Understanding the potential of Artificial Intelligence

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An interesting interview with Daniel Hulme, CEO of the AI solutions startup Satalia, offers other chief executives a primer on the technology that will shape the future of work and business. Published on strategy-business.com by Euan Cameron and Deborah Unger.

Lately, Hulme has spent a good portion of his time explaining the ins and outs of artificial intelligence to other CEOs. He sees a big information gap at the top of most companies — yet this is where technology investment decisions are made.

There are two definitions of AI, and the more popular one is the weakest. This first definition [concerns] machines that can do tasks that were traditionally in the realm of human beings.

Humans are the most intelligent things we know in the universe, so when we start to see machines do tasks once constrained to the human domain, then we assume that is intelligence.

But the key word for me in the definition of goal-directed adaptive behavior is adaptive. If your computer system is not making a decision and then learning whether that decision was good or bad and adapting its own internal model of the world, I would argue that it’s not true AI.

A lot of people are saying, “Well, [with] these deep learning models, these data scientists will solve all our problems,” and actually, they won’t. As I said, machine learning, data science, and statistics are great at finding patterns in data.

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Tags big-data cloud data-science miscellaneous machine-learning