Discussion · CoreSignal social

Every time I start to think I'm wrong about "AI", @edzitron reinforces my sense of reality;

"Hyperscalers will have sunk over $1.3 trillion dollars into generative AI by the end of 2026, and have plans to spend a trillion dollars more next year. On a very rational level, nothing that LLMs have done, do or will do in the future can or will ever bring in the more than $2 trillion (or more) in brand new revenue that will be required to make any of this worth it."

https://www.wheresyoured.at/the-more-you-buy-the-more-you-lose/

#AI

"To give you a sense of how memory hungry AI is, a single 72-GPU GB300 NVL72 AI server has over 20 terabytes of high-bandwidth memory (used almost exclusively in GPUs and other AI chips), and 17 terabytes of the LPDDR5X RAM used in mobile devices, and a gigawatt data center has thousands of those NVL72 servers (or something similar)."

#EdZitron, 2026

https://www.wheresyoured.at/the-more-you-buy-the-more-you-lose/

(1/2)

#AI

"Moreover, that high-bandwidth memory that AI GPUs use requires more wafer space during manufacturing — further reducing the amount of manufacturing capacity for other kinds of memory."

#EdZitron, 2026

https://www.wheresyoured.at/the-more-you-buy-the-more-you-lose/

(2/2)

"However 'useful' AI coding tools may be — and it’s genuinely hard to tell! — is immaterial to the larger point that they’re very, very, very expensive to use, that most of those costs are either hidden from the user or subsidized by employers, and that despite all the fucking noise, they are yet to substantively replace or even enhance human beings outside of the loudest and most annoying people on Twitter. "

#EdZitron, 2026

https://www.wheresyoured.at/the-more-you-buy-the-more-you-lose/

#VibeCoding #CodeAutoGeneration

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