In CIO Today. Interesting look at current state of human to machine advisory communications. Much I would like to learn from the comparison. What's best in understanding and Semantics? Or is it really more about an adaptable and dynamic knowledge graph to anticipate your current context? How is risk of error being included in the correctness of an error, and how is that being communicated to the questioner? A good starting point for many advisory systems is search.
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