1,000 Scientist AI Jam kicks off at Argonne
First-ever gathering will drive DOE’s AI-powered scientific future
image: Hundreds of scientists gathered at Argonne to explore the latest AI models as part of the 1,000 Scientist AI Jam held at nine DOE national labs.
Credit: Image by Argonne National Laboratory.
By Julie Parente | March 17, 2025
Scientists had a hands-on opportunity with cutting-edge models to explore AI’s potential as a research assistant.
The U.S. Department of Energy’s (DOE) Argonne National Laboratory co-hosted a groundbreaking event that explored the potential of artificial intelligence (AI) in scientific research.
The first-ever 1,000 Scientist AI Jam on Feb. 28 exceeded expectations by bringing together 1,500 scientists across DOE’s national laboratories to push the boundaries of AI-driven discovery and maintain U.S. leadership in AI.
The AI Jam convened the nation’s leading scientists to explore advanced AI reasoning models, applying them to complex, real-world scientific challenges. Participants explored how AI could enhance aspects of research including hypothesis generation, experiment automation and computational modeling.
“This session isn’t just about testing AI capabilities — it’s about shaping the future of AI in science.” — James Donovan, Research Partnerships Lead at OpenAI
“The AI Jam is a first step in broader collaboration between DOE scientists and commercial AI research labs to create better AI models for scientific reasoning and research,” said Rick Stevens, Argonne’s Associate Laboratory Director for Computing, Environment and Life Sciences. “We’re coupling the scientific and engineering expertise and experimental facilities at DOE labs with the world-leading AI capabilities of American commercial AI labs. No one else in the world can do that.”
The event was hosted at multiple DOE national laboratories, including Argonne, Lawrence Berkeley National Laboratory, Brookhaven National Laboratory, Idaho National Laboratory, Lawrence Livermore National Laboratory, Los Alamos National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Princeton Plasma Physics Laboratory. Scientists from other DOE labs also participated.
Scientists worked individually and in small teams, each bringing domain-specific scientific problems to test the capabilities of AI models from OpenAI and Anthropic. This hands-on approach allowed researchers to assess AI performance in solving complex challenges and provided valuable data on model efficacy across diverse scientific tasks.
“Today’s collaboration of DOE’s national labs and technology companies is an important step in our efforts to secure America’s future,” U.S. Secretary of Energy Chris Wright said.
“This session isn’t just about testing AI capabilities — it’s about shaping the future of AI in science,” said James Donovan, Research Partnerships Lead at OpenAI. “By collaborating with the nation’s top scientific institutions, we can refine AI models to be more effective, reliable and attuned to the needs of researchers tackling the world’s biggest challenges.”
At Argonne, 280 scientists gathered at tables that filled two large rooms in the Theory and Computing Science conference center. On the wall huge screens showed video feeds of scientists working similarly at the other DOE labs. There was conversation and laughter in the room as scientists talked with colleagues and sought advice from the AI experts on hand.
“I’m enjoying the feedback, ideas and creativity here,” said Sarah Owens, the Sequencing Laboratory manager at Argonne’s Environmental Sample Preparation and Sequencing Facility. She was impressed with the AI models’ ability to answer tough questions about wastewater pathogen detection.
Massimiliano “Max” Delferro, an Argonne chemist and group leader of the Catalysis Science Program, was exploring questions about polymer deconstruction but also appreciated the model’s ability to do coding.
“It’s really exciting for us to accelerate discovery,” he said. “Today we have people from multiple domains — chemists, physicists, nuclear engineers, computer scientists, data scientists and more — all coming together for science.”
Computational biologist Nicholas Chia has been working with AI models for some time and said it’s amazing how advanced their abilities have become. Chia builds large language models for biology to research the origins of life.
“I hope we get insight into what scientists really need out of these models,” he said. “There’s been a lot of guessing so far, but in science we want very specific reasoning, so I hope we push forward on scientific solutions with AI.”
Advanced AI reasoning models will help improve the power grid, advance U.S. manufacturing, design new materials, discover cancer therapeutics and medical treatments, accelerate the move to nuclear power and more, Stevens said.
The insights gained from the jam session will inform advancements in AI-assisted scientific discovery. Future AI Jam sessions will expand to include models from other commercial AI research labs, fostering a broader ecosystem of AI-driven scientific research.
Argonne National Laboratory seeks solutions to pressing national problems in science and technology by conducting leading-edge basic and applied research in virtually every scientific discipline. Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.
The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science.