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AI today and tomorrow: Why enterprise data science is hard
In part one of a series on how to do enterprise AI right, host Travis Nixon chats with Charles Morris, author of The Data Science Lifecycle Process, on companies’ perceptions of their own AI journeys relative to their competitors, how messy and resource-intensive almost all use cases are, and why companies should start now.
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By Katrina MunsellIn part one of a series on how to do enterprise AI right, host Travis Nixon chats with Charles Morris, author of The Data Science Lifecycle Process, on companies’ perceptions of their own AI journeys relative to their competitors, how messy and resource-intensive almost all use cases are, and why companies should start now.