ClaimsGary Marcus

“And the shortcuts work like 80% of the time, but they don’t work 100%.”

Gary Marcus, speaking in conversation 2025 Dr. Ben Goertzel's Conversation with Dr. Gary Marcus at the World AI Summit 2025 (SingularityNET) archived copy

Factual AI capabilities

The shortcuts that LLMs use work about 80% of the time but not 100%.

Unresolvable The public record could not settle it.

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

Reasoning

The 80% figure is an approximate estimate ("like 80%") with no defined measure.

Cite this claim

Gary Marcus, “The shortcuts that LLMs use work about 80% of the time but not 100%.” (said 2025). Verdict: unresolvable. Reliability API, claim c_4c7053a6a8a3, method 0.1.0+c876030c, dataset release v1.1.2. https://epistacklabs.com/claims/c_4c7053a6a8a3

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

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  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

Verdicts are made automatically; how verdicts are made.