Science, the magazine that is part of the American Association for the Advancement of Science (AAAS), reports that the U.S. Department of Energy (DOE) is planning to ask the US Congress for “between $3 billion and $4 billion over 10 years.” Science says that this is “roughly the amount the agency is spending to build next-generation “exascale” supercomputers”. This major AI initiative on the part of DOE has a goal to speed up scientific discoveries.
Earl Joseph, CEO of Hyperion Research, a high-performance computing analysis firm in St. Paul that tracks AI research funding is of the opinion that this could be a good starting point but also notes that “DOE’s planned spending is modest compared with the feverish investment in AI by China and industry.”
On the other hand, Science points to DOE’s one big asset, and that is an abundance of that that it could use. For example, it funds atom smashers, surveys of the universe, and the sequencing of thousands of genomes.
DOE already held four town halls in support of its initiative, where Chris Fall, director of DOE’s Office of Science said that his office generates “almost unimaginable amounts of data, petabytes per day and that algorithms trained with these data could help discover new materials or spot signs of new physics.“
Science also noted that according to IDC, worldwide corporate AI funding is expected to hit $35.8 billion this year, up 44% from 2018. U.S. President Donald Trump signed an executive order launching the American AI Initiative, and the administration requested nearly $1 billion for AI and machine learning research in the fiscal year 2020 across all civilian agencies, according to the U.S. Office of Science and Technology Policy. The U.S. Department of Defense is seeking a similar level of funding for unclassified military AI programs.
For its part, in 2017, China announced a national AI plan that aims for global leadership, and a projected commercial AI market worth 1 trillion yuan ($140 billion) by 2030. And the European Union has committed to spending €20 billion through 2020.
According to Hyperion Research, China accounted for 60% of all investments in AI from 2013 to 2018. U.S. investments were about 30% of the global total. China dominates the number of AI publications, whereas the European Union has the most AI researchers, Joseph says. But U.S. researchers in AI get the most citations per paper, he says, suggesting their research has the most impact.
While DOE has not yet come up with a detailed program, its officials say that their AI initiative “will help keep U.S. researchers at the forefront.” Rick Stevens, associate laboratory director for computing, environment, and life sciences at Argonne National Laboratory in Lemont, Illinois expects that the funding will include the capabilities for “national labs to optimize existing supercomputers for AI, and external funding for academic research into AI computer architectures.”
Jeff Nichols, associate laboratory director for computing and computational science at Oak Ridge National Laboratory in Tennessee, concluded that “AI won’t replace scientists, but scientists who use AI will replace scientists who don’t.”
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