Waste heat from power plants isn’t always useful because it is low grade heat… but it is still much, much, much better than the 35-60C water you could get from a data center.
Do the math on pumping 40C water any distance in a loop. It is hard to make it worth it. The water cools off and the pumping takes significant energy, plus the pump and all the piping cost something.
Then using a heat pump on it makes it even worse.
Low grade heat source is not a term I made up- it refers to heat sources under 100C.
Even much hotter low grade heat usually goes unused. You usually need a perfect confluence of a warmer source, very close need for building heat, and a willingness to pay more for environmental friendliness for it all to work out.
Here's an article on the subject of using waste heat from data centres and other sources for district heating. It includes the math you told me to do as well as references to other articles on the specific subject of using "low-grade heat sources" in combination with heat pumps to feed district heating networks.
And, again, the economics. The hypothetical Polish project cited in the paper showed a breakeven in 6.1 years... if one ignores time value of money and assumes it is delivered for the estimated cost. The annuity formula tells me that at a reasonable 10% discount rate, payback would be in 10 years. Modest overruns in cost from this naive estimation push that to never.
And again this is a pretty idealized case-- very nearby housing, optimistic estimated costs.
Other projects analyzed in your paper had "raw" paybacks of 15 years and 17 years-- AKA never in actuality.
When we are talking about protecting the environment, efficiency and return on capital is important. You'd be better dumping those projects into generating more green energy instead of trying to reclaim the DC energy. This is why:
> > Even much hotter low grade heat usually goes unused. You usually need a perfect confluence of a warmer source, very close need for building heat, and a willingness to pay more for environmental friendliness for it all to work out.
Outgrowing GDP for awhile— especially from a smaller base— is certainly possible. It is much less likely to do it from a long time from already large revenue.
If you looked at Google, Amazon, Apple, Microsoft valuation around 2007 (before the crash), you'd asked the same question about the large base. But here we are.
I am upset that I am forced to either rebalance out of NASDAQ and incur significant tax consequences, or bet that SpaceX is about to become nearly 10 percent of GDP and keep exceptional margins while doing it.
I would not voluntarily take that bet, but we have regulatory and financial engineering nearly forcing me to do so.
I am upset that I am forced to either rebalance out of NASDAQ and incur significant tax consequences
Just to quantify, "The projected SpaceX weighting is around 0.6% of QQQ."
So if you have $100,000 invested in QQQ and SpaceX winds up say 4x overvalued, it may eventually wind up costing you as much as $450 (i.e. 1/5th as large a loss you experienced today in QQQ).
You are arguing I should be fine losing $500 so Elon can cash out? Because - and I hope this doesn't seem uncharitable - some sci-fi fantasy about space colonies?
You could maintain a short SpaceX portion in the approximately same percentage as your NASDAQ ETF. You'd have more slight tax events as you increased or closed out that short position to maintain the percentage, but significantly less than your NASDAQ position's taxes. Then when you sell your ETF you could close out the short to effectively remove SpaceX from the equation.
I am upset that it is not a great bet and that retail investors and pensions are being forced to take it. Let’s not pretend that this is not regulatory capture and financial engineering by techbros.
I'm upset that we allow people like you to avoid paying their fair share of taxes, possibly indefinitely, so anything that makes that harder even "accidentally" is ok by me.
I would rather capital gains be taxed at income rates but indexed to inflation. I am fine with that being a fair bit more.
But ripping off pension funds so you can tax me more, as a side effect of enriching people that engage in these shennanigans, doesn’t seem like a great move.
Depends upon the intelligence vs compute scaling law— which I think no one really knows. Pretty likely to be some degree of diminishing returns, but how much? Is it logarithmic, inverse quadratic, …
If training models gets way cheaper, I would expect the diminishing returns to get steeper too.
And you're right, no one has any clue what the limits of intelligence are. Though to me it seems odd that humanity has reached the pinnacle of it in the last million years or so after a few billion years of lifes development. Just seems improbable we are close to the limits.
I am not making an argument about limits. I just expect some degree of diminishing returns.
A related argument is speed of intelligence vs capability at that speed. You can think of a three way trade off between latency, cost, and capability that is unlikely to be linear in any dimension and that changes in steps as technology or biology evolves.
Ultimately relating to the properties of the computing substrate and almost certainly bounded by some kind of thermodynamic limits that present systems do not approach.
>Pretty likely to be some degree of diminishing returns
intelligence may be different. If we look at biological brains - do we get diminishing returns or completely opposite scaling law when we compare our brain against say gorilla's ?
Interesting thought to consider in principle but fails because gorilla brains continued to evolve too, just along a different path. They're not snapshots of ancestral species locked in time.
Will it continue to appreciate to infinity? Maintain its value forever? Or will something else happen?
The same argument you’ve made would work for tulip bulbs, dotcom prices, or whatever. Prices go up until they don’t. Exponentials don’t last forever and the intrinsics of technology assets depreciate: things wear out and are also replaced with better things.
> 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.
"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.
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.
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.
Sure, according to an unnamed "GenAI principal at Alphabet" of whom "We could not verify the name of the person who describes themselves as 'GenAI principal architect at Alphabet' and therefore we cannot 100% trust their claims."
But let's run with Deep Layer(tm)'s hot take from 2024, GPUs all die in 2 years, no exceptions*. Poor guy just spent $400,000 on a DGX with 8 B200s, each of those B200s generates a piddly ~$3,000 in profit monthly spewing tokens, netting $576K in 2 years, that's a pathetic 20% annual return. Oh no... Won't someone call Michael Burry!
*Never mind the 3-year warranty or any extended service contract, that GPU is D E D and you're S O L.
You gotta include 50k+ in power plus other expenses. Still looks like an ok return on capital, but you are betting heavily that cost of computing doesn’t fall much.
If token prices fall a bunch then it may not even be worth leaving on, depending on your facility’s relative power, cooling costs.
If we push far into oversupply eventually a bunch of firms building this infrastructure are going to lose out.
What? They make money from their own inference and models too, which they can train effectively for free by funding their operations with rental income from their last gen datacenter.
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