Eye-catching advances in some AI fields are not real

guest · Jun 2, 2020

Eye-catching advances in some AI fields are not real
May 27, 2020
https://www.sciencemag.org/news/2020/05/eye-catching-advances-some-ai-fields-are-not-real

Artificial intelligence (AI) just seems to get smarter and smarter. Each iPhone learns your face, voice, and habits better than the last, and the threats AI poses to privacy and jobs continue to grow.
The surge reflects faster chips, more data, and better algorithms.
But some of the improvement comes from tweaks rather than the core innovations their inventors claim—and some of the gains may not exist at all, says Davis Blalock, a computer science graduate student at the Massachusetts Institute of Technology (MIT).

The researchers evaluated 81 pruning algorithms, programs that make neural networks more efficient by trimming unneeded connections. All claimed superiority in slightly different ways. But they were rarely compared properly—and when the researchers tried to evaluate them side by side, there was no clear evidence of performance improvements over a 10-year period.
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The result, presented in March at the Machine Learning and Systems conference, surprised Blalock’s Ph.D. adviser, MIT computer scientist John Guttag, who says the uneven comparisons themselves may explain the stagnation. “It’s the old saw, right?” Guttag said. “If you can’t measure something, it’s hard to make it better.”

Kolter says researchers are more motivated to produce a new algorithm and tweak it until it’s state-of-the-art than to tune an existing one. The latter can appear less novel, he notes, making it “much harder to get a paper from.”
Some of the overstated performance claims can be chalked up to the explosive growth of the field, where papers outnumber experienced reviewers.
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