Closing gaps with opponents
Meta has struggled to maintain up with OpenAI, Anthropic, and different key opponents within the AI race, lately even delaying the launch of its new flagship mannequin, Behemoth, purportedly resulting from inside issues about its efficiency. It has additionally seen the departure of a number of of its prime researchers.
“It’s probably not a secret at this level that Meta’s Llama 4 fashions have had important efficiency points,” Mayham mentioned. “Zuck is basically betting that Wang’s observe report constructing AI infrastructure can remedy Meta’s alignment and mannequin high quality issues quicker than inside growth.” And, he added, Scale’s enterprise-grade human suggestions loops are precisely what Meta’s Llama fashions must compete with ChatGPT and Claude on reliability and task-following.
Knowledge high quality, a key focus for Wang, is a giant consider fixing these efficiency issues. He wrote in a observe to Scale staff on Thursday, later posted on X (previously Twitter), that when he based Scale AI in 2016 amidst a few of the early AI breakthroughs, “it was clear even then that knowledge was the lifeblood of AI programs, and that was the inspiration behind beginning Scale.”
