This dismissal of AI skepticism is egregiously wrong, or at least deeply selective, @jeffclune. Was I wrong that pure LLMs would always be v…

This dismissal of AI skepticism is egregiously wrong, or at least deeply selective, @jeffclune. Was I wrong that pure LLMs would always be vulnerable to hallucinations? Was I wrong that pure LLMs would need to be supplemented with (neuro)symbolic methods that explicitly manipulated symbols? [Harnesses, tools, code interpreters, loops etc are exactly that.] Was I wrong that LLM providers would struggle to make profits because they would lack a moat? Was I wrong that LLMs would be difficult to align and “like bulls in a china shop, powerful but reckless and hard to control”? No, I was not. Those who dismissed those claims were. In my life, those skeptical of AI progress and AI predictions have consistently been wrong, and those predicting things many mock as sci-fi or crazy have almost all been right, with the main errors being timing. This is true more generally for tech progress. Be wary trusting your…

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• update @thestalwart found more recent models less vulnerable. would be good to do a broad study of this.
• If I had a nickel for every snide but underinformed person who failed to distinguish between pure LLMs and neurosymbolic AI I would be a bil…
• To folks who claim I am always wrong, I have a few questions: Was I wrong that these systems would continue to hallucinate and be untrustwor…
• people with advanced degrees who can’t distinguish between pure LLMs (which is what I critiqued in 2022) and LLMs enhanced with neurosymboli…

Source: Gary Marcus (X) | 2026-09-07