“Microsoft, Meta, Amazon, and Google have all burned billions on the assumption that doing so would create something — be it a human-level "artificial general intelligence" or, I dunno, a product that would justify the costs — and it's become painfully obvious that it isn't going to work.”
Our reading:
Big tech's strategy of scaling data centers, GPUs and training data will not produce AGI or a product that justifies the costs.
Assessment: Unresolved
What happened
Did the forecast come true?
Outcome: Unresolved
We checked, and the evidence so far doesn’t settle it.
Judged on a plain reading. They named no measure, so we used the reading a typical informed reader would take. It is spelled out under “How we judged it”.
Evidence up to . Checked .
Why
The post, published 2024-12-03, forecasts with no deadline that big tech's scaling spending will produce neither AGI nor a product that justifies its cost. The contract lets this be settled early only by a widely recognized AGI demonstration, by filings showing AI profits cover cumulative AI capex, or by the named firms abandoning or impairing their AI build-outs for lack of returns. The one evidence item is background. In The Register on 2024-11-01, an Informa analyst estimated that hyperscalers had spent about $200 billion in capex since the start of 2023, while AI services brought in only about $20 billion in revenue. That figure comes from before the post and describes where the forecast started, not how it turned out. The packet contains no evidence that meets either early-resolution rule. The forecast remains open.
Caveats
- The packet holds one context item, dated before the post. It does not show whether any qualifying AGI demonstration, payback disclosure, or abandonment or impairment has happened since.
- The $200 billion and $20 billion figures are one analyst's estimates across hyperscalers. They are not company disclosures and are not broken out for each named firm.
- 'Justify the costs' has no stated threshold or payback period, and AGI has no agreed definition.
Evidence (1 item)
Context only: The Register,
With around $200 billion in capex, only about $20 billion of revenue is actually coming from consumers and businesses in terms of AI services
Why it matters: Shows the gap between spending and AI revenue at the time of the post. That is the starting point for the forecast, not its outcome.
- Publisher
- The Register
- Kind of source
- News report
- About events on
- Published
How we judged it
- Kind of claim
- Forecast
- Deadline
- None given. We don’t add one.
Where we had to interpret
- This is a forecast with no deadline: big tech's scaling strategy will produce neither AGI nor a product whose returns justify the spending.
- 'Justify the costs' is read plainly: AI revenue and profit large enough to earn back the AI capital spending.
- 'Isn't going to work' cannot be shown true before some end point, so it can only be settled early by a decisive event.
Right if: The named companies publicly abandon or sharply write down their AI build-outs, with impairments or capex cuts they attribute to failed AI returns, without having produced AGI or a product that pays for the spending.
Wrong if: A widely accepted demonstration of human-level AGI by one of these companies, or company disclosures showing that AI products earn returns that cover the scaling investment.
We wrote this test after the outcome was known.
What would settle it
A widely recognized AGI demonstration by one of the named companies, company filings showing that AI profits cover cumulative AI capex, or the named firms abandoning or impairing their AI data center build-outs and attributing it to a lack of returns.
We found 34 claims in this post. See them all.
Full record
Source and dates
Where's Your Ed At, Godot Isn't Making it, paragraph 24.
- Said
- We read the source
- live page, full text, public
- Evidence up to
- Checked
We read this wording on 2026-10-28. The post may have been edited after 2024-12-03.
Where it was said (1)
Said once in the posts we read.
: Where's Your Ed At, Godot Isn't Making it
Microsoft, Meta, Amazon, and Google have all burned billions on the assumption that doing so would create something — be it a human-level "artificial general intelligence" or, I dunno, a product that would justify the costs — and it's become painfully obvious that it isn't going to work.
- Where
- paragraph 24
- Published
- 2024-12-03
- We read it
- , live page
- Access
- full text, public
History
Versions
- Current: Unresolved. Evidence up to 2026-10-28.
What happened to this record
PublishedBy us
Published after both AI reviews and the final check passed.