What are "hidden prompts"? And what risks come with collaborating through AI? Discover insights & recommendations in our revised Guidelines on Responsible Use of Generative AI in Research.
Stay tuned for more news on #AI4science!
➡️ http://link.europa.eu/3rvd6Y
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https://nitter.net/EUScienceInnov/status/2052684180056895979#m
LRZ goes TPC26 🚀
#TPC26 ist die Konferenz und Messe des Trillion Parameter Consortiums, auf der globale Kooperationen zwischen den KI-Forschungsbereichen der Industrie und des öffentlichen Sektors diskutiert und vorangetrieben werden.
Während die Hauptveranstaltung in Baltimore stattfindet, richtet das LRZ ein Satelliten-Event in Garching aus.
Mehr unter: https://www.lrz.de/aktuelles/events/detail/lrz-goes-tpc26
Kevin Weil (@kevinweil)
OpenAI의 Science 조직이 다른 연구팀으로 분산되며 OpenAI for Science가 해체·재편된다. 과학 가속을 목표로 한 내부 연구 조직 변화로, AI를 활용한 과학 연구·발견 지원 방향에 중요한 조직 개편 신호로 볼 수 있다.
Today is my last day at OpenAI, as OpenAI for Science is being decentralized into other research teams. It’s been a mind-expanding two years, from Chief Product Officer to joining the research team and starting OpenAI for Science. Accelerating science will be one of the most
This article argues that the most important significance of the AI revolution, especially the rise of large language models, lies not simply in automation, but in a fundamental change in how complex information and human know-how are carried, replicated, and shared. From this perspective, AI for Science is especially important because it may transform not only the efficiency of research, but also the structure of scientific collaboration, discovery, publishing, and evaluation. The article outlines a gradual path from AI as a research tool to AI as a scientific collaborator, and discusses how AI is likely to fundamentally reshape scientific publication. It also argues that continuous learning and diversity of ideas are essential if AI is to play a meaningful role in original scientific discovery.
Michelle Bakels (@MichelleBakels)
Day 21: Google Labs의 Kath Korevec가 'Proactive Agents'를 발표했습니다. 또한 'State of MechInterp' 세션에서는 SAEs의 생산 적용, 회로 추적(circuit tracing), AI4Science 적용 사례와 더 실용적인 해석('Pragmatic' Interp) 접근법 등 기계 해석학(mechanistic interpretability) 관련 최신 연구·토픽을 다뤘습니다.
Is it AI "Hallucination" or "Intuition"? 🧠
Great discussions today on the Prime-Chaos discovery. The skepticism is valid: Python scripts prove the stats, but not the truth.
So, we are leveling up OpenSciEval.
🚀 Phase 2 Mission: Tasking the Agent to translate its heuristic derivation into Lean 4 code for formal verification.
If it compiles, the debate ends. Stay tuned.
Also consider following the authors Aniket Pramanick (Ubiquitous Knowledge Processing (UKP) Lab), Yufang Hou (IT:U- Interdisciplinary Transformation University Austria, IBM Research), Saif M Mohammad (National Research Council Canada / Conseil national de recherches Canada), and Iryna Gurevych (Ubiquitous Knowledge Processing (UKP) Lab).
🗺️ See you at #ACL2025 in Vienna
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EUScience&Innovation🇪🇺
Leibniz Supercomputing Centre
José A. Alonso
sayzard
Ricardo Barros Lourenço
Jean-Philip Piquemal
mariswang
UKP Lab