Well, he dismisses any value whatsoever to GenAI. That's immediate bozo bit criteria to me. And, well, if Anthropic revenue doesn't grow 5x between now and the end of the decade, I'll be pretty surprised. But, sure, if it doesn't, then someone will keep them around anyway. AMD almost died in the 2010s as one example, but they kept getting propped up and now they're back in the game swinging. There are people who can see alpha beyond the next 10Q. Ed Zitron isn't that sort.

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mlyle 3 hours ago | parent | next [-]

> Well, he dismisses any value whatsoever to GenAI.

I didn’t read it that way. I see a lot of value in it.

I just don’t see us justifying the amount of infrastructure being built or current valuations. Or in the unlikely event that we do, the societal upheaval is going to take away the ability to monetize it meaningfully.

OpenAI and Anthropic may make it through. But that is different from saying valuations are justified or that all this infrastructure will pay off.

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LogicFailsMe 3 hours ago | parent [-]

"Those excited about generative AI are either the victim or the perpetrator of a con centered around a technology to ingratiate at the highest cost possible."

How else would you read the above statement? He's just preaching to his own choir IMO.

My take: like any gold rush, a lot of dumb ideas will get backed and they will all fail. And then we'll keep the ones that worked. SSND. Good luck picking the winners a priori.

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mlyle 2 hours ago | parent [-]

I read it in context as being about the market prospects of genai.

The problem is, when there is so much overinvestment, everything gets wrecked. In the aftermath of the dotcom boom there was at least a bedrock of fiber and still useful equipment to build upon amid the rubble. This time we are going so much further; also many of the durable assets are misplaced bets and the depreciating ones will depreciate more steeply.

	▲	LogicFailsMe 2 hours ago \| parent [-]
		Someone should do the analysis of a decade and a half of Nvidia datacenter GPUs from Fermi to Kepler to Maxwell to Pascal to Volta to (Turing) to Ampere to Hopper to Blackwell and generate some hard depreciation numbers. Fiddling around a bit, 16-20% annual depreciation (so 5-6 years total and then any further revenue is bonus goods) it would appear, but that's a fiddle number. But confounding this, K80s and V100s are still offered by cloud providers 13 and 9 years after their releases and academia still loves their GTX 1080 Pascals in their desktops. At companies, the beancounters take a computation and find the best architecture !/$ for that calculation. It does not need to be brand new shiny. It's Nvidia's job to make that case, not them. But anyway, the real data is right there. And those old GPUs demonstrate the dark fiber is already in place (and it's not so dark or they'd pull their racks). AI is the special case. New GPU generations are the only way to access HW implementations of last year's research on precision modes and matrix math. If that slows down, that would be the first real bellwether of a slowdown. It hasn't happened yet. I'm a little surprised myself, but I also think coding agents are the vanguard of general design agents and that's going to hit a lot of industries at once. So as long as the next generation of GPU halves the price of tokens and doubles throughput (or better), the demand for tokens will continue to rise IMO. What I don't think is that AI can come for anyone's job successfully no matter what the C-suite sorts insist. In summary, if you're a bear, you can point to the depreciation cycle and scream the sky is falling. And if you're a bull you can point to GPUs staying in production for a very long time despite the depreciation. Guess we have to wait for 2030.

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vatsachak 2 hours ago | parent | prev [-]

Alright, let me explain what's happening this Q

Chinese providers realized that LLMs have peaked and have started trying to reduce the price per token. Deepseek pro v4 can easily add tests to my complicated code and costs cents for a million tokens.

I can ask Claude or ChatGPT architecture questions and then use Deepseek for the rest.

How are these businesses going to pay to price of energy and GPU depreciation again?