“At some point Anthropic or OpenAI is going to slow down and then stop making models entirely because it costs too much money to train models, and said costs are only increasing.”
Our reading, the sentence that was checked:
Anthropic or OpenAI will eventually slow and then stop training new models because training costs too much and keeps rising.
Assessment: Unresolved No deadline stated on 2026-10-29 Evidence as of
Where and when Ed Zitron wrote it
Where's Your Ed At, The AI Industry Is Losing, paragraph 149.
- Said
- Source observed
- live page, full text, public
- Evidence as of
- the cutoff for this assessment
- Assessment recorded
- assessment wyea-the-ai-industry-is-losing-30be7c-a1
We recorded 31 claims from this post. See every claim from this post.
The wording above is the version this site observed on 2026-10-28. The source may have been edited after 2026-06-30. This page does not claim the wording was captured then.
What the claim commits to
- Kind
- Forecast
- Deadline, as the speaker wrote it
- “At some point”
- Deadline state when assessed
- No deadline stated
- Deadline state on 2026-10-29
- No deadline stated (the release’s reference date)
Conditions
- because training costs keep rising (qualifier, stated by the speaker)
From the speaker
- At some point
- Anthropic or OpenAI
- slow down and then stop making models entirely
- because it costs too much money to train models
- said costs are only increasing
Our interpretation
- Either company can satisfy the forecast, but the sequence requires a slowdown followed by durable cessation of new-model training.
- 'Entirely' excludes stopping one product line, a temporary training pause, or restrictions on particular training environments.
- Rising unaffordable training costs must be an established cause of cessation.
- 'Because' supplies a causal explanation, not a separate 'if' antecedent.
- No deadline or financial affordability threshold is supplied.
Counts as supported if: Either company demonstrably slows and then durably ceases new-model training because rising training costs have become unaffordable.
Counts as contradicted if: A decisive terminal event makes this outcome impossible for both companies, with reliable evidence establishing that the predicted cost-driven sequence did not occur. Continued training for a finite period is insufficient.
Retrospective: these criteria were written after the outcome was public.
Current assessment
Did the forecast come true?
Outcome: Unresolved
The record was checked, and the evidence available by the cutoff does not settle it.
Scored on a plain reading. The speaker named no measure for this claim, so it was judged on the reading an informed reader would take, stated below under our interpretation. Both reviews had to find that reading fair.
- Evidence as of
- Deadline state when assessed
- No deadline stated
- Assessment recorded
- Policy version
- 2026-10-28.7
Rationale
The documented pauses do not meet the forecast. They concerned safety and security, affected particular workloads, and were followed by resumptions. No qualifying cost-driven cessation was found by October 28. Continued training cannot contradict an eventual prediction with no deadline.
Limitations
- Public records may not reveal every internal training decision.
- A temporary pause is not evidence of permanent cessation.
- The claim gives no financial threshold or accounting basis.
Evidence (2 items)
Context only: OpenAI,
We resumed these workloads on October 1
Why it matters here: The workloads were frontier reinforcement-learning training and internal inference. The disclosed pause concerned security safeguards and ended, so it does not meet the forecast's cessation or cost-causation requirements.
- Publisher
- OpenAI
- Kind of source
- Company disclosure: the company describing itself, not an independent finding
- Describes events of
- Public from
Context only: Anthropic,
paused higher-risk RL environments
Why it matters here: Anthropic describes a limited safety-related interruption and says most reinforcement learning had resumed. This is relevant evidence of a pause, but not of ending all model training because of cost.
- Publisher
- Anthropic
- Kind of source
- Company disclosure: the company describing itself, not an independent finding
- Describes events of
- Public from
What would settle it
A documented slowdown followed by durable cessation of new-model training at either lab, with financial evidence showing rising unaffordable training costs caused it.
Where it was said (1)
Said once in the sources this register covers.
: Where's Your Ed At, The AI Industry Is Losing
At some point Anthropic or OpenAI is going to slow down and then stop making models entirely because it costs too much money to train models, and said costs are only increasing.
- Where
- paragraph 149
- Published
- 2026-06-30
- Source observed
- , live page
- Access
- full text, public
History
Assessment versions
- Assessment wyea-the-ai-industry-is-losing-30be7c-a1: Current. Outcome: Unresolved. Evidence as of 2026-10-28. Public date not recorded.
Recorded events
Assessment publishedBy this site
First assessment published after both reviews and the final-text check passed.