An AI rumor you won’t want to miss
We recorded 6 claims from this post. 3 were checked against evidence. 3 can’t be checked. Read the post at its source.
Claims from this post (6)
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
“Crucially, there has never been any principled argument that they would solve hallucinations or reasoning, or edge cases in open-ended worlds —or that synthetic data would suffice indefinitely to keep feeding the machine.”
Our reading: There has never been a principled argument that scaling would solve hallucinations, reasoning, or open-world edge cases, or that synthetic data would suffice indefinitely.
No horizon Evidence as of
Limitation: The claim concerns the existence of arguments, not whether those arguments ultimately proved correct.
Assessment: SupportedSaid
Observation
“They are merely empirical generalizations that held for a certain period time, when there was enough fresh data and compute.”
Our reading: Scaling laws are merely empirical generalizations that held for a limited period while enough fresh data and compute were available.
No horizon Evidence as of
Limitation: The result depends on reading the sentence in light of the surrounding hedges about scaling having stopped.
Assessment: Can’t be checkedSaid
Observation
“As I wrote yesterday (and first noted back in April), I strongly suspect that, contra Altman, we have in fact reached a point of diminishing returns for pure scaling.”
Our reading: Marcus strongly suspects that pure scaling of AI models has reached a point of diminishing returns, as of November 2024.
No horizon
Assessment: Can’t be checkedSaid
Observation
“Just adding data and compute and training longer worked miracles for a while, but those days may well be over.”
Our reading: The era when simply adding data and compute produced large gains may well be over.
No horizon
Assessment: Can’t be checkedSaid
Conditional forecast
“If the rumor is verified, there could be the AI equivalent of a bank run.”
Our reading: If the rumor that a second major AI company is seeing diminishing returns from scaling is verified, the AI industry could see the equivalent of a bank run.
No horizon
Only if: if the rumor that a second major company hit diminishing scaling returns is verified
Assessment: SupportedSaid
Observation
“Scaling was always a hypothesis.”
Our reading: Scaling (improving AI by adding more data and compute) was always a hypothesis.
No horizon Evidence as of
Limitation: Hypothesis does not mean unsupported speculation.