:PROPERTIES:
:CREATED:  [2026-05-11 Mon]
:ID:       4c65fdbb-a45c-4c71-ac29-6488e9271f4a
:END:
#+title: Marcus (2020): The Case Against Pure Deep Learning
#+filetags: :passepartout:architecture:

Gary Marcus's "The Next Decade in AI" argues that deep learning alone is "data hungry, shallow, brittle, and limited in its ability to generalize." The paper demonstrates GPT-2 failing at basic commonsense reasoning:

- "Yesterday I dropped my clothes off at the dry cleaners and have yet to pick them up. Where are my clothes?" → GPT-2: "at my mom's house."
- "There are six frogs on a log. Two leave, but three join. The number of frogs on the log is now" → GPT-2: "seventeen."

Marcus proposes four steps toward robust AI: hybrid architecture (combining neural and symbolic), large-scale knowledge (abstract and causal, not just statistical), reasoning (formal inference over structured representations), and cognitive models (frameworks for how entities relate). Passepartout implements all four: the perceive-reason-act pipeline is hybrid, the symbolic index is causal knowledge, Screamer + ACL2 provide reasoning, and the gate-bootstrapped ontology plus MOMo modules provide cognitive models.

Marcus's core claim — "we have no hope of achieving robust intelligence without first developing systems with deep understanding" — is the justification for Passepartout's entire neurosymbolic investment. The alternative is a system that works "on a good day" and fails unpredictably. The deterministic gate stack and Screamer admission gate are the engineering realization of Marcus's call for robustness.

Reference: Marcus, G. (2020). The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence. arXiv:2002.06177.