IA-MIT

5 Big Predictions for Artificial Intelligence in 2017



Last year was huge for advancements in artificial intelligence and machine learning. But 2017 may well deliver even more. Here are five key things to look forward to.

Positive reinforcement

AlphaGo’s historic victory against one of the best Go players of all time, Lee Sedol, was a landmark for the field of AI, and especially for the technique known as deep reinforcement learning.

Reinforcement learning takes inspiration from the ways that animals learn how certain behaviors tend to result in a positive or negative outcome. Using this approach, a computer can, say, figure out how to navigate a maze by trial and error and then associate the positive outcome—exiting the maze—with the actions that led up to it. This lets a machine learn without instruction or even explicit examples. The idea has been around for decades, but combining it with large (or deep) neural networks provides the power needed to make it work on really complex problems (like the game of Go). Through relentless experimentation, as well as analysis of previous games, AlphaGo figured out for itself how play the game at an expert level.
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Sami Mebazaa

Innovation Director chez Talan
Sami is eager to create a spirit of innovation in the Talan community - including consultants, clients and other stakeholders. In this mission, Sami has worked as the Director of Innovation at Talan since 2010. He strongly believes that the problems we encounter on a daily basis are the source of inspiration for innovation.

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