For years, the assumption inside Silicon Valley was that Facebook—now Meta—held the best cards in artificial intelligence. The company had the data, the engineers, and the cash. It had already built the social infrastructure that defined the internet.
When generative AI exploded, the conventional wisdom said Meta would be the one to capitalize. That did not happen.
Chamath Palihapitiya, a former Facebook vice president who helped grow the platform to billions of users, told Axios this week that Meta chief executive Mark Zuckerberg “completely fumbled” the opportunity. The company, he said, failed to move decisively while Nvidia and its CEO Jensen Huang raced ahead to become the central supplier in the AI ecosystem. Nvidia now sells the chips that power nearly every major generative AI system.
Meta, for all its resources, is playing catch-up. Palihapitiya is not an outsider taking cheap shots.
He was inside the machine. He helped build the user base that made Facebook a global force. His criticism carries weight because he knows how the company operates—or at least, how it used to.
When Axios asked him how Meta lost its advantage, he said he no longer has the internal knowledge to explain the failure. “I don’t know the organisation well enough, nor do I understand the political dynamics to understand why they failed as miserably as they have. But they’ve profoundly failed,” he said.
That is a stark admission from someone who once sat at the table. Palihapitiya drew a direct line between this moment and an earlier missed opportunity.
While still at Facebook, he tried to persuade the company to build its own smartphone platform. He believed Facebook could have carved out a strategic position in mobile hardware, controlling the operating system that billions of people would use. The company passed.
Apple and Google locked in the mobile duopoly. Facebook became a tenant on other people’s property.
The pattern is repeating. In the early days of the generative AI boom, Meta had the data centers, the research talent, and the long-term ambition. It poured money into AI research.
It released large language models. But it did not move fast enough to dominate the infrastructure layer—the chips, the cloud systems, the developer ecosystems that now funnel billions of dollars to Nvidia. Huang’s company now holds a near-monopoly on the hardware that powers the AI revolution.
Meta, meanwhile, is still figuring out how to integrate generative AI into its products without breaking its ad business. The implications go beyond one company’s stock price.
Meta’s stumble means the center of gravity in AI has shifted away from the social media giants and toward hardware and infrastructure firms. Nvidia is now worth more than Meta. The companies that control the physical machinery of AI—the chips, the data center designs, the networking gear—are setting the terms.
Meta, for all its user data, is a customer. Palihapitiya did not offer a fix.
He said he does not understand the internal politics that led to the failure. That itself is telling. A former executive who helped build the company cannot explain why it missed the biggest technology shift in a decade.
It suggests the problem is not a single bad decision but something deeper—a culture, a structure, a leadership blind spot that keeps repeating. Meta still has time. It has money.
It has talent. But the AI race is not a marathon with a late start.
It is a land grab. Nvidia has already claimed the most valuable territory. Every quarter that passes without a decisive move from Menlo Park makes the gap harder to close.
Palihapitiya’s warning is not just about the past. It is about what comes next.
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