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

Gary Marcus Marcus on AI Published

Top 5 reasons why OpenAI was probably never really worth $86 billion

We recorded 13 claims from this post. 6 were checked against evidence. 7 can’t be checked. 9 more are held. Read the post at its source.

Claims from this post (13)

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: UnresolvedSaid

    “The real value was always the people, not the IP, not the data, not the customer list, not the infrastructure.”

    What we tested: OpenAI's real value was always its people, not its IP, data, customer list or infrastructure.

  2. Assessment: SupportedSaid

    “OpenAI’s strength has been in scaling up an existing paradigm (Transformers) that was developed elsewhere (Google), not developing new paradigms.”

    What we tested: OpenAI's strength has been scaling the Transformer paradigm developed at Google, not developing new paradigms.

    What happened: The original paper introduces the Transformer and lists Google Brain and Google Research affiliations, alongside a University of Toronto affiliation. This supports the Google research provenance without implying that every author had only a Google affiliation. (Ashish Vaswani and colleagues / arXiv, )

  3. Assessment: SupportedSaid

    “There has never been a solution to the hallucination problem, and it’s not clear that there will be until we find a new paradigm, as Altman himself partly acknowledged last week, when he did his best Gary Marcus impression.”

    What we tested: The hallucination problem has never been solved and may not be until a new paradigm is found.

    What happened: OpenAI acknowledged residual factual hallucinations in GPT-4. The surrounding discussion reports improvements, not elimination. (OpenAI, )

  4. Assessment: Can’t be checkedSaid

    “OpenAI might find that new paradigm some day, but someone else (e.g., DeepMind or Anthropic) might well get there first.”

    What we tested: Someone other than OpenAI, such as DeepMind or Anthropic, might well find the new paradigm beyond current LLMs before OpenAI does.

  5. Assessment: Can’t be checkedSaid

    “That income is mostly ‘proof of concept” testing, but that income could dry up.”

    What we tested: OpenAI's income this year is mostly from proof-of-concept testing, and that income could dry up.

  6. Assessment: Can’t be checkedSaid

    “The fact that the prospectus warned that the whole thing should be viewed “as a donation” doesn’t seem to have much deterred the investors, but it should have.”

    What we tested: Investors should have been deterred by OpenAI's prospectus warning that investment be viewed as a donation.

  7. Assessment: UnresolvedSaid

    “The whole nonprofit-hybrid model, introduced in 2019 (the company was originally pure non-profit) was always a ticking time bomb, because the people trying to make money were never going to have a perfect relationship with those in the nonprofit that were charged with keeping the world safe.”

    What we tested: OpenAI's nonprofit-hybrid structure was a ticking time bomb because profit-seekers and safety-focused nonprofit stewards would inevitably conflict.

  8. Assessment: Can’t be checkedSaid

    “They may yet get past it, but the tension at the middle would likely remain, always weakening the value of the company as a pure business play.”

    What we tested: Even if OpenAI gets past the board drama, the profit-vs-safety tension will likely remain and weaken its value as a business.

  9. Assessment: Can’t be checkedSaid

    “They never really seemed ready to pursue that, but again, there was always a looming reality that they weren’t facing.”

    What we tested: OpenAI never seemed ready to move beyond LLMs.

  10. Assessment: UnresolvedSaid

    “Large language models alone were never going to solve the alignment problem.”

    What we tested: Large language models alone were never going to solve the alignment problem.

  11. Assessment: SupportedSaid

    “And the overriding nonprofit mission was always going to be at odds with a pure for profit play.”

    What we tested: OpenAI's nonprofit mission was inherently at odds with a pure for-profit business.

    What happened: The section gives the nonprofit board control and says investors and employees accept the Charter's priority even at the expense of their financial stakes. Those explicit constraints support the structural reading of conflict with a purely profit-driven investment. (OpenAI, )

  12. Assessment: Can’t be checkedSaid

    “Of course after all the drama, the company that was reportedly about to invest at a reported $86 billion valuation, Thrive Capital, and its own investors, like CalPERS (the California pension system which is believed to have financed Thrive in part) probably now won’t.”

    What we tested: Thrive Capital probably will not now invest in OpenAI at an $86B valuation.

  13. Assessment: Can’t be checkedSaid

    “They may have just dodged a bullet.”

    What we tested: Thrive Capital and its investors, such as CalPERS, who probably now won't invest at the reported $86 billion valuation, may have just dodged a bullet.

Held from this post (9)

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