The biggest advance in AI since the LLM
We recorded 8 claims from this post. 4 were checked against evidence. 4 can’t be checked. 2 more are held. Read the post at its source.
Claims from this post (8)
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
“And the thing is, Claude Code is NOT a pure LLM. And it’s not pure deep learning. Not even close.”
Our reading: Claude Code is not a pure LLM and not pure deep learning.
No horizon Evidence as of
Limitation: The independent study is a preprint.
Assessment: UnresolvedSaid
Observation
“The source code leak proves it. Tucked away at its center is a 3,167 line kernel called print.ts.”
Our reading: The leaked Claude Code source shows a 3,167-line kernel called print.ts at its center, proving it is not a pure LLM.
No horizon Evidence as of
Limitation: A longer file alone does not disprove a shorter function inside it.
Assessment: Can’t be checkedSaid
Observation
“But Anthropic figured out that if you really need to get your patterns right, you can’t trust a pure LLM. They are too probabilistic. And too erratic.”
Our reading: Pure LLMs are too probabilistic and erratic to be trusted when patterns must be gotten right, as Anthropic recognized.
No horizon
Qualifier: if you really need to get your patterns right
Assessment: SupportedSaid
Observation
“Putting things differently, Anthropic, when push came to shove, went exactly where I have said for 25 years that the field needed to go: to Neurosymbolic AI.”
Our reading: Anthropic adopted neurosymbolic AI in building Claude Code.
No horizon Evidence as of
Limitation: The result depends on Marcus's broad contextual definition of neurosymbolic AI.
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“What we really need to do to get trustworthy AI rather than the current unpredictable “jagged” mess, is to go in the knowledge-, reasoning-, and world-model driven direction I laid out in 2020, in an article called The Next Decade in AI, in which neurosymbolic AI is just the *starting point* in a longer journey.”
Our reading: To get trustworthy AI, the field should pursue knowledge-, reasoning- and world-model driven approaches beyond neurosymbolic AI, as current AI is an unpredictable jagged mess.
No horizon
Qualifier: to get trustworthy AI
Assessment: UnresolvedSaid
Forecast
“The first part has already come to pass. In time, other three will, too.”
Our reading: The other three parts of Marcus's 2020 agenda (knowledge, reasoning, world models) will eventually be adopted, as neurosymbolic AI already has been.
No deadline stated Evidence as of
Limitation: The terms are vague, and current industry uses of 'reasoning' and 'world models' may not match the paper's meaning.
Assessment: Can’t be checkedSaid
Causal claim
“Meanwhile, the implications for the allocation of capital are pretty massive: smartly adding in bits of symbolic AI can do a lot more than scaling alone, and even Anthropic has now discovered (though they haven’t acknowledged publicly) scaling is no longer the essence of innovation.”
Our reading: Smartly adding in bits of symbolic AI can do a lot more than scaling alone, Anthropic has discovered (without acknowledging it publicly) that scaling is no longer the essence of innovation, and the implications for capital allocation are pretty massive.
No horizon
Qualifier: smartly adding in bits of symbolic AI
Assessment: Can’t be checkedSaid
Held from this post (2)
These records did not pass every check, so nothing about them is published. Held is not a finding.