Comment by pcstl

>You're refuted.

No, the whole thesis is XYZ likely fail because REVENUE RECORDS is not enough to dig out of hole relative to MAGNITUDE MORE SPEND. Saying Zitron wrong because XYZ made $2 for every $10 it spends revenue needed to justify spending. Fixtaing on the $1-$2 is misdirection/innumeracy, the thesis is in reaching the $10 relative to time, i.e. that $2 has to be $10 in X time, but the current velocity suggest it will not be.

I agree with Zitron directionally on accounting, I in fact disagree with him on AI... I am extremely AI pilled, i.e. I think there is a future where AI is worth trillions and will capture large swatch of economy. The transformation will be extreme, unlike any past revolutions... but the accounting suggest that future isn't coming in time to rescue current AI incumbents from finance blackhole, which some may survive, i.e. bail outs, nationalization... but the $$$ suggest however we get there, there will likely be massive $$$ corrections involved irrespective of adoption.

On a spectrum between tulip wilting and fiber build out, we know deprecation cycle of DC hardware leans towards tulips i.e. <10 years (very generous) vs 20+ years for fiber layout, a lot of which is actually infra/earth works etc.

The numbers being cited is ~100B is well within accounting/ledger maxxxing tricks relative to current pool of investment. Luu is not analyzing number's he's just listing and believing numbers, and analytically entirely avoids the core Zitron thesis... once you tap out of easy investor $$$, FAANG warchest, accounting tricks... where is the rest of the order magnitude more $$$ that justifies existing spent relative to time frame coming from?

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.

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.

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.

But even those concessions have been a shift: at every point, he's been as bearish as possible on LLMs, often past credibility.

And if you take it as a given that AI will never be any better than ~~now~~ a year ago, and that anyone who disagrees is an idiot or a liar, then that pretty much demands that the entire AI economy must be as fraudulent as he imagines. Which, while it serves his purpose of serving up AI-skeptic invective slop well, doesn't actually model what's going on, which is speculative investments that have the potential to generate extraordinary returns.

There are plenty of people on the far right whose positions are rational provided that you agree with their views. Conversely, there are plenty of people on the far left whose positions remain irrational despite that you might agree with their views. It is a serious cognitive error both to fail to see the irrationality of those you agree with as well as to fail to see the rationality of those you disagree with.

Stupidity has always been terrifyingly powerful.

That's literally the meaning of the statement "the market can stay irrational longer than you can stay solvent".

Irrational means stupid.

Stupid can win for a very long time, and in the end the "loss" is born mostly by bag-holders.

Because it's not a single data point, intelligence is a wide surface area where you can be smart in some areas and stupid in others. Furthermore whether you are being intelligent is relative to ideals and goals, and not everyone has the same ones.

you're likely working under an assumption of meritocracy/overvaluing of kinds of intelligence

I read it as suggesting that AI models are simultaneously terrifyingly powerful and incompetent dunces.

It is weakness in the long-term.

It's pretty clear in how people talk about billionaires: They must somehow conclude that the people most successful within a system that rewards certain things are not competent because the things the system rewards are not what they think the system should reward (it is fine to believe the system rewards the wrong things, but people walk straight into denying that those people have skill even within the system, or they claim that skill within the bounds of the system does not reflect any "real" skill - totally ignoring that elites tend to stay elites even through, say, Communist uprisings).

Hence how someone can say that Musk is "dumb" with a straight face.

heh, no. Eco is referring to how the white house casts groups like academics, immigrants, socialists, and trans people.

Sometimes it really is sufficient to say "This person is a grifter and from that all else follows".

but the article cherry picks. the article ignores Zitron’s economic arguments about data center costs vs. future profite.