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It’s being hailed — at least by some — “the next generation of the way we do science.”
The U.S. Department of Energy’s (DOE) Argonne National Laboratory is leading projects to use Artificial Intelligence to speed “transformative discoveries” in science. The lab recently received a $37 million grant from the DOE to further its projects.
“With machine learning and artificial intelligence, the computer plays an active role, which means it gives you its answers, predictions or possibilities that maybe a human didn’t think of,” said Brahim Mustapha, an accelerator physicist in Argonne’s Physics division, who oversees one of the many AI-related projects in development at the laboratory.
Some current projects include:
- Creating AI-powered “digital twins” of research environments, to predict outcomes based on experimental controls, and make actual use of facilities such as the Advanced Photon Source more efficient.
- Using machine learning to better understand what happens when a material fails, so that a stronger material can be designed in its place.
- Collecting extensive amounts of data to categorize and synthesize new materials for future experiments.
According to a fact paper released last week, computer and technology advances are rapidly evolving to the point where AI is taking a larger role in research. And just like in other areas, such as military operations or business intelligence and analytics, scientists are contemplating a future where AI will outstrip humans in capabilities.
The Dawn of “Aurora”
An exascale supercomputer dubbed Aurora, due to come online in 2022, will reportedly help researchers make much faster experimental advances. The computer is designed to handle vast amounts of data and to “support AI-powered research.”
Researcher Subramanian Sankaranarayanan pointed to practical examples of how AI is allowing scientists to handle and utilize growing amounts of data:
“For example, can we make a prediction about what the next mutation of the virus that causes COVID-19 is going to look like? The use of AI now makes it possible to search through this giant space and identify the kinds of mutations that may happen,” he said. “This could also apply to research on materials for battery applications, various forms of energy storage or the effects of pollutants on the environment. There are so many areas that will benefit.”
But scientists admit that they don’t know what the ultimate impacts of AI’s growing role in scientific research will be. According to Ian Foster, director of Argonne’s Data Science and Learning division:
“There’s an old saying that people always overestimate the short-term impact of innovations, but underestimate the long-term aspects… While short-term things might move more slowly than we like, long-term AI will change many aspects of society, even in ways we don’t fully understand yet.”