arXiv rate limit, AI paper mills, Google FluSight

Fair Moderation, Equitable Access, and AI: arXiv’s Updated Rate Limit Policy

arXiv, and the scientific community at large, are facing a watershed moment. Scholarly publishing is currently changing at a rapid pace, and we are seeing a…

Introducing Routines: Research that keeps working - Elicit

Tell the Elicit Research Agent what to keep current. Routines find new evidence, update your work, and report back for your review.

Google's AI ranks #1 for predicting flu hospitalizations.

Google’s science AI model was the best at forecasting flu-related hospital admissions, the Centers for Disease Control announced.

AI-Newton: A Concept-Driven Physical Law Discovery System without Prior Physical Knowledge

While current AI-driven methods excel at deriving empirical models from individual experiments, a significant challenge remains in uncovering the common fundamental physics that underlie these models -- a task at which human physicists are adept. To bridge this gap, we introduce AI-Newton, a novel framework for concept-driven scientific discovery. Our system autonomously derives general physical laws directly from raw, multi-experiment data, operating without supervision or prior physical knowledge. Its core innovations are twofold: (1) proposing interpretable physical concepts to construct laws, and (2) progressively generalizing these laws to broader domains. Applied to a large, noisy dataset of mechanics experiments, AI-Newton successfully rediscovers foundational and universal laws, such as Newton's second law, the conservation of energy, and the universal gravitation. This work represents a significant advance toward autonomous, human-like scientific discovery.

Claude for Science. Thursday, November 12, at the Niels Bohr Institute, University of Copenhagen. In September, Anthropic reported that Claude agents found a CRISPR-like enzyme system in… | Jacob Langvad Nilsson | 17 comments

Claude for Science. Thursday, November 12, at the Niels Bohr Institute, University of Copenhagen. In September, Anthropic reported that Claude agents found a CRISPR-like enzyme system in bacteriophage DNA. Earlier in the same month, another AI lab said its model had settled a question about the Navier-Stokes equations, one of the seven Millennium Prize Problems. Results like these don't come from a lucky afternoon with a chatbot. They come from years of method development, careful engineering and building on the work that came before. What has changed is how much of that work a model can now take on, and the speed of which it does it. The latest models read the literature, write and run their own code, and work through a dataset for hours without losing track. In the enzyme case, hundreds of Claude agents searched DNA data for 21 hours and flagged a pattern nobody had asked them to look for. The method still has to be sound. But a researcher with a good question can now test far more ideas in a week than before. That is what we want to show. How researchers here set up their work so that stronger models can move it forward. The evening is about how the Danish science community uses Claude to drive new research and breakthroughs. Four STEM researchers from academia and industry each show one case. What they asked Claude, how they worked, what they found, and what failed. The room is part of it. Niels Bohr lectured in Auditorium A, and in the 1930s Heisenberg and Pauli sat in the front row. We will meet in this historical auditorium and get a glimpse of frontier scientific research using Claude. ▪️ Doors open 15:30, programme 16:00 to 19:00 ▪️ Four case studies from Danish research ▪️ 50 seats on the original wooden benches ▪️ Registration by approval Thanks to Daniel Murnane for making this happen. Thanks to the Niels Bohr Institute and the University of Copenhagen for having us. To Katrin Hjorth Thordardottir for logistics. And thanks to Anthropic and the Claude Community team, Martine N., Cassie Baquero Mayes, Chiara Massironi for your continued support. Link to sign up in the first comment below. We are still confirming speakers. Which researcher in Denmark should I talk to? | 17 comments on LinkedIn

5 days left to apply! 4 new sponsors, $100k + in cash & credits. 4 tracks: → Computer-use - originator.inc → Autoresearch - cthree.cloud x AIDDA Institute → Drug & protein design - Serova… | Jonty Corrin

5 days left to apply! 4 new sponsors, $100k + in cash & credits. 4 tracks: → Computer-use - originator.inc → Autoresearch - cthree.cloud x AIDDA Institute → Drug & protein design - Serova → Materials design - Polaron + 2 special-prize challenges with Cognition & Modal

A new type of paper mill

About the possibility of new paper mills in mathematics.

What about the preprints?

Preprints are central to math research and immediately feed back into LLMs. Could the mainstream preprint workflow be adjusted in a way that gives individuals more choices to impact the balance bet…