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Chile – Semantics, Deep Learning, and the Transformation of Business

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Steve Omohundro, recognised Artificial Intelligence scholar, explains why semantics matter when talking about AI, what the deep learning trend is, and how business is going to be transformed by it.

McKinsey predicts that AI and robotics will create $50 trillion of value over the next 10 years. Many predict that the recent technology of “deep learning” will be a big part of the transformation. Over 250 deep learning startup companies have attracted more than $1 billion of venture investment in the past year. Deep learning systems have recently broken records in speech recognition, image recognition, image captioning, translation, drug discovery and other tasks. Why is this happening now and how is it likely to play out? We review the development of AI and the pendulum swings between the “neats” and the “scruffies”. We describe traditional approaches to semantics through logics and grammars and the new deep learning vector semantics. We relate it to Roger Shepard’s cognitive geometry and the structure of biological networks. We also describe limitations of deep learning for safety and regulation. We show how it fits into the rational agent framework and discuss what the next steps may be.