7 ms·

(edited to remove snark) Your comment seems to miss the point that the article does not (necessarily) have a problem with Zitron being insufferable/annoying/smu

(edited to remove snark) Your comment seems to miss the point that the article does not (necessarily) have a problem with Zitron being insufferable/annoying/smug. It's that his predictions are verifiably wrong. It's one thing to be annoying and right. Zitron is annoying, but not right.

torginus 15d ago
Are they? These companies have been caught tweaking their numbers. One example, not sure if cited by Zitron, or others, is that they build data centers through holding companies, who have to absorb the costs and massive capex based financial liabilites, so that the brand-name big-tech companies get to keep their expenses off their books. There have been trillions of debt discovered this way. Another issue is the apparently relentless progress of the hardware industry, needed to justify their super-high P/E ratios, measured against the fact, that to lessen the effect of HW amortization, hyperscalers opted to lengthen the depreciation timelines of their GPUs. So there is an apparent contradiction that new hardware needs to be both substantially better, and substantially the same, to make both stories true. I'm not a finance guy, and a lot of it is over my head, but even finance people keep asking the 'who's gonna pay for this' question. We're way past the belief that this is going to produce reasonable returns (as in a value for money kind of way), and hoping we can financially engineer ourselves out of this situation without having to feel the pain.
- nl 15d ago
  > These companies have been caught tweaking their numbers... they build data centers through holding companies, who have to absorb the costs and massive capex based financial liabilites, so that the brand-name big-tech companies get to keep their expenses off their books. This is about as far from "tweaking their numbers" as you can get. It's a standard way infrastructure-heavy industries structure their investments and people would be asking questions if they didn't do this! > hyperscalers opted to lengthen the depreciation timelines of their GPUs. Yes and so they should! GPU depreciation timelines used to be 3 years!! Google is famously still running 10 year old TPUs at 100% utilization, and 10 year old H100s are worth more now on the second hand market than they were when they were bought. H100 spot prices have only dropped from $5 in May 24 to $3.20 now despite the release of the B200: https://semianalysis.com/gpu-pricing-index/ https://semianalysis.com/gpu-pricing-index/
  - jsnell 15d ago
    There are no ten year old H100s. The first production shipments happened exactly four years ago. I'm pretty sure your claim about TPUs is similarly exaggerated, only a v1 (barely) qualifies and would have no utility today.
    - nl 15d ago
      You are absolutely right, I apologize. I think I was talking about A100 prices (which are still only 6 years old) and conflated a few different things there. But A100 rental prices have climbed since 2024 (as far back as free account records show on https://semianalysis.com/gpu-pricing-index/ https://semianalysis.com/gpu-pricing-index/). Coreweave has announced they will keep A100s in use until 2029 which will be 9 years old then. I think that is where I got the 10yo number I had in my head. On TPUs, I was also wrong on that, but less so. The quote is: "seven and eight-year-old TPUs have 100 percent utilization."[1] That was last year, so 8 or 9 year old TPUs now (assuming it is still true). Slight exaggeration there and I wish I'd looked it up before posting. Despite this, my point (that 3 year depreciation schedules for GPUs was too short) remains correct I think. [1] https://www.datacenterdynamics.com/en/news/google-says-tpu-demand-is-outstripping-supply-claims-8yr-old-hardware-iterations-have-100-utilization/ https://www.datacenterdynamics.com/en/news/google-says-tpu-d...
