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Making Predictions About the Predictive Tech of ML

Making Predictions About the Predictive Tech of ML

Episode 110

AI today is getting better at learning. In fact, learning is what differentiates what we call AI from advanced analytics. Machine learning algorithms minimize an error function by autonomously and iteratively adjusting their model variables. But what’s next for AI and machine learning? In this episode of the IoT business show I speak with James Canton, who in a meta way makes predictions about this prediction technology.

In this episode of the IoT business show I speak with James Canton, who in a meta way makes predictions about this prediction technology.

James is a futurist, business advisor and author. He is CEO and Chairman of the Institute for Global Futures and wrote the recent book, Future Smart. For over 25 years he has been speaking and advising clients on how to harness innovations to better compete.

One way to think about the relationship between statistics, analytics and AI is as an algorithmic evolution.  Just like analytics evolved to make statistics more valuable, AI is now making analytics more valuable.  The current state of the AI art today is machine learning – analytical algorithms wrapped with logic that naturally select to learn a narrow skill.  When looking at the long game, what scares experts, pundits and the general population alike is the evolutionary factors will naturally select to develop a type of intelligence not aligned with human interests.  In a way, trying to predict what’s next for AI is predicting what these algorithms will “learn” next.  What that is, is uncertain but what we do know is it’s a long way to singularity or the unintended consequences described in the paperclip maximizer thought experiment.

Here’s What We’ll Cover in this Episode

  • How hyper connectivity will change AI and IoT.
  • AI teaching other AI.
  • High velocity cognitive decision making.
  • The secret AI wars raging today to establish the new world economic world order.
  • The definition of the AI economy and where the money is being spent today.
  • The four steps to resetting your AI thinking.

Mentioned in this Episode and Other Useful Links

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What’s next in AI after machine learning?

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