The False Glorification of Yann LeCun
We recorded 7 claims from this post. 2 were checked against evidence. 5 can’t be checked. 2 more are held. Read the post at its source.
Claims from this post (7)
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: SupportedSaid
Observation
“But he neither invented them nor was he the first to apply the back-propagation algorithm to learning their weights (though many people mistakenly believe this).”
Our reading: LeCun neither invented convolutional neural networks nor was the first to train their weights with back-propagation.
No horizon Evidence as of
Limitation: This result includes temporal convolutional networks; a claim restricted to two-dimensional image CNNs would require a separate priority comparison.
Assessment: Can’t be checkedSaid
Observation
“I was likely the first, with a series of challenges to GPT-2 and GPT-3 on Twitter in the fall of 2019 and in a series of articles in 2019 and 2020.”
Our reading: Marcus was likely the first to argue that large language models would not lead to AGI, through challenges to GPT-2 and GPT-3 in 2019-2020.
No horizon
Assessment: ContradictedSaid
Observation
“(It’s only when ChatGPT eclipsed Meta that LeCun began to be sharply, publicly critical of LLMs)”
Our reading: LeCun began to be sharply and publicly critical of LLMs only when ChatGPT eclipsed Meta.
No horizon Evidence as of
Limitation: The decisive essay was coauthored.
Assessment: Can’t be checkedSaid
Observation
“Instead, I was probably the first person to doubt this publicly, back in 2022:”
Our reading: Marcus was probably the first person to publicly doubt, in 2022, that scaling LLMs would reach human-level AI.
No horizon
Assessment: Can’t be checkedSaid
Observation
“There are serious holes in the scaling argument. To begin with, the measures that have scaled have not captured what we desperately need to improve: genuine comprehension…”
Our reading: The scaling argument has serious holes, because the measures that have improved with scale do not capture genuine comprehension.
No horizon
Assessment: Can’t be checkedSaid
Observation
“What’s more, the so-called scaling laws aren’t universal laws like gravity but rather mere observations that might not hold forever, much like Moore’s law, a trend in computer chip production that held for decades but arguably began to slow a decade ago.11”
Our reading: The so-called scaling laws are not universal laws like gravity but mere observations that might not hold forever, much like Moore's law, which held for decades but arguably began to slow a decade ago.
No horizon
Qualifier: might not hold forever
Assessment: Can’t be checkedSaid
Forecast
“Similarly, Fei-Fei Li is building a world-model focused AI startup, World Labs; based on past experience, I will be surprised if LeCun ever gives her endeavors much mention.”
Our reading: LeCun is unlikely ever to give much mention to Fei-Fei Li's world-model startup, World Labs.
No horizon
Held from this post (2)
These records did not pass every check, so nothing about them is published. Held is not a finding.