Latest Interviews
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Clear all filters- Dwarkesh Patel2h 31m
Dylan Patel — The single biggest bottleneck to scaling AI compute
The Big Four hyperscalers have forecasted a combined $600 billion in capital expenditure, yet only about 20 gigawatts of incremental compute capacity is expected to come online in the US this year due to long-lead infrastructure projects. While OpenAI aggressively secured long-term capacity, Anthropic now faces a critical 4-gigawatt gap that forces reliance on expensive spot markets, highlighting a broader industry struggle against semiconductor supply bottlenecks and memory bandwidth constraints. Ultimately, EUV tool production limits and labor shortages constrain global AI scaling, positioning US allies with advanced manufacturing capabilities to maintain a significant lead over China for the foreseeable future.
- Dwarkesh Patel2h 11m
@Asianometry & Dylan Patel — How the semiconductor industry actually works
Dylan Patel, Jon Y, Jane Street, Stripe, Xi, Liang Mong Song, China, Huawei, Taiwan, US, John Y
Semiconductor experts discuss the escalating geopolitical race where China's ability to rapidly build gigawatt-scale data centers and leverage domestic chip manufacturing could allow it to surpass Western AI capabilities by next year. The dialogue highlights critical bottlenecks in power infrastructure and supply chains, noting that while export controls have inadvertently spurred Chinese innovation in 7nm and 5nm processes, the US and its allies face significant grid limitations and capital requirements ranging from $50 billion to $100 billion to meet future cluster demands. Ultimately, the speakers analyze a market driven by a "Pascal's Wager" among tech CEOs who are betting massive capital on transformative models like GPT-5 to justify current debt-financed infrastructure despite looming risks such as a potential Taiwan crisis and delayed revenue generation.