Signals · 12
Open-sourcing AstaBrief, the fast report-generation model in Asta — We’re releasing AstaBrief, an 8B open-weights model for generating cited scientific reports, available in Asta’s Fast mode or to download and run on your own infrastructure.
The Allen Institute for AI has open-sourced AstaBrief, an 8B open-weights model designed for generating cited scientific reports.
Introducing Olmo-core 3: Open, scalable training infrastructure for large MoEs — Olmo-core 3 introduces a redesigned, fully open training stack for efficiently scaling mixture-of-experts models into the trillion-parameter range.
The Allen Institute for AI has introduced Olmo-core 3, an open training infrastructure for scaling mixture-of-experts models.
Teaching future scientists to interrogate AI tools for scientific discovery — University of Washington students put Ai2’s AutoDiscovery to the test, showing how AI can surface promising scientific leads while making human judgment, domain expertise, and rigorous validation more important than ever.
University of Washington students tested Ai2's AutoDiscovery, demonstrating how AI tools aid scientific discovery while highlighting the need for human judgment.
How Goodfire used Ai2’s open post-training stack to trace unwanted model behavior — Goodfire used Ai2’s fully open post-training stack to predict LLM behavioral changes, trace unwanted model behavior back to individual training examples, and test targeted fixes without sacrificing broader capability gains.
Goodfire utilized Ai2's open post-training stack to identify unwanted LLM behavior and apply targeted fixes.
The hard parts of AI-assisted science — At an Ai2 event marking our expanded collaboration with Providence Swedish, researchers explored the hardest problems in AI-assisted science: keeping systems steerable, grounded in human judgment and sound methods, and responsive to new evidence and experiments.
Researchers at an Ai2 event discussed the key challenges of AI-assisted science, including steerability and grounding systems in human judgment.
Ai2 and Providence Swedish Cancer Institute partner to advance AI-assisted scientific discovery — Ai2 and Providence Swedish Cancer Institute are expanding their collaboration after AutoDiscovery helped researchers uncover and validate a promising new immune signal in invasive lobular breast cancer.
Ai2 and Providence Swedish Cancer Institute are expanding their partnership after AI-assisted tools helped discover a new breast cancer immune signal.
When a model reads a drug's class from its name—not its knowledge — Researchers used Olmo 3 and its open training data to show that models can infer a drug’s class from its name instead of knowing the specific medication, and traced that shortcut to how often drugs appeared in training.
Researchers used OLMo 3 to show that language models often infer a drug's class from its name rather than actual knowledge.
TutorMoments: Do AI tutors know when to help and when to hold back? — TutorMoments is an open, replay-based evaluation framework that tests whether AI tutors can recognize when to support a student and when to hold back and encourage deeper reasoning.
Ai2 expands collaboration with Hugging Face to accelerate open science — Ai2 is expanding its partnership with Hugging Face to give its growing portfolio of fully open models, datasets, benchmarks, and applications the storage, bandwidth, and integrations needed to reach more researchers and developers.
Tracing distinctive language in AI-written text — Stony Brook researchers used our infini-gram engine to trace distinctive phrases in AI-generated writing back to existing sources, finding that top-selling self-published books on Amazon with substantial detected AI text overlap more heavily with rare language from previously published works.
The OlmoEarth Platform: Geospatial inference at planetary scale — How we built the OlmoEarth Platform to fine-tune geospatial models and run continent-scale satellite inference while managing massive data pipelines, distributed compute, and automatically recovering from failures at scale.
Who gets to understand AI? — Why fully open models and research artifacts are essential to independent scrutiny, broader participation, and continued U.S. scientific leadership in AI.