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OpenAI’s CFO says the company is passing on opportunities because it does not have enough compute

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OpenAI is turning down some opportunities this year because it doesn’t have enough computing power to support them, according to its CFO Sarah Friar.

“We’re making some very tough trades at the moment and things we’re not pursuing because we don’t have enough compute,” Friar told ARK Invest CEO Cathie Wood in an interview released this week.

Friar said the issue is particularly acute in 2026, as demand for AI continues to surge globally.

“Today, I do spend a lot of time trying to find any last-minute compute available here in 2026,” she said.

OpenAI President Greg Brockman echoed that pressure in an interview on the “Big Technology Podcast” released Wednesday, saying the company has struggled to keep up with demand.

Their comments highlight a growing constraint across the AI industry: even the most advanced companies are being limited by access to the computing power needed to train and run models.

“If you do not have it [compute], you do not have revenue. That is one thing I know for sure,” Friar said.

Compute limits force trade-offs

The shortage is forcing OpenAI to make strategic trade-offs.

Brockman said the company is prioritizing a small number of core use cases, including a personal AI assistant and tools that can solve complex tasks, because it “can’t possibly get to all of them” given current compute limits.

That dynamic is already shaping product decisions. OpenAI has pulled back from some initiatives — including discontinuing its video app Sora — as it focuses resources on core, revenue-generating AI products.

The company, which now serves around 900 million consumers and more than 1 million businesses, Friar said, is raising huge sums. It recently completed a $122 billion funding round, in part to secure future compute capacity.

“We cannot build compute fast enough to keep up with demand,” Brockman said, describing what he called “very painful decisions” about what to launch and where to allocate resources.

OpenAI is making “multi-year commitments” to secure future capacity, Friar said.

Other AI companies appear to be facing similar constraints.

Anthropic recently tightened usage caps for its Claude model during peak hours, a sign that even leading model makers are struggling to keep up with surging demand.

For now, a basic constraint remains: even in the age of AI, you can’t scale without the hardware behind it.




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AMD’s CEO says AI will need 10 ‘yottaflops’ of compute — here’s what that actually means

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AI needs so much computing power that AMD CEO Lisa Su put it in terms of a unit most people have never heard of: the yottaflop.

Su said in her keynote at CES 2026 on Tuesday that the world would need more than “10 yottaflops” of compute — a measure of how fast a computer is — over the next five years to keep up with AI’s growth.

“How many of you know what a yottaflop is?” Su asked the audience. “Raise your hand, please,” she added, before quickly explaining the term herself when no one appeared to raise their hand.

“A yottaflop is a one followed by 24 zeros. So 10 yottaflop flops is 10,000 times more compute than we had in 2022,” she said.

In computing, a flop is a single basic math calculation. A computer doing 1 billion calculations per second is equal to a gigaflop. A yottaflop is equivalent to a computer performing one septillion calculations per second.

In theory, scientists say 10 yottaflops would be enough computing power to run complex, atom-level simulations for entire planets.

In 2022, global AI compute stood at about one zettaflop — a one followed by 21 zeros. By 2025, Su said, that figure had already surged to more than 100 zettaflops.

“There’s just never, ever been anything like this in the history of computing,” she said at the Las Vegas conference.

Su’s 10 yottaflop prediction is about 5.6 million times faster than the most powerful supercomputer today — the US Department of Energy’s El Capitan.

However, powering today’s AI compute is already putting a strain on the US power grid. The build-out of energy infrastructure would be a big bottleneck in scaling up AI compute power.

During the keynote, Su also used the stage to unveil AMD’s next generation of AI chips, including its MI455 GPU, as the company pushes deeper into supplying data-center hardware for customers such as OpenAI.




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