Amazon's AGI Lab chief David Luan is pushing back against criticism of his controversial "reverse acquihire" from AI startup Adept. The former Adept CEO says he chose Amazon's multi-billion-dollar compute resources over building another "small model" enterprise company, as tech giants increasingly poach entire startup teams to accelerate their AI ambitions.
Amazon's newest AI research chief is doubling down on his decision to abandon his own startup for the tech giant's deep pockets. David Luan, who left his role as CEO of AI startup Adept to head Amazon's AGI Lab, told The Verge he hopes to be "remembered more as being an AI research innovator rather than a deal structure innovator."
The comment comes as Luan faces scrutiny over Amazon's reverse acquihire of his team last year - one of the first high-profile examples of a deal structure that's reshaping how tech giants compete for AI talent. Unlike traditional acquisitions, reverse acquihires see large companies hire key startup personnel and license their technology while leaving the original company intact.
"It's perfectly rational" for companies like Amazon to "put together critical mass on both talent and compute right now," Luan explained during the interview with reporter Alex Heath. The admission reveals how the current AI arms race has fundamentally altered traditional startup exit strategies, with founders increasingly choosing corporate resources over independence.
Luan's reasoning centers on the astronomical computational requirements for advancing artificial general intelligence. "Every single one of them is going to require two-digit billion-dollar clusters to go run it," he said, referring to what he calls "the four crucial remaining research problems left to AGI." The comment underscores the growing divide between well-funded corporate labs and resource-constrained startups in the race toward AGI.
The Amazon executive's position reflects a broader shift in Silicon Valley's talent dynamics. According to Financial Times reporting, reverse acquihires have become increasingly common as companies like , , and Amazon compete for scarce AI expertise without the regulatory scrutiny that traditional acquisitions might trigger.
