ClaimsGary Marcus

“with some “chortling” and skepticism from me”

Gary Marcus, posting on X 30 April 2020 Post by @GaryMarcus on X, 2020-04-30 (X)

Factual AI capabilities

A piece on common sense in AI by John Pavlus includes some chortling and skepticism from Gary Marcus.

Resolved true The record shows it happened or was so.

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

The second judge would not resolve this claim; the verdict shown is the first judge's.

What would count as true or false

This is a factual claim judged as of 2020-04-30. It is true if an article on common sense in AI by John Pavlus, published on or before about 2020-04-30 (for example in Quanta Magazine), quotes or paraphrases Gary Marcus in a skeptical or dismissive way about the AI approaches it discusses. The word 'chortling' is Marcus's own playful description and does not need to appear literally. Any amused or dismissive reaction attributed to him counts. Mostly true: the article includes Marcus's skepticism but is slightly off the described topic or date (for example published a few days after the post). Mixed: Marcus appears in the article, but his comments are mainly neutral or supportive, with little skepticism. Mostly false: the article is by a different author, or Marcus is only mentioned in passing with no skeptical comment. False: no such Pavlus article exists, or it does not mention Marcus at all.

Set before the research began.

Evidence (3)

  1. E1 Common Sense Comes to Computers Quanta Magazine · 30 April 2020

    “Marcus posted the exchanges to his Twitter account with his own added commentary: “LMAO,” internet slang for a derisive chortle.”
  2. E2 Common Sense Comes to Computers Quanta Magazine · 30 April 2020

    “To him and others, COMET’s approach suffers from a fundamental limitation of deep learning: “statistics ≠ understanding.” “You can see that [COMET] does a decent job of guessing some of the parameters of what a sentence might entail, but it doesn’t do so in a consistent way,” Marcus wrote via email.”
  3. E3 Common Sense Comes to Computers Quanta Magazine · 30 April 2020

    “Marcus, a prominent critic of AI hype, gave the neural network a pop quiz.”

Reasoning

The Quanta Magazine article on common sense in AI, dated 2020-04-30, says Marcus posted exchanges to his Twitter account with his own commentary, "LMAO," which it calls "a derisive chortle" (E1). It also quotes him saying the approach suffers from "statistics ≠ understanding" and is inconsistent (E2), and calls him "a prominent critic of AI hype" who gave the network "a pop quiz" (E3). The topic, the date and the skeptical comments attributed to Marcus all match the criteria. The quoted excerpts do not show the byline, so the evidence does not directly confirm that John Pavlus wrote the article, but everything else matches the claim.

Cite this claim

Gary Marcus, “A piece on common sense in AI by John Pavlus includes some chortling and skepticism from Gary Marcus.” (said 30 April 2020). Verdict: resolved true. Reliability API, claim c_415fb64bcc39, method 0.1.0+c876030c, dataset release v1.1.2. https://epistacklabs.com/claims/c_415fb64bcc39

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

Reply to this claim

For Gary Marcus, or someone speaking for them: a correction or counter-evidence. Replies are read before anything is shown; an approved reply shows your name, role, date, statement and link. Your email address is never shown and is deleted 30 days after the decision (privacy).

More factual claims by Gary Marcus

  1. Mostly true Factual January 2026
    “Reviews by Joanna Stern and Marques Brownle of one early prototype were damning;”

    Reviews by Joanna Stern and Marques Brownlee of one early humanoid robot prototype were damning.

  2. Mostly true Factual January 2026
    “Many would agree we have reached a point of diminishing returns for scaling; faith in scaling as a route to AGI has dissipated.”

    Many would agree the AI field has reached a point of diminishing returns from scaling, and faith in scaling as a route to AGI has dissipated.

  3. Mostly true Factual January 2026
    “Despite all the hype, agents didn’t turn out to be reliable.”

    AI agents did not turn out to be reliable in 2025.

  4. Mixed Factual 2025
    “but the systems don’t have the knowledge graph to do that.”

    Current AI systems lack the knowledge graph needed to handle easy facts like those on the first page of Wikipedia.

  5. Resolved true Factual 2025
    “Hasn’t worked so far. That’s for sure.”

    Bolting extra components onto an LLM and scaling it up has so far not produced human-level AGI.

All of them

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