“I personally haven't changed; I still think that LLMs are unreliable, and still think that they are a very poor basis for factuality.”
Our reading, the sentence that was checked:
LLMs are unreliable.
Assessment: Supported Evidence as of
Where and when Gary Marcus wrote it
Marcus on AI, The Open Letter Controversy, paragraph 16.
- Said
- Source observed
- live page, full text, public
- Evidence as of
- the cutoff for this assessment
- Assessment recorded
- assessment marcus-the-open-letter-controversy-dcb6c2-a1
We recorded 12 claims from this post. See every claim from this post.
The wording above is the version this site observed on 2026-10-29. The source may have been edited after 2023-03-30. 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 are unreliable
Our interpretation
- In the adjacent factuality context, unreliable means that contemporary LLMs could produce material factual or reasoning errors and should not be trusted without checking.
- The statement does not mean that every answer is wrong or that LLMs fail at every task.
- The current-state assessment uses March 1–30, 2023, the latest publication-month evidence through the post date.
Counts as supported if: Contemporary leading LLMs have documented factual or reasoning failures that prevent dependable unchecked use.
Counts as contradicted if: Representative evaluations establish dependable factual and reasoning performance across ordinary uses without material recurring errors or a need for verification.
Retrospective: these criteria were written after the outcome was public.
Current assessment
Was it true for the period described?
Outcome: Supported
The dated evidence matches 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
Both OpenAI and Google documented factual failures in their March 2023 models. OpenAI also identified reasoning errors, and Google warned that false answers could appear confident. This supports unreliability in the passage's factual-use context. GPT-4's reported improvement over GPT-3.5 is material, but relative improvement does not remove the documented failures.
Limitations
- The evidence is developer disclosure rather than an independent cross-model audit.
- The claim is supported for unchecked factual use, not as a claim that LLMs cannot perform useful tasks.
- No universal error rate is inferred.
Evidence (2 items)
Supports the claim: OpenAI,
Most importantly, it still is not fully reliable (it “hallucinates” facts and makes reasoning errors).
Why it matters here: OpenAI identifies factual and reasoning failures in its released model and recommends care in using its outputs. The same section reports a 40% improvement over GPT-3.5 on internal adversarial factuality evaluations, which qualifies the criticism without establishing dependable absolute reliability.
- Publisher
- OpenAI
- Kind of source
- Company disclosure: the company describing itself, not an independent finding
- Describes events of
- Public from
Supports the claim: Google,
And they can provide inaccurate, misleading or false information while presenting it confidently.
Why it matters here: Google describes confident false answers and gives a concrete botanical error from Bard. This shows that the reliability concern was present in another contemporary model family.
- Publisher
- Kind of source
- Company disclosure: the company describing itself, not an independent finding
- Describes events of
- Public from
Where it was said (1)
Said once in the sources this register covers.
: Marcus on AI, The Open Letter Controversy
I personally haven't changed; I still think that LLMs are unreliable, and still think that they are a very poor basis for factuality.
- Where
- paragraph 16
- Published
- 2023-03-30
- Source observed
- , live page
- Access
- full text, public
History
Assessment versions
- Assessment marcus-the-open-letter-controversy-dcb6c2-a1: Current. Outcome: Supported. 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.
About assessment marcus-the-open-letter-controversy-dcb6c2-a1.