ClaimsGary Marcus

“a year ago today I posted “deep learning: a critical appraisal”, asking whether DL might be approaching a wall, and be just one tool among many needed for AGI.”

Gary Marcus, writing on X 2 January 2019 Post by @GaryMarcus on X, 2019-01-02 (X)

Factual AI capabilities

Gary Marcus posted "Deep Learning: A Critical Appraisal" on 2018-01-02, asking whether deep learning might be approaching a wall and be just one tool among many needed for AGI.

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?

What would count as true or false

True if a paper or article by Gary Marcus titled "Deep Learning: A Critical Appraisal" was first posted publicly (e.g. arXiv submission date or blog post date) on 2 January 2018, and its text raises whether deep learning may be approaching a wall and argues it is one tool among several needed for AGI or general intelligence. Mostly true if it was posted within a few days of 2 January 2018, or if one of the two framings (approaching a wall; one tool among many) is present only loosely or in different words. Mixed if the paper exists under that title but the date is off by weeks to months, or only one of the two arguments appears. Mostly false if the date is off by more than a year, or the paper makes neither argument in recognisable form. False if no such paper by Marcus exists, or it was first posted in a clearly different year.

Set before the research began.

Evidence (4)

  1. E1 Gary Marcus’ Deep Learning Critique Triggers Backlash | Synced Synced · 6 January 2018

    “On January 2, NYU Professor and Founder of Uber-owned machine learning startup Geometric Intelligence Gary Marcus published the paper Deep Learning: A Critical Appraisal on ArXiv.”
  2. E2 Gary Marcus’ Deep Learning Critique Triggers Backlash | Synced Synced · 6 January 2018

    “So is deep learning hitting a wall as argued in Marcus’ paper?”
  3. E3 Gary Marcus’ Deep Learning Critique Triggers Backlash | Synced Synced · 6 January 2018

    “He then raised possibilities for a future beyond deep learning: focus more on unsupervised learning; symbol-manipulation (aka GOFAI, the Good Old-Fashioned AI); derive insights from cognitive and developmental psychology; or focus more on acquiring common sense knowledge, scientific reasoning, game playing, etc.”
  4. E4 Deep Learning: A Critical Appraisal axi.lims.ac.uk (arXiv 1801.00631 listing)

    “I present ten concerns for deep learning, and suggest that deep learning must be supplemented by other techniques if we are to reach artificial general intelligence.”

Reasoning

An independent Synced article dated 6 January 2018 reports that Marcus published "Deep Learning: A Critical Appraisal" on arXiv on January 2 (E1). The arXiv identifier 1801.00631 is consistent with January 2018 (E4). The paper's abstract says deep learning must be supplemented by other techniques to reach artificial general intelligence, which matches the "one tool among many" framing (E4). Synced describes the paper as arguing that deep learning is hitting a wall (E2), and says it points to approaches beyond deep learning (E3).

Cite this claim

Gary Marcus, “Gary Marcus posted "Deep Learning: A Critical Appraisal" on 2018-01-02, asking whether deep learning might be approaching a wall and be just one tool among many needed for AGI.” (said 2 January 2019). Verdict: resolved true. Reliability API, claim c_4420abdd274c, method 0.1.0+c876030c, dataset release v1.1.2. https://epistacklabs.com/claims/c_4420abdd274c

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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