In the second episode in our series on foundation models for science, we discuss Oak Ridge National Laboratory's work and hear about lessons learned from the recent 1000 Scientists AI Jam, a recent event that brought together researchers from several Department of Energy national laboratories, OpenAI and Anthropic. My guest is Prasanna Balaprakash, ORNL's director of AI programs. We talk about how foundation models could help with climate forecasts and his team's 2024 Gordon Bell finalist research and futuristic work that applies principles of swarm intelligence for managing distributed computing resources.

Prasanna Balaprakash has been the director of artificial intelligence programs at Oak Ridge National Laboratory (ORNL) since March 2023. Previously he had worked as a postdoctoral researcher and staff computer scientist at Argonne National Laboratory. He was a 2018 recipient of a Department of Energy Early Career Research Program award.

Large language models aren't just powering chatbots like ChatGPT. This type of computational model is an example of a particular flavor of artificial intelligence known as foundation models, which are trained on vast amounts of data to make inferences in new areas. Although text is one rich data source, science offers many more from biology, chemistry, physics and more. Such models open up a tantalizing new set of research questions. How effective are foundation models for science? How could they be improved? Could they help researchers work on challenging questions? And what might they mean for the future of science?

This episode begins a series where we'll explore these questions and more, talking with computational scientists about their work with foundation models and the opportunities and challenges in this exciting, rapidly changing area of research. We'll start by talking with Ian Foster of Argonne National Laboratory and the University of Chicago about AuroraGPT, a foundation model being developed for science and named for Argonne's new exascale computer.

You'll meet:

Ian Foster is a senior scientist at Argonne National Laboratory where he directs the data science and learning division. He’s also a professor of computer science at the University of Chicago. He is the co-leader of the data team for Argonne's AuroraGPT project.

Wrapping up our discussion of the 2024 Nobel Prizes in Physics and Chemistry, computer scientist Mansi Sakarvadia and computational structural biologist Josh Vermaas talk about the recent prizes and what they mean for science. You'll hear about how the prizes both break down research barriers and introduce concerns about misinformation and public trust. The research honored with the chemistry prize has already changed how researchers study questions that involve understanding proteins' structures. For more on the 2024 Nobel Prizes, check out our recent interview with Anil Ananthaswamy.

You'll meet:

Mansi Sakarvadia is a Ph.D. student in the computer science department at the University of Chicago and a current Department of Energy Computational Science Graduate Fellow. She studies ways to interpret how machine learning models work.

Josh Vermaas is an assistant professor at Michigan State University. His research in computational structural biology focuses on understanding photosynthesis and energy transfer processes in plants as part of the MSU-DOE Plant Research Laboratory.

2024 was artificial intelligence’s Nobel Prize year with the physics and chemistry prizes recognizing the underpinnings and application of these algorithms. Science journalist and author Anil Ananthaswamy spent years writing a popular book, Why Machines Learn: The Elegant Math Behind Modern AI, that explores the equations and historical context for this technology.

In this conversation, Anil and host Sarah Webb explore that math and history, the significance of these Nobel Prizes for both AI and science, and the challenges that come with this powerful and fast-moving technology.

You’ll meet:

Anil Ananthaswamy is an award-winning journalist and journalist-in-residence at the Simons Institute for the Theory of Computing at the University of California, Berkeley. Previously he has worked as a staff writer and editor for New Scientist magazine. He has written four books including Why Machines Learn: The Elegant Math Behind Modern AI (Dutton, 2024).

The annual Supercomputing meeting (SC24) convenes November 17-22 in Atlanta with the theme of HPC creates, and Science in Parallel previews a special display at the meeting: the Art of HPC. Host Sarah Webb interviews Sadie Bartholomew of the United Kingdom's National Centre for Atmospheric Science and the University of Reading about her work as a research software engineer and her passion for creative coding. She submitted several pieces of digital art that will be displayed at SC24.

Sadie discussed the many patterns in her work—within weather and climate, in coding and in digital art. She makes her pieces using matplotlib, a visualization tool in Python. She talks about the synergy and fulfillment she finds at the interface of computing and aesthetic pursuits.

Early in her applied math journey, Paulina Rodriguez was a little skeptical of calculators and computers. But her desire to really understand what’s going on under the hood has ultimately led to satisfying research. During her Ph.D., she’s explored the credibility of computational models for medical device applications, making sure that researchers understand the accuracy, validity and uncertainty of simulated results.

Paulina shares how she honed her problem-solving skills and creativity as she navigated her education. Her enthusiasm and determination are infectious, and she describes her personal struggle to bring her whole self to her work.

You'll meet:

Paulina Rodriguez, a Ph.D. student in applied math at George Washington University and a fourth-year recipient of the Department of Energy Computational Science Graduate Fellowship (DOE CSGF). Paulina completed her bachelor’s degree at University of California, Santa Cruz and master’s degree at Claremont Graduate University, both in mathematics. Her current research focuses on establishing methods for assessing the credibility of computational models for medical device applications, work that she’s doing at Sandia National Laboratories in New Mexico in collaboration with the U.S. Food and Drug Administration.

Episode artwork created using ChatGPT from prompts by Paulina Rodriguez.

Science communication often attracts people with diverse interests, who thrive in multiple roles. Paul Sutter is no exception: he’s an astrophysicist, host, author and more. He’s also a visiting professor at Barnard College, Columbia University. Paul’s roots are in computational science, and he shares how his many projects continue to build on that foundation. We also discuss his most recent book: Rescuing Science: Restoring Trust in an Age of Doubt, which critiques today’s scientific enterprise and and offers ideas for supporting a better future.

You'll meet:

Paul M. Sutter is a theoretical cosmologist, science communicator, media host, NASA advisor and U.S. cultural ambassador. He is currently a visiting professor at Barnard College, Columbia University. He completed his physics Ph.D. in 2011 at the University of Illinois Urbana-Champaign, where he was supported by a Department of Energy Computational Science Graduate Fellowship. He also held a joint position as chief scientist at the Center of Science and Industry in Columbus, Ohio, and as a cosmological researcher at the Ohio State University.

Video games are everywhere, but the fundamental elements that generate human reactions such as suspense or surprise aren’t understood. Instead, game designers start from scratch each time they want to build a new experience for players.

Rogelio Cardona-Rivera of the University of Utah wants to understand games and the fundamental elements that make people respond as they do—as a science of games. The research is important for more than just gaming—Rogelio is working on a variety of projects, including artificial intelligence research, technology for Indigenous storytelling and virtual reality in math education.

Join us for a conversation about the emerging field of technical games research that also dives into the creative and communications challenges of working at the bleeding edge of disparate fields: computer science, cognitive science, narrative and more.

You’ll meet:

Rogelio Cardona-Rivera is an assistant professor of games at the University of Utah. Rogelio completed their Ph.D. at North Carolina State University in 2019, supported by a Department of Energy Computational Science Graduate Fellowship and funding from the National GEM Consortium. Their undergraduate degree is in computer engineering from the University of Puerto Rico at Mayagüez.