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.
Assessment: UnresolvedSaid
Observation
“The real value was always the people, not the IP, not the data, not the customer list, not the infrastructure.”
Our reading: OpenAI's real value was always its people, not its IP, data, customer list or infrastructure.
No horizon Evidence as of
Limitation: Workforce and technology value may depend on each other.
Assessment: SupportedSaid
Observation
“OpenAI’s strength has been in scaling up an existing paradigm (Transformers) that was developed elsewhere (Google), not developing new paradigms.”
Our reading: OpenAI's strength has been scaling the Transformer paradigm developed at Google, not developing new paradigms.
No horizon Evidence as of
Limitation: This is a qualitative assessment of the principal GPT advances, not a ranking of every OpenAI research contribution.
Assessment: SupportedSaid
Observation
“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.”
Our reading: The hallucination problem has never been solved and may not be until a new paradigm is found.
No horizon Evidence as of
Limitation: Support concerns a general solution, not whether particular applications could achieve useful reliability.
Assessment: Can’t be checkedSaid
Forecast
“OpenAI might find that new paradigm some day, but someone else (e.g., DeepMind or Anthropic) might well get there first.”
Our reading: Someone other than OpenAI, such as DeepMind or Anthropic, might well find the new paradigm beyond current LLMs before OpenAI does.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“That income is mostly ‘proof of concept” testing, but that income could dry up.”
Our reading: OpenAI's income this year is mostly from proof-of-concept testing, and that income could dry up.
No horizon
Qualifier: mostly
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“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.”
Our reading: Investors should have been deterred by OpenAI's prospectus warning that investment be viewed as a donation.
No horizon
Assessment: UnresolvedSaid
Causal claim
“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.”
Our reading: OpenAI's nonprofit-hybrid structure was a ticking time bomb because profit-seekers and safety-focused nonprofit stewards would inevitably conflict.
No horizon Evidence as of
Limitation: Both principal causal accounts come from parties involved in the dispute.
Assessment: Can’t be checkedSaid
Forecast
“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.”
Our reading: Even if OpenAI gets past the board drama, the profit-vs-safety tension will likely remain and weaken its value as a business.
No horizon
Qualifier: even if they get past the drama
Assessment: Can’t be checkedSaid
Observation
“They never really seemed ready to pursue that, but again, there was always a looming reality that they weren’t facing.”
Our reading: OpenAI never seemed ready to move beyond LLMs.
No horizon
Assessment: UnresolvedSaid
Forecast
“Large language models alone were never going to solve the alignment problem.”
Our reading: Large language models alone were never going to solve the alignment problem.
No deadline stated Evidence as of
Limitation: The experiments do not establish reliable alignment across all relevant deployment settings.
Assessment: SupportedSaid
Observation
“And the overriding nonprofit mission was always going to be at odds with a pure for profit play.”
Our reading: OpenAI's nonprofit mission was inherently at odds with a pure for-profit business.
No horizon Evidence as of
Limitation: The outcome depends on reading at odds as a structural constraint, not perpetual operational conflict.
Assessment: Can’t be checkedSaid
Forecast
“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.”
Our reading: Thrive Capital probably will not now invest in OpenAI at an $86B valuation.
No horizon
Qualifier: after the board drama
Assessment: Can’t be checkedSaid
Rhetoric
“They may have just dodged a bullet.”
Our reading: 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.
No horizon
Only if: probably now won't invest
Held from this post (9)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The two reviews read the claim differently
- Attribution is uncertain
- The record does not meet the current rules. Our reading, not assessed: OpenAI's 2023 revenue of $1-2B has unclear profit, and few companies testing LLMs were using them in production.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: OpenAI is a company with no obvious moat, modest revenue relative to its valuation, and a sky-high valuation above more established companies like FedEx, Airbnb and Colgate-Palmolive, all built on a promise that always seemed to Marcus not to be realistic.
- The record does not meet the current rules. Our reading, not assessed: Elon Musk's Grok replicated much, though not all, of what OpenAI had done in a few months, and Kai-Fu Lee's new company replicated a lot of it in less than a year.
- The criteria are ambiguous. Our reading, not assessed: OpenAI still has no clear business model and systems like GPT-4 remain expensive to run.
- The two reviews read the claim differently