Pundit ClaimsAI claims by Gary Marcus and Ed Zitron, with the evidence

“LLMs will always hallucinate, their outputs are not trustworthy as a result, they cannot be deterministic, and any chance of any mistakes of any kind are unforgivable.”

I Will Never Respect A Website, paragraph 6. The full statement is at the source.

Our reading, the sentence that was checked:

LLMs cannot be deterministic.

Assessment: Contradicted Evidence as of

Where and when Ed Zitron wrote it

Where's Your Ed At, I Will Never Respect A Website, paragraph 6.

Said
Source observed
live page, full text, public
Evidence as of
the cutoff for this assessment
Assessment recorded
assessment wyea-i-will-never-respect-a-website-d4324f-2-a1

We recorded 36 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 2026-04-14. This page does not claim the wording was captured then.

What the claim commits to

Kind
Observation
Deadline, as the speaker wrote it
None stated. This site does not add one.
Deadline state when assessed
No horizon
Deadline state on 2026-10-29
No horizon (the release’s reference date)

From the speaker

  • LLMs
  • cannot be deterministic

Our interpretation

  • The ordinary technical meaning of deterministic is producing identical outputs from identical inputs under fixed model and execution conditions.
  • The claim denies that deterministic LLM inference is possible; it does not merely describe default behavior of hosted chatbot services.
  • This is an as-of-publication capability claim without a reporting cycle. The target covers implementations already demonstrated by 2026-04-14, with no lower date supplied by the speaker.
  • Reproducibility and factual correctness are separate properties.

Counts as supported if: Evidence that LLM inference necessarily varies despite fixed inputs, model parameters, decoding and execution conditions, with no feasible deterministic implementation.

Counts as contradicted if: A documented LLM implementation that provides reproducible inference under specified conditions, supported by implementation details and repeated-output tests.

Retrospective: these criteria were written after the outcome was public.

Current assessment

Was it true for the period described?

Outcome: Contradicted

The dated evidence goes against what the claim committed to, under the criteria frozen before grading.

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 horizon
Assessment recorded
Policy version
2026-10-28.7

Rationale

Before the post, Thinking Machines Lab documented deterministic LLM inference and reported 1,000 identical completions after changing its inference kernels. That contradicts the claim that LLMs cannot be deterministic. The same report explains why ordinary inference services can vary even at temperature zero; default variability is compatible with deterministic implementations.

Limitations

  • The evidence is the implementing lab's report, not an independent replication.
  • The result requires specified inference controls and does not promise identical outputs across arbitrary hardware or software changes.
  • Deterministic output can still contain factual errors.

Evidence (1 item)

  • Goes against the claim: Thinking Machines Lab,

    1000 completions are identical.

    Why it matters here: The authors report identical completions for Qwen3-235B-A22B-Instruct-2507 using temperature zero and batch-invariant kernels. The report explains the implementation and supplies a direct counterexample to impossibility.

    Publisher
    Thinking Machines Lab
    Kind of source
    Demonstration
    Describes events of
    Public from

Where it was said (1)

Said once in the sources this register covers.

  • : Where's Your Ed At, I Will Never Respect A Website

    LLMs will always hallucinate, their outputs are not trustworthy as a result, they cannot be deterministic, and any chance of any mistakes of any kind are unforgivable.

    Published
    2026-04-14
    Source observed
    , live page
    Access
    full text, public

History

Assessment versions

Recorded events

  1. Assessment publishedBy this site

    First assessment published after both reviews and the final-text check passed.

    About assessment wyea-i-will-never-respect-a-website-d4324f-2-a1.