The desperate race to save Generative AI
We recorded 10 claims from this post. 4 were checked against evidence. 6 can’t be checked. 5 more are held. Read the post at its source.
Claims from this post (10)
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
Forecast
“LLMs may eventually be replaced by better technologies, but for now, they aren’t going anywhere, even if some of the commercial purveyors go out of business.”
Our reading: LLMs will not disappear for now even if some commercial providers go out of business, though they may eventually be replaced by better technologies.
No deadline stated Evidence as of
Limitation: Unresolved does not mean the observed trend contradicts the forecast.
Assessment: UnresolvedSaid
Observation
“OpenAI’s lobbying campaign, simply put, is based on a false dichotomy (give everything to us free or we will die)—and also a threat: either we get to use all the existing IP we want for free, or you won’t get to generative AI anymore.”
Our reading: OpenAI's copyright lobbying campaign rests on a false dichotomy and an implied threat that generative AI will go away without free use of IP.
No horizon Evidence as of
Limitation: This is an evidence-access limitation, not a finding that Marcus’s characterization is accurate.
Assessment: SupportedSaid
Observation
“To begin with, the threat is empty: open source LLMs are already out in the wild, and a large number of people know how to build them.”
Our reading: OpenAI's threat that generative AI would disappear is empty because open source LLMs already exist and many people can build them.
No horizon Evidence as of
Limitation: The result uses the ordinary public-model reading of open source.
Assessment: Can’t be checkedSaid
Observation
“Streamers, for example, license everything they stream; there is literally no conceptual reason why OpenAI could not do the same. They just don’t want to.”
Our reading: There is no conceptual reason OpenAI could not license the commercial works it uses, as streamers do; it simply does not want to.
No horizon
Assessment: Can’t be checkedSaid
Causal claim
“Covering all those claims with the accidental infringing machine they have created would be a nightmare. The only chance they have of becoming the zillionaires they aspire to be is to rewrite the rules.”
Our reading: Indemnifying customers against copyright claims would be a nightmare for OpenAI, and its only chance of great riches is rewriting copyright rules.
No horizon
Assessment: UnresolvedSaid
Observation
“It’s likewise a flaw that that current AI cannot learn without a tendency to inadvertently regurgitate big bits of text and images that look uncannily like their sources, but not a logical necessity.”
Our reading: Current AI cannot learn without a tendency to inadvertently regurgitate big bits of text and images that look uncannily like their sources, which is a flaw but not a logical necessity.
No horizon Evidence as of
Limitation: The extraction studies do not establish an unavoidable tendency across contemporary text and image generators [e1, e2].
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“That’s a flaw in the software, not society’s responsibility.”
Our reading: The plagiarism tendency is a software flaw that society should not be responsible for accommodating.
No horizon
Assessment: Can’t be checkedSaid
Observation
“Indeed, as Southen and I pointed out yesterday in the IEEE Spectrum, the tendency towards potential infringement, in current AI looks like maybe it gets worse in bigger models.”
Our reading: The tendency of current AI toward potential infringement may get worse in bigger models.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“If the current batch of AI companies cannot create AI that performs reasonably well based on public domain sources and whatever they are prepared to pay to license, they should go back to the drawing board—and figure out how to build software that doesn’t have a plagiarism problem—rather than fleecing artists, writers, and other content providers.”
Our reading: If the current batch of AI companies cannot create AI that performs reasonably well based on public domain sources and whatever they are prepared to pay to license, they should go back to the drawing board and figure out how to build software that doesn't have a plagiarism problem, rather than fleecing artists, writers, and other content providers.
No horizon
Only if: if the current batch of AI companies cannot create AI that performs reasonably well based on public domain sources and whatever they are prepared to pay to license
Assessment: Can’t be checkedSaid
Conditional forecast
“if UK or other lawmakers succumb to their nonsense arguments, and rewrite existing rules for the benefit of GenAI, abandoning principles that go back to the time of the printing press, there will be momentary jubilation for many, and OpenAI will (maybe, if the GPU costs and unreliability problems don’t otherwise kill them, two big ifs) get rich.”
Our reading: If lawmakers rewrite copyright rules to benefit GenAI, OpenAI may get rich, provided GPU costs and unreliability problems do not kill it.
No horizon
Only if: if lawmakers rewrite copyright rules for GenAI
Held from this post (5)
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
- The criteria are ambiguous. Our reading, not assessed: It is not clear that retrieval augmented generation played a key role in the NYT regurgitation examples.
- The criteria are ambiguous. Our reading, not assessed: Image generation programs have not been using RAG so far, and it would be much harder to do with images.
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: Current AI cannot learn without internet-scale data, a flaw of current methods rather than a necessity for AI in general.