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

Gary Marcus Marcus on AI Published

Reports of the birth of AGI are greatly exaggerated

We recorded 11 claims from this post. 4 were checked against evidence. 7 can’t be checked. 8 more are held. Read the post at its source.

Claims from this post (11)

In the order they appear in the post. Each quotation is the speaker’s words in this post. A label such as “Supported” or “Can’t be checked” is the claim’s current assessment; its page has the evidence and the reasons.

  1. Assessment: Can’t be checkedSaid

    “The problem with the paper though isn’t just its hostility towards critics, or the way in which it lowers the bar, it’s that its key arguments don’t go through.”

    What we tested: The problem with the Agüera y Arcas and Norvig paper is not just its hostility toward critics or the way it lowers the bar for AGI, but that its key arguments don't go through.

  2. Assessment: UnresolvedSaid

    “The first author’s nine-year-old can do five digit multiplication better than an LLM.”

    What we tested: The first author's own nine-year-old child can do five-digit multiplication better than an LLM.

  3. Assessment: Can’t be checkedSaid

    “It’s certainly plausible that some of the prerequisites of AGI may have been achieved, but considerable overreach to presume that all of “the most important ones” have already been invented.”

    What we tested: It is certainly plausible that some prerequisites of AGI may have been achieved, but it is considerable overreach to presume that all of the most important ones have already been invented.

  4. Assessment: Can’t be checkedSaid

    “Maybe what’s required already exists, but more likely, we are still at least a few paradigm shifts away .”

    What we tested: AGI is more likely than not still at least a few paradigm shifts away.

  5. Assessment: Can’t be checkedSaid

    “The fact that LLMs trained on the task of next-token prediction can also do a pretty good job at a variety of natural language tasks, and, very recently, a considerably less good job of tasks that combine text with images, as emphasized by Agüera y Arcas and Norvig is certainly interesting, but it doesn’t justify the claim that they constitute “general intelligence”.”

    What we tested: LLMs trained on next-token prediction doing a pretty good job at a variety of natural language tasks, and very recently a considerably less good job at tasks combining text with images, is certainly interesting but does not justify the claim that they constitute general intelligence.

  6. Assessment: SupportedSaid

    “Transformers and generative AI are getting a lot of attention, and have considerable utility, but they are nothing like the all purpose tools some people seems to imagine them to be.”

    What we tested: Transformers and generative AI are getting a lot of attention and have considerable utility, but they are nothing like the all-purpose tools some people seem to imagine them to be.

    What happened: The cumulative usage disclosed on this date demonstrates substantial engagement. The same paragraph documents uses including illustrated stories, social-media thumbnails and design inspiration, supporting practical utility without establishing universal reliability. (Microsoft Bing, )

  7. Assessment: Can’t be checkedSaid

    “In AI, no single technique is likely to be a silver bullet, now or ever.”

    What we tested: No single AI technique is likely ever to be a silver bullet.

  8. Assessment: UnresolvedSaid

    “There are some applications where the current systems are reliable enough to be practically useful, though not nearly as many as is often claimed.”

    What we tested: Current systems are reliable enough to be useful in some applications, but far fewer than often claimed.

  9. Assessment: SupportedSaid

    “No doubt the next generation of systems will have greater abilities and more extensive applications and will somewhat mitigate the weaknesses.”

    What we tested: The next generation of systems will, without doubt, have greater abilities and more extensive applications and will somewhat mitigate the weaknesses of current systems.

    What happened: The first incremental successor reports fewer false statements than the October-generation Claude 2.0 on the company's factual-question evaluation. This directly supports mitigation of an existing weakness, within that evaluation's scope. (Anthropic, )

  10. Assessment: Can’t be checkedSaid

    “But there is zero justification for claiming that the current technology has achieved general intelligence.”

    What we tested: There is zero justification for claiming that the current technology has achieved general intelligence.

  11. Assessment: Can’t be checkedSaid

    “Current models trained on next-token prediction have remarkable abilities and remarkable weaknesses. The scope of those abilities and weaknesses of the current systems is not well understood.”

    What we tested: Current next-token prediction models have remarkable abilities and weaknesses whose scope is not well understood.

Held from this post (8)

These records did not pass every check, so nothing about them is published. Held is not a finding.