One afternoon in April, Cecilia Garraffo settled down at the head of a conference room table in Cambridge, Massachusetts, and gazed out at what might be the last astrophysicists of their kind.
The walls of this room had, in the past, reverberated with the din of thousands of other groups of scientists. Now, as streaks of sunlight poured in, the discussions turned to nonhuman collaborators. One by one, the gathered researchers discussed how they planned to apply machine learning to problems in astronomy. Observing an interstellar comet. Discerning wispy filaments of galaxies at the universe’s largest scales. Developing a new “tokenizer” that can translate astrophysical images into a form more readable by artificial intelligence (AI). “Sometimes models will be overconfident,” Garraffo warned a junior team member.
Afterward, as everyone filed out, black hole researcher Daniel Palumbo made a brief announcement. Representatives from AI chipmaker NVIDIA were on campus in search of scientists who wanted to solve problems using their hardware. To anyone who might need extra processing power, “today’s the day,” he said.
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