Pundit ClaimsAI claims by Gary Marcus and Ed Zitron, with the evidence

Unresolved claims by Gary Marcus, page 9 of 9

Deadlines are judged as of 2026-10-29. About Gary Marcus and the sources covered.

Unresolved claims by Gary Marcus (808)

The record was checked, and the evidence available by the cutoff does not settle it. Forecasts whose deadline has not arrived are listed apart, as not yet due.

Page 9 of 9: claims 801 to 808 of 808, ordered by the date first said, newest first. To find a claim by its words, use search.

  1. Assessment: UnresolvedSaid

    Causal claim

    “The thing is, it’s easy to convince yourself that AI problems are much easier than they are actually are, because of the long tail problem.”

    Our reading: The long tail problem makes it easy to believe AI problems are much easier than they actually are.

    No horizon Evidence as of

    Limitation: The closest empirical evidence uses a simulated robot task.

    Source: Dear Elon Musk, here are five things you might want to consider about AGI

  2. Assessment: UnresolvedSaid

    Observation

    “As Ernie Davis, Scott Aaronson, and I showed, a week or so after the release, it’s easily fooled, especially with complex sentences and words like “similar” that would require a deep understanding of language to be interpreted correctly”

    Our reading: DALL-E 2 is easily fooled, especially by complex sentences and words requiring deep language understanding.

    No horizon Evidence as of

    Limitation: Unresolved does not mean the claim was false.

    Source: Horse rides astronaut

  3. Assessment: UnresolvedSaid

    Causal claim

    “Since we know that Imagen can draw images of horses riding astronauts (if the instructions are specific enough) we know that the failure to draw a horse riding an astronaut given the prompt “a horse riding an astronaut” can only have one explanation: the system doesn’t understand what the prompt “a horse riding an astronaut” means.”

    Our reading: Since Imagen can draw horses riding astronauts when the instructions are specific enough, its failure to draw one from the prompt 'a horse riding an astronaut' can only be explained by the system not understanding what that prompt means.

    No horizon Evidence as of

    Limitation: The available demonstration is not a controlled causal experiment.

    Source: Horse rides astronaut

  4. Assessment: UnresolvedSaid

    Causal claim

    “And, no, it wasn’t about common sense at all.”

    Our reading: Imagen's failure on 'a horse riding an astronaut' was not due to common sense.

    No horizon Evidence as of

    Limitation: The demonstration provides no repeated-sample success rates or controlled comparison separating wording from scene plausibility [e5].

    Source: Horse rides astronaut

  5. Assessment: UnresolvedSaid

    Observation

    “(In reality, Imagen has no idea what weight, mass, or density are.)”

    Our reading: Imagen has no understanding of weight, mass or density.

    No horizon Evidence as of

    Limitation: The behavioral interpretation makes the claim testable but does not settle philosophical questions about understanding.

    Source: Horse rides astronaut

  6. Assessment: UnresolvedSaid

    Causal claim

    “There is no intention to create misinformation—but also no capacity to avoid it, because fundamentally, GPT-3 is a model of how words relate to one another, not a model of how language might relate to the perceived world.”

    Our reading: GPT-3 cannot avoid producing misinformation because it models how words relate to each other, not how language relates to the world.

    No horizon Evidence as of

    Limitation: The evidence is about error rates, not about mechanism.

    Source: Noam Chomsky and GPT-3

  7. Assessment: UnresolvedSaid

    Conditional forecast

    “The bottom line is this, something that AI once cherished but has now forgotten: If we are to build AGI, we are going to need to learn something from humans, how they reason and understand the physical world, and how they represent and acquire language and complex concepts.”

    Our reading: If we are to build AGI, we will need to learn something from humans: how they reason and understand the physical world, and how they represent and acquire language and complex concepts.

    No deadline stated Evidence as of

    Only if: if we are to build AGI

    Source: The New Science of Alt Intelligence

  8. Assessment: UnresolvedSaid

    Observation

    “As I have written, I am fine with thinking of Gato as an “Alt Intelligence”— an interesting exploration in alternative ways to build intelligence—but we need to take it in context: it doesn’t work like the brain, it doesn’t learn like a child, it doesn’t understand language, it doesn’t align with human values, and it can’t be trusted with mission-critical tasks.”

    Our reading: Gato does not work like the brain, learn like a child, understand language, or align with human values, and cannot be trusted with mission-critical tasks.

    No horizon Evidence as of

    Limitation: The evidence is the developers' original report, rather than independent validation of all five assertions [e6].

    Source: The New Science of Alt Intelligence