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AI data centers are being already used at max capacity, aren't they? I have a hard time imagining people would suddenly use AI less than they do as of today, let alone collectively drop it altogether. So the worst case scenario is that they'd need to be auctioned off way under what they'd be worth now, but still for someone to use them for AI.

Inference is much cheaper than training a new model, so running them just for inference is a completely different thing than having to price in the fact that at the moment all of these companies need to compromise between compute for inference and compute for training new models. If no new models were to be trained, and all the compute was inference only, that would change everything when it comes to the overall compute cost of AI.

Dotcom infra buildup is a bad comparison, in that it wasn't even close to being all utilized. The infra was completely overproportional to the day to day usage.

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AI data centers that exist and are operational are running at maximum capacity. That's why you see things like the tiny little data center run by xai showing up as a valuable resource to xai (on the sale side) and anthropic (buy side). It is "only" 300 megawatts and there's a 1.25 billion rent on it per month.

If all these other data centers were anywhere near coming on line, that 300mw data center would be a rounding error not a line item as it is right now.

So someone's signed contracts for way more and way larger data centers, someone's purchased billions in hardware for these not yet operational data centers. I'm wondering how depreciation's going to work on all these assets...

Anyhow, I'm not really sure what "max capacity" is here, nor am I really aware when they're going to be delivering the operational assets that are currently levered to their eyeballs and consuming 1/3rd of the memory made on the planet.

As far as inference vs training, have new gotten radically better than old models or only marginally (at the cost of 10x or more the training costs)?

Very exciting stuff.

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I imagine the trend for AI usage will go up over the very long term (5-10yrs etc.), but short term how much usage is being propped up by employer's forcing their employees to use it? Or by user's being curious about the novelty but ultimately abandoning it if it doesn't do what they want? It'll be interesting to see what changes as tokenmaxxing disappears.
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I would day that the dotcom was directionally correct but the timing was wrong. For instance you had pets.com in 1999 but in 2020 you had chewy.com. It's like you had broadcast.com in 2000 but by 2020 you had YouTube that was making more in ad revenue than the next 4 largest competitors.

With investing timing matters a lot.

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You sell the GPU's to remote gaming companies.

Replace servers with regular compute.

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I imagine that the big incentive for remote gaming would be massive price increases in gaming hardware driven by the AI industry...

If the AI industry collapses, it would seem like the price of DDR etc. would dramatically decrease and lower demand for remote gaming

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AI GPUs have terrible graphical capabilities, if at all. They can run shaders, but they are lacking in texture units, rasterization, etc... huge bottleneck here.

These AI "GPUs" are worse for gaming than even the crappiest actual GPUs (with a G as in Graphics). Also, the display drivers won't support them, not officially at least.

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The G in AI GPU stands for "grift"
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Nvidia would have to ship game ready drivers for H100s but it could work.
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They don't have display-out. You'd have to send back the screen data over pcie to the motherboard for display.
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Not exactly a problem for cloud gaming.
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Has there ever been a market for cloud gaming apart from middle class people with macbooks who casually want to play one particular game but not enough to pay for a whole PC or console?
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I have a big beefy gaming PC. I still use cloud gaming from time to time. It means I don't need to juggle so many 100GB installs on my gaming handheld or cheap personal laptop, both of which can sometimes struggle to play actually demanding games. Battery life on those mobile computers are significantly better when cloud streaming a game instead of running computationally demanding games locally. It also makes the friction around trying out a game significantly lower, all I need to do is click play and the game is running instead of having to wait for it to download, play it a bit, decide I don't really like the game, and then uninstall it.

The feature being bundled in with GamePass makes it worth it. I used to VPN home and try and run games remotely, but it was honestly a bit of a pain. Just pressing a button and having the game launch is quite nice.

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Not gonna run game on fucking tensor cores alone
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Just do software rasterization and ray tracing and play Cyberpunk 2077 on medium at 720p/30fps, what's the problem?
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> Those data centers are specifically for AI workloads. Let’s say everything crashes and we now have all the data centers, what do you do with them?

You just run the models and sell the tokens. The demand will still be there even if there will be less money in chasing new frontier model

> GPU are pretty specialized hardware, without AI a data center full of outdated graphics cards isn’t really too valuable.

AI accelerators used in DC are not really "graphic cards" any more, you ain't running gaming on it

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> AI accelerators used in DC are not really "graphic cards" any more, you ain't running gaming on it

I think the lighter 40 series cards like L40 still have OK graphics features. But otherwise yeah, after the Ampere generation graphics features went down the drain. The A100 and A40 cards can do graphics well but it already makes no sense in terms of power-to-performance ratio.

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You still have to pay for power and water. Those are not insignificant costs.
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