ClaimsDario Amodei

“At the present moment, it is still the case that pre-training is the majority of the cost.”

Dario Amodei, Anthropic CEO, interviewee 11 November 2024 Transcript for Dario Amodei: Anthropic CEO on Claude, AGI & the Future of AI & Humanity (Lex Fridman Podcast)

Factual AI compute, hardware and data

As of late 2024, pre-training accounts for the majority of the cost of building AI models.

Unresolvable The public record could not settle it.

Factual: Statements about the present or the past, checked against the record: did they hold up?

Reasoning

Cost breakdowns are not published, and the claim covers all AI models, so no public record settles it.

Cite this claim

Dario Amodei, “As of late 2024, pre-training accounts for the majority of the cost of building AI models.” (said 11 November 2024). Verdict: unresolvable. Reliability API, claim c_5d1367599ca6, method 0.1.0+c876030c, dataset release v1.1.2. https://epistacklabs.com/claims/c_5d1367599ca6

This claim is in dataset release v1.1.2, with the same verdict.

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More factual claims by Dario Amodei

  1. Mostly true Factual 28 February 2026
    “the amount of computation that goes into the models doubles every four months.”

    The amount of computation going into AI models doubles every four months.

  2. Mostly true Factual 5 June 2025
    “Distillation of frontier models allows lagging companies to narrow the gap using a fraction of the cost it would take to develop their own AI independently.”

    Distillation of frontier models lets lagging companies narrow the gap at a fraction of the cost of developing their own AI independently.

  3. Mostly false Factual 10 March 2025
    “I thought it was a very plausible blocker one or two years ago.”

    Dario Amodei thought one or two years before March 2025 that data limits were a very plausible blocker to AI progress.

  4. Mostly true Factual 13 October 2022
    “Importantly, because this type of RL is new, we are still very early on the scaling curve”

    Because reasoning-focused RL is new, the amount all AI developers spend on the RL training stage is still small, so the field is early on its scaling curve.

  5. Resolved true Factual 13 October 2022
    “I'd guess the number today is maybe ~4x/year.”

    The current rate of algorithmic curve shift is maybe about 4x per year.

All of them

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