This Andy Kessler piece might be right or wrong but it's a worthwhile read. As he puts it: "I can tell you how the artificial- intelligence datacenter boom will probably end, but I can’t tell you when. Implementing large language models has been a brute-force approach: Big, fast and expensive GPUs from Nvidia crunch a trillion parameters using massive amounts of memory housed in liquid cooled, gigawatt-gobbling data centers, all with brute-force pricing. It sure smells like IBM mainframes of old. Be careful about extrapolating anything from today’s pricing. With AI, like all new technologies, the refinement stage is kicking in—just as mainframes gave way to cheaper minicomputers, microprocessors, web servers and now AI architectures. AI token prices have been dropping but are set to plunge faster than most anticipate. Tech growth is never a straight line. Silicon Valley’s mantra for decades has been smaller, cheaper, faster, better. I asked venture capitalist Steve Jurvetson to translate that into numbers. “We often see a technology shift when the new approach is 10 times better. It can be 10 times more performant or 10 times cheaper, sometimes both.” He calls it the “factor of 10.” And it’s happening. Last week, according to Open-Router, OpenAI and Anthropic were charging a premium for some of their models—$1 to $2 per million input tokens. Comparable Chinese open weight models like Z.ai’s GLM and Alibaba’s Qwen charged 6 to 12 cents, around 90% less—that factor of 10 inflection point. American AI labs have gone from 70% market share last year to 30% today. All are still growing. But prices matter."
[EOP]
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