  - torginus 15d ago
    > This is about as far from "tweaking their numbers" as you can get. It's a standard way infrastructure-heavy industries structure their investments and people would be asking questions if they didn't do this! Well, it's enough to throw off standard EBITDA accounting and allow firms to report fictional earnings numbers. A standard story has been that companies have beat their Q3 estimates, only for their stocks to go down.
comfysocks 15d ago
To be fair to Ed, I’d describe his usual argument (at least currently) as saying that Meta, MS, google are “mature” companies trying to be maintain the high valuations and growth of a young company, which they no longer are. If you take this to be his argument, then dan’s numbers are more consistent ed’s claim.
- ngcazz 15d ago
  more consistent with? more consistent than?
  - comfysocks 15d ago
    Yes, “consistent with”. Thanks.
- Danox 15d ago
  Of the three Google is in the best position. Meta and MS are in trouble. Zuckerberg will survive because he has control of his company, but Nadella is not going to survive Copilot if it don’t work.
maxglute 15d ago
Yes? What happened to FAANG in last 3 years, they cut a fuck load of jobs, the raised rent/prices, then inflation, then experience surge in new category AI. 1 + 2, i.e. squeezing rock has limits. 3 is fundamentally not sustainable, i.e. AI revenue gap order of magnitude relative to spend. This like debt crisis, there's lot of levers to burn to maximize extraction and make ledger look good short term, but is fundamentally not long term sustainable. Articles arguing over minutiae / short term accuracy pointless, market can stay irrational than one can stay liquid blah, blah - I mean its useful for investing - but when talking about long term predictions he's just stating the obvious, the financials don't make sense within the business cycle current players are operating in. Like one can believe AI is speciation event technology eventually, but still given actual constraints, i.e. literally not enough investors for $$$, not enough hardware, not enough infra over xyz time horizon that these companies carrying stupendous debt and mathematically guaranteed stranded / deprecated compute infra is only digging themselves deeper vs future competitors. Sure AI can eventually capture 30% of GDP and knowledge worker's life time achievement is worth a few $100 of compute or a few pennies in thinking sand. But ultimate winners is probably going to be some future startup that pays pennies for thinking sand not incumbent who paid magnitude more and simply can't operate profitably due to balance sheet.
- torginus 15d ago
  Hasn't AI been horrible for FAANG fundamentally? - They've all been compelled to build the same horribly expensive AI infra, to serve similar models that have no ability to lock-in customers - Google Search has to compete with LLMs - Meta hasn't demonstrated a credible argument on how they're planning to use AI. AI 'friends' would kill their business model. Their saving grace ironically is that people absolutely hate interacting with AIs. Same goes for other AI assistants. - Hyperscalers have to compete for the same hardware as AI companies, driving their costs up - AI turned out to be excellent at both porting software to more optimized stacks and deleting the 'prestige' of building these ultra-inefficient microservice containerized stuff. I haven't read a single article about somebody bragging about this stuff. When it comes to tech (which is not AI), usually its about Zig, Rust and going native. - So if customers really start feeling the heat of rising costs, they have a realistic path of optimizing their compute usage by using AI to rewrite the worst-offending components. I think one of the few things in which AI has demonstrated measurable economic value is rewriting software in Rust to be more efficient

