Zuckerberg Says AI Talent Wants More GPUs, Less Bureaucracy — Not Just Big Money

As Meta continues its bold push into artificial intelligence, CEO Mark Zuckerberg has offered insights into what truly drives top AI researchers to join his company — and it’s not just the massive paychecks making headlines.

In a recent conversation on The Information’s TITV, Zuckerberg addressed reports claiming that Meta has offered salaries as high as ₹1,600 crore ($200 million) to AI specialists. While he acknowledged that compensation plays a role, he emphasized that elite researchers are more interested in autonomy and cutting-edge tools than in managing large teams or collecting oversized paychecks.

"Historically, when I was recruiting people to different parts of the company, people are like, 'Okay, what's my scope going to be?'" Zuckerberg shared. "Here, people say, 'I want the fewest number of people reporting to me and the most GPUs.'"

GPUs — or graphical processing units — are essential for training advanced AI models. Meta, like other major tech firms, relies heavily on Nvidia’s top-tier chips, such as the H100s, to power its large language models and AGI initiatives. According to Zuckerberg, ensuring that each researcher has access to maximum computing power is a major strategy in attracting world-class talent.

This approach seems to be working. Meta’s current AI hiring spree is among the most aggressive Silicon Valley has seen. The company has successfully drawn in top minds from rivals including OpenAI, Google DeepMind, Apple, and Anthropic. Among the most notable hires are Trapit Bansal, previously with OpenAI, and Ruoming Pang from Apple. Both are now part of Meta’s ambitious new Superintelligence Lab.

Led by former GitHub CEO Nat Friedman and Scale AI founder Alexandr Wang, the lab is quickly becoming a heavyweight in the race toward Artificial General Intelligence (AGI) — AI systems capable of reasoning and learning like humans. The team now includes at least 11 prominent names from Google and OpenAI, including Lucas Beyer, Xiaohua Zhai, Jack Rae, Johan Schalkwyk, Ji Lin, Shengjia Zhao, and Jiahui Yu.

Backing this talent pool is an equally massive infrastructure buildout. Meta recently unveiled plans for a next-generation AI supercluster named Prometheus, expected to go live by 2026. It will be supported by sprawling data centres — including the 5-gigawatt Hyperion — making it one of the largest AI infrastructure efforts globally.

In a move reminiscent of Elon Musk’s “tent factories” at Tesla, Meta has also started constructing temporary tent-based data centres. These prefabricated facilities allow the company to begin AI model training earlier, even before the full infrastructure is in place.

The urgency behind these moves’ stems in part from mixed reactions to Meta’s Llama 4 model earlier this year. Since then, the company has revised its roadmap, committing $14 billion to Scale AI for improved training data and dramatically stepping up its AI recruitment game.

With its unique mix of raw computing power, operational freedom, and a robust infrastructure plan, Meta is positioning itself as a serious contender in the global race for AGI — and not merely by throwing money at the problem.