วิกฤตความคุ้มค่าของ AI

A year ago in The Back Of The AI Envelope I pointed out that the AI platforms were running the drug-dealer's algorithm, "the first one's free". By massively subsidizing the use of their products, they were generating overwhelming demand for them. They used this demand to justify massive investments, in the hope that, by the time they had to show a return on these invetment, the users would be so addicted that they would pay the vastly higher prices needed to generate a return.

I have to confess that I was late to the party. The earliest skepticism I've been able to find was from Sequoia Capital's David Cahn in September 2023, entitled AI’s $200B Question. Only nine months later Cahn re-ran the same analysis in AI’s $600B Question. His estimate of the revenue gap had tripled. Cahn wasn't alone. Independent journalists such as Ed Zitron were flagging this problem long before I was.

I started to write this post a couple of months ago when the maiinstream business press began to notice companies complaining about the cost of the tokens their employees were burning. Since then the trickle has turned into a flood, which made finishing the post hard. Below the fold I throw up my hands and dump out a small sample from the flood.

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