A knockout blow for LLMs?
We recorded 19 claims from this post. 10 were checked against evidence. 9 can’t be checked. 1 more is held. Read the post at its source.
Claims from this post (19)
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: Can’t be checkedSaid
Recommendation or value judgment
“Apple has a new paper; it’s pretty devastating to LLMs, a powerful followup to one from many of the same authors last year.”
Our reading: Apple's new paper is pretty devastating to LLMs and is a powerful followup to a paper from many of the same authors last year.
No horizon
Qualifier: pretty
Assessment: SupportedSaid
Observation
“neural networks of various kinds can generalize within a training distribution of data they are exposed to, but their generalizations tend to break down outside that distribution.”
Our reading: Neural networks of various kinds can generalize within the training distribution of data they are exposed to, but their generalizations tend to break down outside that distribution.
No horizon Evidence as of
Limitation: Support concerns a recurring empirical weakness, not an impossibility theorem or a measured failure rate for all neural networks.
Assessment: UnresolvedSaid
Observation
“Claude, on the other hand, can barely do 7 discs, getting less than 80% accuracy, left bottom panel below, and pretty much can’t get 8 correct at all.”
Our reading: Claude gets under 80% accuracy on 7-disc Tower of Hanoi and essentially cannot solve 8 discs.
No horizon Evidence as of
Limitation: The original PDFs exceeded the reading tool's size limit.
Assessment: SupportedSaid
Observation
“It is truly embarrassing that LLMs cannot reliably solve Hanoi.”
Our reading: LLMs cannot reliably solve the Tower of Hanoi.
No horizon Evidence as of
Limitation: The evidence does not establish failure for every model, prompt, or tool configuration.
Assessment: Can’t be checkedSaid
Conditional forecast
“If you can’t use a billion dollar AI system to solve a problem that Herb Simon one of the actual “godfathers of AI”, current hype aside) solved with AI in 1957, and that first semester AI students solve routinely, the chances that models like Claude or o3 are going to reach AGI seem truly remote.”
Our reading: If a billion-dollar AI system cannot be used to solve a problem (Tower of Hanoi) that Herb Simon solved with AI in 1957 and that first-semester AI students solve routinely, then the chances that models like Claude or o3 will reach AGI seem truly remote.
No horizon
Only if: if a billion-dollar AI system can't solve a problem Herb Simon solved with AI in 1957 and first-semester AI students solve routinely
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“AGI shouldn’t be about perfectly replicating a human, it should (as I have often said) be about combining the best of both worlds, human adaptiveness with computational brute force and reliability.”
Our reading: AGI should not be about perfectly replicating a human but should be about combining the best of both worlds: human adaptiveness with computational brute force and reliability.
No horizon
Assessment: Can’t be checkedSaid
Rhetoric
“And good luck getting to “alignment” or “safety” without reliabilty.”
Our reading: Marcus sarcastically suggests that getting to 'alignment' or 'safety' without reliability is a long shot.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“I am not interested in a “AGI” that can’t do arithmetic, and I certainly wouldn’t want to entrust global infrastructure or the future of humanity to such a system.”
Our reading: Marcus is not interested in an 'AGI' that can't do arithmetic, and he certainly would not want to entrust global infrastructure or the future of humanity to such a system.
No horizon
Scope: an 'AGI' that can't do arithmetic
Assessment: Can’t be checkedSaid
Forecast
“We are not going to be “extract the light cone” of the earth or “solve physics” [whatever those Altman claims even mean] with systems that can’t play Tower of Hanoi on a tower of 8 discs.”
Our reading: We are not going to 'extract the light cone' of the earth or 'solve physics' (Altman claims whose meaning Marcus questions) with systems that can't play Tower of Hanoi on a tower of 8 discs.
No horizon
Scope: systems that can't play Tower of Hanoi on 8 discs
Assessment: UnresolvedSaid
Observation
“[Aside from this, models like o3 actually hallucinate a bunch more than attentive humans, struggle heavily with drawing reliable diagrams, etc; they happen to share a few weakness with humans, but on a bunch of dimensions they actually fall short.]”
Our reading: Models like o3 hallucinate much more than attentive humans and struggle with reliable diagrams.
No horizon Evidence as of
Limitation: The claim combines two distinct empirical assertions.
Assessment: SupportedSaid
Observation
“What the Apple paper shows, most fundamentally, regardless of how you define AGI, is that LLMs are no substitute for good well-specified conventional algorithms.”
Our reading: LLMs are no substitute for good well-specified conventional algorithms.
No horizon Evidence as of
Limitation: The evidence does not cover every algorithm, model, or configuration.
Assessment: UnresolvedSaid
Observation
“(They also can’t play chess as well as conventional algorithms, can’t fold proteins like special-purpose neurosymbolic hybrids, can’t run databases as well as conventional databases, etc.)”
Our reading: LLMs can't play chess, fold proteins, or run databases as well as conventional or special-purpose systems.
No horizon Evidence as of
Limitation: The packet supplies no qualifying protein-structure or database-execution comparison.
Assessment: SupportedSaid
Observation
“What this means for business and society is that you can’t simply drop o3 or Claude into some complex problem and expect it to work reliably.”
Our reading: o3 or Claude cannot simply be dropped into complex problems and expected to work reliably.
No horizon Evidence as of
Limitation: The evaluations use agent interfaces and do not directly test exclusively unassisted chat.
Assessment: SupportedSaid
Observation
“In the best case (not always reached) they can write python code, supplementing their own weaknesses with outside symbolic code, but even this is not reliable.”
Our reading: LLMs writing Python code to supplement their weaknesses is not reliable.
No horizon Evidence as of
Limitation: The decisive evaluation covers spatiotemporal tasks; it does not establish unreliability in every Python application [e1].
Assessment: Can’t be checkedSaid
Observation
“Worse, as the latest Apple papers shows, LLMs may well work on your easy test set (like Hanoi with 4 discs) and seduce you into thinking it has built a proper, generalizable solution when it does not.”
Our reading: LLMs may succeed on easy test sets and mislead users into thinking they have a generalizable solution when they do not.
No horizon
Assessment: UnresolvedSaid
Forecast
“At least for the next decade, LLMs (with and without inference time “reasoning”) will continue have their uses, especially for coding and brainstorming and writing.”
Our reading: For at least the next decade LLMs will continue to have uses, especially for coding, brainstorming and writing.
Not yet due Evidence as of
Limitation: The evidence covers one provider and an interim usage period.
Assessment: Can’t be checkedSaid
Observation
“But this particular approach has limits that are clearer by the day.”
Our reading: The LLM approach has limits that are becoming clearer every day.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“LLMs are just one form of deep learning, and maybe others — especially those that play nicer with symbols – will eventually thrive.”
Our reading: Other forms of deep learning, especially those that work well with symbols, may eventually thrive.
No horizon
Qualifier: especially those that work better with symbols
Assessment: UnresolvedSaid
Forecast
“But anybody who thinks LLMs are a direct route to the sort AGI that could fundamentally transform society for the good is kidding themselves.”
Our reading: Anybody who thinks LLMs are a direct route to the sort of AGI that could fundamentally transform society for the good is kidding themselves.
No deadline stated Evidence as of
Limitation: The result depends on an evaluator-supplied reading of AGI and 'direct route'.
Held from this post (1)
These records did not pass every check, so nothing about them is published. Held is not a finding.