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Home›Science & Tech›Ideas and opportunities for transforming science with AI

Ideas and opportunities for transforming science with AI

By admin1
September 21, 2022
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September 21, 2022 — Researchers and representatives from the U.S. Department of Energy (DOE) will attend this year’s Monterey Data Conference, hosted by a group of scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) and sponsored by the Fast Computing Association. people gathered. Laboratories, academia, and industry for robust programs designed around the theme of transforming science with artificial intelligence (AI).

Through presentations, panels, and networking events, attendees finished the three-day event with new inspiration, new connections, and new understandings of how AI is being used across a wide range of scientific disciplines.

“Our goal was to bring people together in the DOE lab space, including leaders in high-level positions, scientists doing hands-on research in the field, and a contingent of relevant industry representatives. said Steve Farrell. He is a Machine Learning Engineer in the Data and Analytics Services Group at the National Energy Research Scientific Computing Center (NERSC) and a conference coordinator.

NERSC Division Director Sudip Dosanj said: “Data and AI are very important topics for his DOE lab, and the conference brought together scientists, computer scientists, and computer companies to discuss how to tackle new scientific challenges.”

Nearly 100 attendees gathered for an invitation-only event at a venue overlooking California’s Monterey Bay after a two-year hiatus due to the pandemic. The program featured invited talks and panel discussions on scalable and productive computing systems for AI. Interpretable, Robust, Science-Based AI Methods. A new scientific AI application. AI for automated driving of scientific facilities. Data management for scientific AI. Computing and AI in extreme conditions.

“The session was really good. I was impressed with the quality of every speaker on every panel,” said Farrell. “Many people were discussing some pretty advanced, cutting-edge issues in AI applications and methods.”

A panel on climate science applications for AI, using AI for HPC simulation workloads, and diversity, equity, and inclusion were all featured on day one of the event. Conference keynote speaker Pamela Isom, director of her DOE Artificial Intelligence Technology Office (AITO), spoke about the need for governance in AI.

Throughout the conference, speakers and topics represented a range of AI applications, from space exploration to self-driving technology to food system management. Benchmarking AI was also a popular topic, especially given Farrell’s own research focus. Slides from his presentations at many conferences are available online to give you a sense of the opportunities and challenges of adopting AI in multiple scientific disciplines.

“After having to postpone these kinds of in-person events for several years due to the pandemic, I am now able to have the opportunity to network with others, meet everyone, hear more about their work and shape it. It’s been a great collaboration,” Farrell said. “We plan to make this an annual event.”

NERSC is a user facility of the DOE Office of Science.

About NERSC and Berkeley Lab

The National Energy Research Scientific Computing Center (NERSC) is an Office of Science User Facility of the U.S. Department of Energy and serves as the primary high-performance computing center for scientific research sponsored by the Office of Science. The NERSC Center at Lawrence Berkeley National Laboratory is a collection of national laboratories and universities working on a wide range of problems in combustion, climate modeling, fusion energy, materials science, physics, chemistry, computational biology, and other fields. It serves over 7,000 scientists. Berkeley Lab is a DOE National Laboratory in Berkeley, California. It conducts unclassified scientific research and is administered by the University of California for the U.S. Department of Energy. »Learn more about computing science at Berkeley Lab.


Source: Keri Trautman, NERSC

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