Gary Marcus
Cognitive scientist and long-standing critic of deep learning's claims; writes Marcus on AI and wrote Rebooting AI.
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Where they publish
Newsletter Marcus on AI His newsletter on what large language models can and cannot do. Has a feed.
Recent
- Top three ways Dario Amodei has blown his credibility in seven days 19 Sept 2026 Actions speak louder than words
- The real reason Trump is standing behind AI — and the latest example of why that might turn out to be a bad idea 18 Sept 2026 More disconcerting updates 😱
- Wake up, people. What we should actually fear, near term, is not so much rogue superintelligence as unleashed agentic AI causing hacking the internet at scale. 18 Sept 2026 Rome is burning and people are fantasizing about Skynet.
Show 17 more
- Liability, regulation, and AI’s new false dichotomy 17 Sept 2026
- Sam Altman says trust me; Jensen Huang says everything is going to be fine; Bernie Sanders says AI is more dangerous than nukes 16 Sept 2026 Here’s who we should be listening to instead
- Translating Sam 15 Sept 2026 Wondering what Sam’s endorsement of Dario is really about?
- BREAKING: Secret US AI evaluation framework has been partly revealed 15 Sept 2026
- President Trump’s Date With Destiny? 14 Sept 2026 September 24, if played right, could change everything
- Two cheers (out of three) for Dario Amodei 13 Sept 2026 A partial endorsement of his essay “We Must Pace the Frontier”
- Could rogue agent swarms take over the entire internet in the next six months? 12 Sept 2026 Dario Amodei seems to think so.
- No, Anderson Cooper, AI is not going to kill all humans by 2030 10 Sept 2026 AI is already causing harms, there are are many real risks, but constant focus on absurd end-of-the-world fantasies has made the situation worse
- BREAKING: Two rays of hope 10 Sept 2026 Pushing for transparency
- The Case for Boycotting Generative AI 9 Sept 2026 I believe the time has come
- Two dire warnings, one from Terence Tao, the other from someone who just quit Anthropic 9 Sept 2026 Lots to consider
- OpenAI’s Egregious Pattern of Misconduct 8 Sept 2026 Nine troubling new reports in seven days
- Sad to see Jensen Huang claim that AGI has arrived, with no evidence and no definitions 6 Sept 2026 Declaring victory without a definition simply muddies the waters
- Pause OpenAI, now 4 Sept 2026 Quite simply, they can no longer be trusted.
- Hot take on GPT-6 Astra 3 Sept 2026 An impressive system that can (to some unknown extent) build symbolic world models
- The new Sanders-Casar Ban Artificial Superintelligence Act – and why I oppose it 3 Sept 2026 There’s a lot to like here, but the proposal clearly goes too far.
- Elon Musk is on a prediction rampage, and most of the media can’t seem to figure out what to do about it. 2 Sept 2026 The bad news is that he’s not alone
Link verified 20 Sept 2026. Recent items update automatically from the channel.
Beliefs
Korrents What they believe 10 beliefs — each backed by an exact quote.
Each is a — compiled by korrents.com, not by them: the one-line wordings are korrents', the quotes are theirs.
Recent
Almost every major figure in AI has now arrived at the critique of large language models he began making in 2019.
But one by one, almost every major thinker in AI has come around to the critique of LLMs that I began presenting in 2019.
Game over for pure LLMs. Even Turing Award Winner Rich Sutton has gotten off the bus. Said 26 Sept 2025
GPT-5 was an ordinary incremental advance, and the gap between what was promised for it and what shipped is the story of the field.
People had grown to expect miracles, but GPT-5 is just the latest incremental advance.
GPT-5: Overdue, overhyped and underwhelming. And that’s not the worst of it. Said 9 Aug 2025
The LLM line of research will reach a capability plateau.
But this particular approach has limits that are clearer by the day.
A knockout blow for LLMs? Said 7 Jun 2025
Show 7 more
Anyone who thinks large language models are a direct route to transformative AGI is kidding themselves.
But anybody who thinks LLMs are a direct route to the sort AGI that could fundamentally transform society for the good is kidding themselves.
A knockout blow for LLMs? Said 7 Jun 2025
There is no route to AI alignment or safety that goes around reliability: a system that cannot reliably follow a known algorithm cannot be made safe.
And good luck getting to “alignment” or “safety” without reliabilty.
A knockout blow for LLMs? Said 7 Jun 2025
A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted.
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.
A knockout blow for LLMs? Said 7 Jun 2025
Success on the easy version of a task is evidence of nothing, because it seduces you into believing the model found a general solution when it did not.
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.
A knockout blow for LLMs? Said 7 Jun 2025
AGI worth the name would combine human adaptiveness with machine reliability, not reproduce human performance including human failures.
The vision of AGI I have always had is one that combines the strengths of humans with the strength of machines, overcoming the weaknesses of humans.
A knockout blow for LLMs? Said 7 Jun 2025
Scaling the 2019-2023 recipe — same architecture, bigger model, more data — is not enough; further progress depends on new architectural ideas.
Neurosymbolic AI — combining such machinery with neural networks – is likely a necessary condition for going forward.
LLMs don’t do formal reasoning - and that is a HUGE problem Said 11 Oct 2024
Large language models do not reason formally: their performance collapses as a problem is made bigger, in the way a calculator's never does.
Another manifestation of the lack of sufficiently abstract, formal reasoning in LLMs is the way in which performance often fall apart as problems are made bigger.
LLMs don’t do formal reasoning - and that is a HUGE problem Said 11 Oct 2024
Beliefs others hold too
Scaling the 2019-2023 recipe — same architecture, bigger model, more data — is not enough; further progress depends on new architectural ideas. 2 hold this
Neurosymbolic AI — combining such machinery with neural networks – is likely a necessary condition for going forward.
LLMs don’t do formal reasoning - and that is a HUGE problem Said 11 Oct 2024
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