Meta has been blowing minds by luring away AI researchers from rival labs with pay packages of as much as $250 million, but there might be sound business sense behind these extravagant numbers.
Andrew Ng, one of the pioneers of AI and a prominent AI educator, has explained why AI labs are offering extravagant pay packages to AI researchers. “Recently Meta made headlines with unprecedented, massive compensation packages for AI model builders exceeding $100M (sometimes spread over multiple years),” he wrote on X. “With the company planning to spend $66B-72B this year on capital expenses such as data centers, a meaningful fraction of which will be devoted to AI, from a purely financial point of view, it’s not irrational to spend a few extra billion dollars on salaries to make sure this hardware is used well,” he said.
“A typical software-application startup that’s not involved in training foundation models might spend 70-80% of its dollars on salaries, 5-10% on rent, and 10-25% on other operating expenses (cloud hosting, software licenses, marketing, legal/accounting, etc.). But scaling up models is so capital-intensive, salaries are a small fraction of the overall expense. This makes it feasible for businesses in this area to pay their relatively few employees exceptionally well. If you’re spending tens of billions of dollars on GPU hardware, why not spend just a tenth of that on salaries? Even before Meta’s recent offers, salaries of AI model trainers have been high, with many being paid $5-10M/year, although Meta has raised these numbers to new heights” he continued.
Ng also explained why Meta was going in so heavily on AI. “Many of Meta’s properties rely on user-generated content (UGC) to attract attention, which is then monetized through advertising. AI is a huge threat and opportunity to such businesses: If AI-generated content (AIGC) substitutes for UGC to capture people’s attention to sell ads against, this will transform the social-media landscape. This is why Meta — like TikTok, YouTube, and other social-media properties — is paying close attention to AIGC, and why making significant investments in AI is rational,” he said.
“Further, when Meta hires a key employee, not only does it gain the future work output of that person, but it also potentially gets insight into a competitor’s technology, which also makes its willingness to pay high salaries a rational business move (so long as it does not adversely affect the company’s culture),” Ng explained.
These arguments make a lot of sense. Meta is spending tens of billions of dollars in setting up infrastructure, $100 million salaries to make sure the datacenters are used well look reasonable in comparison. Also, by acquiring researchers from rival labs, Meta can often immediately access years of know-how developed at these labs, making these researchers especially valuable. It remains to be seen if these multi-hundred-million dollar salaries sustain, but there’s never been a better time to be a cutting-edge AI researcher — they’re making the same amount of money that was once the preserve of top sports stars.