“For one thing, although many people seem to have heard of a few of these errors (e.g. from reports in the media), few realize how pervasive or broad in scope they are; indeed a recent Twitter thread that claimed falsely that these problems had been resolved got a surprising amount of traction.”
Our reading, the sentence that was checked:
Although many people seem to have heard of a few of ChatGPT's errors, few realize how pervasive or broad in scope they are, and a recent Twitter thread falsely claiming these problems had been resolved got a surprising amount of traction.
Assessment: Unresolved Evidence as of
Where and when Gary Marcus wrote it
Marcus on AI, Large Language Models like ChatGPT say The Darnedest Things, paragraph 10.
- Said
- Source observed
- live page, full text, public
- Evidence as of
- the cutoff for this assessment
- Assessment recorded
- assessment marcus-large-language-models-like-chatgpt-7b8b70-a2
We recorded 10 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 2023-01-09. 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)
Conditions
- these errors (ChatGPT's errors described in the post) (scope, stated by the speaker)
- many people seem to have heard of a few (qualifier, stated by the speaker)
From the speaker
- many people seem to have heard of a few of these errors
- few realize how pervasive or broad in scope they are
- a recent Twitter thread
- claimed falsely that these problems had been resolved
- a surprising amount of traction
Our interpretation
- The factual core concerns limited public understanding of the range of ChatGPT errors and a specific, widely circulated thread falsely claiming their resolution.
- For the ongoing awareness claim, the most recent relevant observation window is launch through January 9, 2023.
- The plain reading of traction is substantial circulation or engagement; surprise itself is the author's reaction and has no independent numerical threshold.
- Continuing model errors alone cannot establish what the public understood or what the unidentified thread claimed.
Counts as supported if: Contemporaneous awareness evidence shows that understanding of the breadth of errors was uncommon, and an identified thread with dated engagement records materially claimed that those errors were resolved despite documented continuing failures.
Counts as contradicted if: Comparable awareness evidence shows broad understanding, or the identified thread did not make the attributed claim, lacked substantial circulation, or accurately described resolution of the specific problems it addressed.
Retrospective: these criteria were written after the outcome was public.
Current assessment
Was it true for the period described?
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 horizon
- Assessment recorded
- Policy version
- 2026-10-28.7
Rationale
OpenAI acknowledged on November 30, 2022 that ChatGPT sometimes produced plausible-sounding but incorrect or nonsensical answers [e1]. This disclosure establishes acknowledged errors, but does not establish public understanding of their breadth during November 30, 2022–January 9, 2023, or the referenced thread's claims, accuracy, or circulation [e1]. Neither component is settled by this evidence [e1].
Limitations
- The packet contains no matching contemporaneous awareness research for a defined audience.
- The referenced thread and its engagement by January 9, 2023 were not identified; this does not establish that the thread did not exist.
- The intended audience and the thread's precise scope remain unknown.
Evidence (1 item)
Context only: OpenAI,
incorrect or nonsensical answers.
Why it matters here: OpenAI acknowledged errors at launch. This does not establish how many people understood their breadth, or whether a later thread falsely claimed particular problems were fixed.
- Publisher
- OpenAI
- Kind of source
- Company disclosure: the company describing itself, not an independent finding
- Describes events of
- Public from
What would settle it
Contemporaneous research measuring a defined audience's understanding of ChatGPT's error breadth, plus the archived thread, its engagement by January 9, 2023, and independent error records testing its precise claims.
Where it was said (1)
Said once in the sources this register covers.
: Marcus on AI, Large Language Models like ChatGPT say The Darnedest Things
For one thing, although many people seem to have heard of a few of these errors (e.g. from reports in the media), few realize how pervasive or broad in scope they are; indeed a recent Twitter thread that claimed falsely that these problems had been resolved got a surprising amount of traction.
- Where
- paragraph 10
- Published
- 2023-01-09
- Source observed
- , live page
- Access
- full text, public
History
Assessment versions
- Assessment marcus-large-language-models-like-chatgpt-7b8b70-a2: 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.
About assessment marcus-large-language-models-like-chatgpt-7b8b70-a2.