Closing gaps with competitors
Meta has struggled to keep up with OpenAI, Anthropic, and other key competitors in the AI race, recently even delaying the launch of its new flagship model, Behemoth, purportedly due to internal concerns about its performance. It has also seen the departure of several of its top researchers.
“It’s not really a secret at this point that Meta’s Llama 4 models have had significant performance issues,” Mayham said. “Zuck is essentially betting that Wang’s track record building AI infrastructure can solve Meta’s alignment and model quality problems faster than internal development.” And, he added, Scale’s enterprise-grade human feedback loops are exactly what Meta’s Llama models need to compete with ChatGPT and Claude on reliability and task-following.
Data quality, a key focus for Wang, is a big factor in solving those performance problems. He wrote in a note to Scale employees on Thursday, later posted on X (formerly Twitter), that when he founded Scale AI in 2016 amidst some of the early AI breakthroughs, “it was clear even then that data was the lifeblood of AI systems, and that was the inspiration behind starting Scale.”
This story originally appeared on Computerworld
