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Résumé : Here, we informally review the logical reasoning abilities of large language models, and how that seems to suggest that these models are neither deep thinkers nor an existential threat, in the sense of a rogue autonomous agent. Sample conversations are included to illustrate its shallowness. We conclude by arguing for the need to revert to well-established areas that unify logical reasoning and learning, such as statistical relational learning and neuro-symbolic AI, which enable frameworks for clear behavior specification. We also discuss the advantages and limitations of these proposed frameworks, and briefly consider how hybrid architectures that combine neural and symbolic approaches may offer a more productive path forward.