Silicon Valley is pricing academics out of AI research

That's an article by Naomi Nix, Cat Zakrzewski and Gerrit De Vynck in today's Washington Post.

... the sky-high cost of working with AI models is boxing researchers out of the field, compromising independent study of the burgeoning technology.

As companies like Meta, Google and Microsoft funnel billions of dollars into AI, a massive resources gap is building with even the country’s richest universities. Meta aims to procure 350,000 of the specialized computer chips — called GPUs — necessary to run gargantuan calculations on AI models. In contrast, Stanford’s Natural Language Processing Group has 68 GPUs for all of its work.

To obtain the expensive computing power and data required to research AI systems, scholars frequently partner with tech employees. Meanwhile, tech firms’ eye-popping salaries are draining academia of star talent.

Big tech companies now dominate breakthroughs in the field. In 2022, the tech industry created 32 significant machine learning models, while academics produced three, a significant reversal from 2014, when the majority of AI breakthroughs originated in universities, according to a Stanford report.

Researchers say this lopsided power dynamic is shaping the field in subtle ways, pushing AI scholars to tailor their research for commercial use. Last month, Meta CEO Mark Zuckerberg announced the company’s independent AI research lab would move closer to its product team, ensuring “some level of alignment” between the groups, he said.

I'm not sure what I think about this. I'm inclined to think that the academic world is more interested in talking about breakthrough research – "to boldly go where no man has gone before" – than in actually performing it. But I can't say that industry seems any better on that score. Simply scaling up on current architectures will not deliver the breakthroughs we need.

There's more at the link.

H/t Tyler Cowen.