Symbolic AI: The key to the thinking machine
Symbolic artificial intelligence Wikipedia In symbolic AI, discourse representation theory and first-order logic have been used to represent sentence meanings. Latent semantic analysis (LSA) and explicit semantic analysis also provided vector representations of documents. In the latter case, vector components are interpretable as concepts named by Wikipedia articles. For example, language models learn to imitate existing conventions [3], and multi-modal models learn about conventions of denotation, so that they can e.g. produce an image from a description [26]. Proponents of neuro-symbolic models often emphasize these models’ ability to rapidly learn a new concept, from a definition or a few examples [e.g. Horn clause logic is moreRead More →
