[Studyboard] We are very late. Too late? B.
Bruno Buchberger
buchberger.bruno at gmail.com
Sat Apr 11 18:36:02 CEST 2026
---------- Forwarded message ---------
From: Gary Marcus from Marcus on AI <garymarcus at substack.com>
Date: Sat, Apr 11, 2026 at 6:20 PM
Subject: The biggest advance in AI since the LLM
To: <buchberger.bruno at gmail.com>
Why Claude Code changes everything
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The biggest advance in AI since the LLM
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Claude Code changes everything
Gary Marcus <https://substack.com/@garymarcus>
Apr 11
<https://substack.com/@garymarcus>
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<https://substack.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.QtcFuunnR6Bs7ZnsMR2LO6OIcTyyt9g45G5Q7bTe_dY?&utm_source=substack&utm_medium=email>
READ IN APP
<https://open.substack.com/pub/garymarcus/p/the-biggest-advance-in-ai-since-the?utm_source=email&redirect=app-store&utm_campaign=email-read-in-app>
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Even
Grok knows that neurosymbolic hybrid power is the future
Claude Code
<https://substack.com/redirect/e71fefbe-6093-4a89-897b-2576eab07955?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>,
an impressive and possibly game-changing “coding agent” for programmers to
write code faster is the single biggest advance in AI since the LLM.
And the thing is, Claude Code is NOT a pure LLM. And it’s not pure deep
learning. Not even close.
That changes everything.
The source code leak
<https://substack.com/redirect/88eeffc2-a057-4a00-bb86-f792f4a29bb9?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>
proves it. Tucked away at its center is a 3,167 line kernel called
<https://substack.com/redirect/1e665d7c-f5f9-4fdb-8925-2775feb32a71?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>*print.ts
<https://substack.com/redirect/1e665d7c-f5f9-4fdb-8925-2775feb32a71?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>*
.
*print.ts* is a pattern matching. And pattern matching is supposed to be
the *strength* of LLMs.
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.
Instead, the way Anthropic built that kernel is straight out of classical
symbolic AI. For example, it’s in large part a big IF-THEN conditional,
with 486 branch points and 12 levels of nesting — all inside a
deterministic, symbolic loop that the real godfathers of AI, people like
John McCarthy and Marvin Minsky and Herb Simon, would have instantly
recognized.¹
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.
That’s right, the biggest advance since the LLM is neurosymbolic
<https://substack.com/redirect/0536f294-ae0e-4ce1-b196-fcfda8792551?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>.
AlphaFold, AlphaEvolve, AlphaProof, and AlphaGeometry are all
neurosymbolic, too; so is Code Interpreter; when you are calling code, you
are asking symbolic AI to do an important part of the work
<https://open.substack.com/pub/garymarcus/p/how-o3-and-grok-4-accidentally-vindicated?r=8tdk6&utm_medium=ios>
.
Claude Code isn’t better because of scaling. It’s better because it is
neurosymbolic
<https://substack.com/redirect/0536f294-ae0e-4ce1-b196-fcfda8792551?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>.
Anthropic accepted the importance of using classical AI techniques
alongside neural networks — precisely the marriage I have spent my career
advocating
<https://substack.com/redirect/4023e1a8-1594-4ba1-91b3-356357ebc3e2?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>.
It’s both massive vindication for me personally (see my 2019 debate with
Yoshua Bengio
<https://substack.com/redirect/12c84519-6a14-42e1-88a9-df1edcb379da?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>
for context, or my 2001 book, The Algebraic Mind
<https://substack.com/redirect/4023e1a8-1594-4ba1-91b3-356357ebc3e2?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>),
and for the hundreds of other researchers who have stood by neurosymbolic AI
<https://substack.com/redirect/f17ddb48-f247-4194-bd69-8eb1dd552207?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>
even when prominent people like Geoff Hinton wrongly disparaged us
<https://substack.com/redirect/ca64a092-3f5d-4824-acba-5b4ac7f770d9?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>
for years.
Still, Claude Code ain’t perfect, or even close.
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
<https://substack.com/redirect/cb9f4689-46c9-4a8e-a5d6-912a1039c602?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>,
in which neurosymbolic AI is just the *starting point* in a longer journey.
Read that article
<https://substack.com/redirect/cb9f4689-46c9-4a8e-a5d6-912a1039c602?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>
if you want to know what else we need to do next. The first part has
already come to pass. In time, other three will, too.
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.
The paradigm has changed.
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P.s. for a good recent review
<https://substack.com/redirect/0536f294-ae0e-4ce1-b196-fcfda8792551?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>
of neurosymbolic AI, read this
<https://substack.com/redirect/0536f294-ae0e-4ce1-b196-fcfda8792551?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>:
<https://substack.com/redirect/0c6d16f9-9f10-469d-8662-8825512b6cd5?j=eyJ1IjoiMjYweWhzIn0.m1tNzOVhaSv9i9EblceBSry3VETBUwU7ZHYTCJO5nD4>
1
Claude Code is plainly neurosymbolic but the symbolic code part is a mess;
as Ernie Davis and I argued in *Rebooting AI* in 2019, we also need major
advances in software engineering. But that’s a story for another day.
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Restack
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Bruno Buchberger
Dr.phil. Dr.h.c.mult., Member of the Academy of Europe
Professor of Computer Mathematics
Founder of RISC, Softwarepark Hagenberg and FH Hagenberg
buchberger.bruno at gmail.com
++ 43 664 42 11 646
www.brunobuchberger.com
Research Institute for Symbolic Computation (RISC)
Johannes Kepler University (JKU), Schloss Hagenberg, A4236 Hagenberg,
Austria
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