals can offer little useful insight if reported selectively or obscurely. Audit cards can help.

Cooperation on AI safety is necessary but also comes with potential risks. In our new paper, we identify technical AI safety areas that present comparatively lower security concerns, making them more suitable for international cooperation—even between geopolitical rivals. 🧵

📣 Submissions OPEN for the 1st Technical AI Governance Workshop at #ICML2025! 🔗 Submit on OpenReview: openreview.net/group?id=ICML.… 🗓️ Deadlines: Abstract 7 May | Full paper 12 May (23:59 AOE)

transparency in AI is dying: no evals, no release notes, just vibes and more bad naming

“The much discussed AI-2027 scenario, for example, predicts in passing that by the end of 2025 (eight months from now!), there will be AIs that have “a PhD-level knowledge of every field”. I often get the sense that many of the people who make those kinds of predictions have no

We trained our Large Sensor Model (LSM) on over 40 million hours of de-identified multimodal sensor data from 165K users to demonstrate how it could improve performance in wearable tasks like exercise and activity recognition. Here’s what we found → goo.gle/4fYDQJ4

⏰ 1 week left! Abstracts for the Technical AI Governance Workshop at #ICML2025 are due 7 May, 23:59 AOE

open problems in technical ai governance: x.com/AnkaReuel/stat…

In 1999, engineers at Georgia Tech proposed the "Aware Home." It was a vision of ubiquitous computing designed to serve its inhabitants, giving them full knowledge and control over their own data. The dream was user empowerment—using data (and ultimately AI) to fill in the gaps

🚨 Lucie-Aimée Kaffee and I are looking for a junior collaborator to research the Open Model Ecosystem! 🤖 Ideally, someone w/ AI/ML background, who can help w/ annotation pipeline + analysis. docs.google.com/forms/d/e/1FAI…

A bit late to the party, but our paper on predictable inference-time / test-time scaling was accepted to #icml2025 🎉🎉🎉 TLDR: Best of N was shown to exhibit power (polynomial) law scaling (left), but maths suggest one should expect exponential scaling (center). We show how to

🚨New preprint 🚨 Turning Down the Heat: A Critical Analysis of Min-p Sampling in Language Models We examine min-p sampling (ICLR 2025 oral) & find significant problems in all 4 lines of evidence: human eval, NLP evals, LLM-as-judge evals, community adoption claims 1/8