@FinanceYF5: Chamath said he asked the CTO about the company's AI token spending today and got a shocking answer: token costs double every 45 days, but downstream productivity improves by at most 5%. His exact words were that costs double, benefits stay roughly flat, and the team found that to iterate to the next generation of capabilities, the amount of tokens required grows exponentially, because...

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Chamath revealed that his company found AI token costs double every 45 days while downstream productivity improves by at most 5%. He believes AI development is approaching a bottleneck and suggests companies reconsider their strategies or even consider exiting.

Chamath said he asked the CTO about the company's AI token spending today and got a shocking answer: token costs double every 45 days, but downstream productivity improves by at most 5%. His exact words were that costs double, benefits stay roughly flat, and the team found that to iterate to the next generation of capabilities, the amount of tokens required grows exponentially, because they are approaching some kind of bottleneck. He said they will pause and rethink what to do next, and that in the next three to four years, almost all companies will likely go through this round of reckoning. He even suggested: if you can exit now, do it now, before this issue penetrates the entire market, while valuations and fundraising are still high.
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Chamath said he asked the CTO today about the company’s AI token spending, and got a ridiculous answer: token costs double every 45 days, while downstream productivity gains are at most 5%.

His exact words were: costs double, but benefits remain essentially flat. The team found that to iterate to the next generation of capabilities, the amount of tokens required is growing exponentially, because they are approaching some kind of bottleneck.

He said the next step is to pause and rethink what to do. In the next three to four years, most companies will likely go through this round of reckoning.

He even suggested: exit now if you can—before this issue permeates the entire market, while valuations and fundraising can still be done at high levels.

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@0xCheshire: Chamath just revealed a deeply unsettling truth for the AI industry. He asked his own CTO to review the company's spending, and the result was staggering: "Our token costs are doubling every 45 days," yet the downstream productivity gains are at most about 5%. Costs are skyrocketing exponentially, while returns remain basically flat...

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Chamath reveals the harsh reality of AI costs vs. returns: token costs double every 45 days, but downstream productivity gains are at most 5%. Large model capability improvement has hit an asymptote, and within the next 3-4 years, every company will face an ultimate reckoning between cost and benefit.

@DashHuang: Imagine AI as digital employees. It's normal for the salary of subordinates managed by one person to be at a 1:1 ratio, or even 1:10, with their own salary. Therefore, it is foreseeable that the cost of AI tokens will match or exceed employee salaries in the future. Of course, the measurement of ROI will be the same as for team size and salary costs.…

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Compares AI token consumption to digital employee salaries, predicts token costs will match or exceed employee wages, and discusses how businesses measure ROI and control costs.

[Mike Pound] Why AI Tokens are so Expensive - Computerphile

Reddit r/singularity

This article explains why AI tokens are expensive: the autoregressive generation process requires predicting token by token and repeatedly computing the entire context, causing computational cost to grow linearly with context length; coding agents, due to multi-turn interactions and file reads, quickly accumulate very long contexts, further increasing token costs.