The Great AI Silicon Shortage

Treść źródłowa

The Compute ShortageToken demand is skyrocketing and the need for AI compute continues to accelerate. The improvement in model capabilities combined with the rapid emergence of agentic workflows has driven a surge in user adoption and aggregate token demand. Anthropic added a staggering $6B of ARR in the single month of February alone driven by broad adoption of agentic coding platform Claude Code, and if Anthropic had more compute they would have added more. Despite a huge AI infrastructure buildout over the past few years, available compute is scarce. On-demand GPU prices continue to go up even for Hoppers which are almost 2 generations old.From our own experiences, we have reached out to every neocloud we know asking if they have small clusters available, but everything is already firmly locked up. This tight supply environment explains the sharp reset in hyperscaler capex plans. Consensus estimates have moved materially higher across the board, with Google standing out as the most extreme example, where 2026 capex expectations have roughly doubled versus prior expectations, primarily driven by datacenter and server spend.Source: Company Earnings, BloombergThis is a tremendous level of spending, and hyperscalers would deploy even more capital if they could, but they are constrained by one critical factor: silicon supply. There is simply not enough advanced logic and memory fabrication capacity to support the pace of compute deployments. While the AD (After Da launch of ChatGPT) era has been riddled with various constraints such as CoWoS packaging and datacenter power, we…