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Octoth0rpetoday at 6:47 PM8 repliesview on HN

> Krishna also referenced the depreciation of the AI chips inside data centers as another factor: "You've got to use it all in five years because at that point, you've got to throw it away and refill it," he said

This doesn't seem correct to me, or at least is built on several shaky assumptions. One would have to 'refill' your hardware if:

- AI accelerator cards all start dying around the 5 year mark, which is possible given the heat density/cooling needs, but doesn't seem all that likely.

- Technology advances such that only the absolute newest cards can be used to run _any_ model profitably, which only seems likely if we see some pretty radical advances in efficiency. Otherwise, it seems like assuming your hardware is stable after 5 years of burn in, you could continue to run older models on that hardware at only the cost of the floorspace/power. Maybe you need new cards for new models for some reason (maybe a new fp format that only new cards support? some magic amount of ram? etc), but it seems like there may be room for revenue via older/less capable models at a discounted rate.


Replies

abraaetoday at 6:53 PM

It's just the same dynamic as old servers. They still work fine but power costs make them uneconomical compared to latest tech.

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rzerowantoday at 7:38 PM

I think its illustrative to consider the previous computation cycle ala Cryptomining. Which passed through a similar lifecycle with energy and GPU accelerators.

The need for cheap wattage forced the operations to arbitrage the where location for the cheapest/reliable existing supply - there rarely was new buildout as the cost was to be reimbursed by the coins the miningpool recovered.

For the chip situation caused the same apprecaition in GPU cards with periodic offloading of cards to the secondary market (after wear and tear) as newer/faster/more efficient cards came out until custom ASICs took over the heavy lifting, causing the GPU card market to pivot.

Similarly in the short to moedium term the uptick of custo ASICs like with Google TPU will definately make a dent in bot cpex/opex and potentially also lead to a market with used GPUs as ASICs dominate.

So for GPUs i can certainly see the 5 year horizon making a impact in investment decisions as ASICs proliferate.

austin-cheneytoday at 6:59 PM

It’s not about assumptions on the hardware. It’s about the current demands for computation and expected growth of business needs. Since we have a couple years to measure against it should be extremely straightforward to predict. As such I have no reason to doubt the stated projections.

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rlupitoday at 8:32 PM

Do not forget that we're talking about supercomputers. Their interconnect makes machines not easily fungible, so even a low reduction in availability can have dramatic effects.

Also, after the end of the product life, replacement parts may no longer be available.

You need to get pretty creative with repair & refurbishment processes to counter these risks.

lithostoday at 8:18 PM

It's worse than that in reality, AI chips are on a two year cadence for backwards compatibility (NVIDIA can basically guarantee it, and you probably won't be able to pay real AI devs enough to stick around to make hardware work arounds). So their accounting is optimistic.

mcculleytoday at 6:50 PM

But if your competitor is running newer chips that consume less power per operation, aren't you forced to upgrade as well and dispose of the old hardware?

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coliveiratoday at 7:42 PM

There is the opportunity cost of using a whole datacenter to house ancient chips, even if they're still running. You're thinking like a personal use chip which you can run as long as it is non-defective. But for datacenters it doesn't make sense to use the same chips for more than a few years and I think 5 years is already stretching their real shelf life.

dmoytoday at 6:56 PM

5 years is maybe referring to the accounting schedule for depreciation on computer hardware, not the actual useful lifetime of the hardware.

It's a little weird to phrase it like that though because you're right it doesn't mean you have to throw it out. Idk if this is some reflection of how IBM handles finance stuff or what. Certainly not all companies throw out hardware the minute they can't claim depreciation on it. But I don't know the numbers.

Anyways, 5 years is an infection point on numbers. Before 5 years you get depreciation to offset some cost of running. After 5 years, you do not, so the math does change.

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