Perplexity CEO points to AI compute bottlenecks, suggesting Micron could outpace Meta in market value

Perplexity co-founder and CEO Aravind Srinivas said Micron Technology could eventually surpass Meta Platforms in market capitalization, delivering a blunt take on where power for modern artificial intelligence is headed. In an interview reported by Yahoo Finance, Srinivas attributed the shift to supply-and-demand constraints around the hardware needed for AI systems, saying the company or industry that becomes the bottleneck could see outsized gains.

The claim, while speculative, lands amid intense scrutiny of the AI stack, where investors and executives have increasingly focused not only on model developers and platform distribution, but also on the enabling layers that can limit performance or scale. Srinivas’s view frames semiconductors and memory as the chokepoints, rather than purely the software and user-facing products that typically capture headlines.

Micron is a leading supplier of memory technologies used across computing systems. In AI contexts, memory and high-performance compute components are critical for training workloads and for inference, the process of producing responses from deployed models. Meta, by contrast, is primarily known as a large-scale social and advertising platform, but it also operates major AI research and infrastructure initiatives to support ranking, recommendations, and model-based services. The question raised by Srinivas is whether market leadership will follow the constraints of supply for AI hardware more than the visibility of AI-driven applications.

Meta did not address Srinivas’s remarks in the information available for this report. The only official link provided is Meta’s newsroom homepage, which is broad and does not contain a directly cited statement tied to the prediction. As a result, the story centers on Srinivas’s comments rather than any response, confirmation, or rebuttal from Meta or Perplexity.

The statement also fits a broader market pattern in which AI valuations sometimes swing based on perceived scarcity. When investors believe a particular component has limited availability or unusually strong pricing leverage, companies providing that component can attract capital even if end-user platforms appear to be the most obvious beneficiaries of AI adoption.

Still, it is important to underline what is not established by the reporting. The Yahoo Finance piece attributes a forward-looking view to Perplexity’s CEO, but it does not, in the materials provided here, lay out a detailed causal chain, forecasts, or specific assumptions about Micron’s capacity, margins, or timelines. It also does not provide comparative valuation metrics explaining how the market would translate the bottleneck idea into a near-term market-cap crossing.

For Meta, the company’s most consequential variable remains the pace and cost of AI infrastructure, including the ability to secure compute and memory resources as demand rises. Even if investors shift attention to semiconductors, Meta’s position as a major consumer of AI capacity could cut both ways, depending on whether hardware becomes cheaper due to supply growth or more expensive due to persistent scarcity.

What to watch next is whether Micron and peers in memory and AI-related compute components see business developments that reinforce the bottleneck thesis, such as evidence of sustained demand tightness or pricing power. Separately, investors may look for clearer indicates from large AI platform operators, including whether they highlight infrastructure constraints or procurement outcomes in their own disclosures.