torginus 15d ago

Are they? These companies have been caught tweaking their numbers. One example, not sure if cited by Zitron, or others, is that they build data centers through holding companies, who have to absorb the costs and massive capex based financial liabilites, so that the brand-name big-tech companies get to keep their expenses off their books. There have been trillions of debt discovered this way. Another issue is the apparently relentless progress of the hardware industry, needed to justify their super-high P/E ratios, measured against the fact, that to lessen the effect of HW amortization, hyperscalers opted to lengthen the depreciation timelines of their GPUs. So there is an apparent contradiction that new hardware needs to be both substantially better, and substantially the same, to make both stories true. I'm not a finance guy, and a lot of it is over my head, but even finance people keep asking the 'who's gonna pay for this' question. We're way past the belief that this is going to produce reasonable returns (as in a value for money kind of way), and hoping we can financially engineer ourselves out of this situation without having to feel the pain.

nl 15d ago
> These companies have been caught tweaking their numbers... they build data centers through holding companies, who have to absorb the costs and massive capex based financial liabilites, so that the brand-name big-tech companies get to keep their expenses off their books. This is about as far from "tweaking their numbers" as you can get. It's a standard way infrastructure-heavy industries structure their investments and people would be asking questions if they didn't do this! > hyperscalers opted to lengthen the depreciation timelines of their GPUs. Yes and so they should! GPU depreciation timelines used to be 3 years!! Google is famously still running 10 year old TPUs at 100% utilization, and 10 year old H100s are worth more now on the second hand market than they were when they were bought. H100 spot prices have only dropped from $5 in May 24 to $3.20 now despite the release of the B200: https://semianalysis.com/gpu-pricing-index/ https://semianalysis.com/gpu-pricing-index/
- jsnell 15d ago
  There are no ten year old H100s. The first production shipments happened exactly four years ago. I'm pretty sure your claim about TPUs is similarly exaggerated, only a v1 (barely) qualifies and would have no utility today.
  - nl 15d ago
    You are absolutely right, I apologize. I think I was talking about A100 prices (which are still only 6 years old) and conflated a few different things there. But A100 rental prices have climbed since 2024 (as far back as free account records show on https://semianalysis.com/gpu-pricing-index/ https://semianalysis.com/gpu-pricing-index/). Coreweave has announced they will keep A100s in use until 2029 which will be 9 years old then. I think that is where I got the 10yo number I had in my head. On TPUs, I was also wrong on that, but less so. The quote is: "seven and eight-year-old TPUs have 100 percent utilization."[1] That was last year, so 8 or 9 year old TPUs now (assuming it is still true). Slight exaggeration there and I wish I'd looked it up before posting. Despite this, my point (that 3 year depreciation schedules for GPUs was too short) remains correct I think. [1] https://www.datacenterdynamics.com/en/news/google-says-tpu-demand-is-outstripping-supply-claims-8yr-old-hardware-iterations-have-100-utilization/ https://www.datacenterdynamics.com/en/news/google-says-tpu-d...
- torginus 15d ago
  > This is about as far from "tweaking their numbers" as you can get. It's a standard way infrastructure-heavy industries structure their investments and people would be asking questions if they didn't do this! Well, it's enough to throw off standard EBITDA accounting and allow firms to report fictional earnings numbers. A standard story has been that companies have beat their Q3 estimates, only for their stocks to go down.

comfysocks 15d ago

To be fair to Ed, I’d describe his usual argument (at least currently) as saying that Meta, MS, google are “mature” companies trying to be maintain the high valuations and growth of a young company, which they no longer are. If you take this to be his argument, then dan’s numbers are more consistent ed’s claim.

ngcazz 15d ago
more consistent with? more consistent than?
- comfysocks 15d ago
  Yes, “consistent with”. Thanks.
Danox 15d ago
Of the three Google is in the best position. Meta and MS are in trouble. Zuckerberg will survive because he has control of his company, but Nadella is not going to survive Copilot if it don’t work.

maxglute 15d ago

Yes? What happened to FAANG in last 3 years, they cut a fuck load of jobs, the raised rent/prices, then inflation, then experience surge in new category AI. 1 + 2, i.e. squeezing rock has limits. 3 is fundamentally not sustainable, i.e. AI revenue gap order of magnitude relative to spend. This like debt crisis, there's lot of levers to burn to maximize extraction and make ledger look good short term, but is fundamentally not long term sustainable. Articles arguing over minutiae / short term accuracy pointless, market can stay irrational than one can stay liquid blah, blah - I mean its useful for investing - but when talking about long term predictions he's just stating the obvious, the financials don't make sense within the business cycle current players are operating in. Like one can believe AI is speciation event technology eventually, but still given actual constraints, i.e. literally not enough investors for $$$, not enough hardware, not enough infra over xyz time horizon that these companies carrying stupendous debt and mathematically guaranteed stranded / deprecated compute infra is only digging themselves deeper vs future competitors. Sure AI can eventually capture 30% of GDP and knowledge worker's life time achievement is worth a few $100 of compute or a few pennies in thinking sand. But ultimate winners is probably going to be some future startup that pays pennies for thinking sand not incumbent who paid magnitude more and simply can't operate profitably due to balance sheet.

torginus 15d ago
Hasn't AI been horrible for FAANG fundamentally? - They've all been compelled to build the same horribly expensive AI infra, to serve similar models that have no ability to lock-in customers - Google Search has to compete with LLMs - Meta hasn't demonstrated a credible argument on how they're planning to use AI. AI 'friends' would kill their business model. Their saving grace ironically is that people absolutely hate interacting with AIs. Same goes for other AI assistants. - Hyperscalers have to compete for the same hardware as AI companies, driving their costs up - AI turned out to be excellent at both porting software to more optimized stacks and deleting the 'prestige' of building these ultra-inefficient microservice containerized stuff. I haven't read a single article about somebody bragging about this stuff. When it comes to tech (which is not AI), usually its about Zig, Rust and going native. - So if customers really start feeling the heat of rising costs, they have a realistic path of optimizing their compute usage by using AI to rewrite the worst-offending components. I think one of the few things in which AI has demonstrated measurable economic value is rewriting software in Rust to be more efficient