Good questions. Note that it's hard to tell what's happening from a single reference, and any single reference could be wrong, which is why I look at multiple sources including those I linked above to piece together the bigger picture. Here's what I see.

For 1) the report cannot determine an exact split between VC-backed startup vs other revenue because the startups are private. What it focuses on is deduping the revenues, so the headline number of $110B - 175B annually is the outside money flowing into the system, and not circular flows.

However that outside money includes revenues, VC-backed cash, and training costs, which cannot be disentangled by this methodology. But note:

a) That does not imply circularity, as the apollo.com link suggests.

b) We also can't assume this is mostly from burning investor cash rather than actual going concerns. Large VCs like A16Z, YC and Menlo Ventures, without disclosing margins, report seeing dramatic revenue growth in their startups, e.g.

https://a16z.com/revenue-benchmarks-ai-apps/

https://www.cnbc.com/2025/03/15/y-combinator-startups-are-fa...

So while often VCs are also investors in the frontier labs, the flow of money here is explicitly not "hyperscalers -> startups -> frontier labs -> hyperscalers," but rather "VCs + revenue -> startups -> frontier labs -> hyperscalers." And VCs report that revenue is the fastest growing in history, which is corroborated by all the other links measure AI adoption growth.

Furthermore, this $110 - 175B number also gels with the $177B number that the a16z link estimates.

For 2) the slides are much better for this (and the caveats are important) but the simplest I can put it is, at this point the marginal cost to serve tokens is far below and falling faster than token prices. Each new generation of hardware drops the cost to serve even further. As above, this rhymes with other sources including Anthropic's S-1.

Regarding your point about the 2008 GFC, the difference here is that their individual incentives are not at odds with the global good, because at this point it appears to be bad for everybody! In the GFC there was no real pain until the crash; here the pain is all around from the start. The hyperscalers are actively torching their extremely profitable cash flows (along with a lot of goodwill) and taking on heavy debt, despite being punished by the stock market, to fund this buildout that apparently everybody hates but can't stop using.

Niiiiice joke :)

> along with a lot of goodwill

One word: Oracle :))

Or two more: Google Microsoft :))

So we are not allowed to guess anything because not every facts are known ? Not nice try.

Fact: they are burning someone money. Or rather: they already burned a lot of money. For sure that was VC's and investors cash. Maybe some loans.

And now they trying to offload debt via IPO's.

Now: hardware side. Micron stopped producing what peoples wanted and still want to buy. So memory prices skyrocketed - llm industry own way of crafting inflation.

Nvidia sells and also buys and lots of promises circling around.

Oracle and Amazon buys at least from Nvidia and sells and take lots of promises too.

That influences markets and now IPO tries to cash on hype wave.

That's what is known so:

a) That does suggest circularity as some suspects

b) We know VC's cash is used for burning since few decades - they trow cash and dream about swans and unicorns :>

So who from "outside" throw money "into the system" ?? Certainly it not coming from selling inference.

All that is enough to start investigations.

Or you are trying to push: we don't know let's they do whatever they want with all that pensions invested ? Then I say: who pays you ?

> apparently everybody hates but can't stop using

Yep. llms momorization of knowledge is helpful for fast retreaving. But making it artificially scarcity and cashing on it is not good heart doing and nowhere close to goodwill. Especially in US making money is not a crime. But some schemes are.