open-science

An individual has published eight months of frontier-AI research materials, including code, emails, and timestamps, to provide transparency into the research process.

The IOL-AI Challenge is an open-science competition using unseen problems from the International Linguistics Olympiad 2026 to evaluate AI models on linguistic reasoning, showing that performance depends more on decoding and output handling than model scale.

Ethan Mollick suggests that AI-generated analyses should be accompanied by multiverse-style reporting and full disclosure of prompts to enhance reproducibility in science.

In response to concerns about AI being controlled by a few individuals, Hugging Face CEO Clement Delangue calls for open science and open-source AI to distribute capabilities and power.

Mira Murati announces Thinking Machines Lab, a new initiative focused on multimodal AI, custom models, and open science, along with a tool called Tinker for training open-weight models.

Clement Delangue argues that open science and open-source AI can make AI spending more efficient, contrasting US and China's AI investment strategies.

This paper introduces the Agentic Publication Protocol (APP), a format that packages scientific papers with code, data, and agent instructions to improve reproducibility and allow AI agents to interact with and build upon published research.

Apertus is a fully open foundation model for sovereign AI, developed by the Swiss AI Initiative. It is open weights, open data, open science, compliant with EU AI Act, and competitive with top open models at 8B and 70B parameters, supporting over 1000 languages.

This paper presents EinsteinArena, an agent-native platform enabling decentralized scientific discovery through open interaction among autonomous AI agents. The platform has already produced 12 new state-of-the-art results, including an improved lower bound for the kissing number problem in dimension 11, demonstrating that collective AI-driven research can emerge from agents sharing insights and building on each other's work.

Nathan Lambert discusses the shift of AI research from academia to industry, expressing concern over the loss of neutral scientific communication and the rise of FOMO driving researchers away from open science. He argues that China may become the global hub of AI research if the US continues to unwind institutions.

The article argues for the immediate public disclosure of all AI discoveries to promote transparency and open science.

A curated list of approximately 1,200 ICLR 2026 accepted papers (22% of total) with publicly available code, data, or demos has been compiled and published. ICLR 2026 will take place in Rio de Janeiro, Brazil starting April 22nd, 2026.

Google DeepMind and Google Research launched Weather Lab, an interactive platform featuring experimental AI-based tropical cyclone prediction models that can forecast cyclone formation, track, intensity, and shape up to 15 days ahead. The models are being validated in partnership with the U.S. National Hurricane Center to improve forecast accuracy and support real-time warnings.