Machine Learning and the Future of Artificial Intelligence

Machine Learning and the Future of Artificial Intelligence

Machine Learning and the Future of Artificial Intelligence
The author recently completed a wonderful course in Machine Learning taught by Prof Andrew Ng of Stanford on Coursera.

Machine Learning, more popularly known as Artificial Intelligence or AI is not a new topic.

AI has been in the making for over 60 years. But it has started delivering creditable results in the last few years. The success of the driverless car has captured the popular imagination but progress in the areas of image recognition, natural language processing and anomaly detection is no less impressive and has applications across sectors.

One might argue that AI is part of the digital transformation that is sweeping the world in any case, so what is so special about it. Well there is a fundamental difference. Till this time computers were great for doing repetitive jobs quickly and reliably so they were deployed mostly for automation.

They replaced humans for mechanical tasks. But for the first time AI is allowing computers to take up tasks that involve thinking and learning. An AI machine is not limited by the imagination of its programmer. It can actually learn by itself and get better with experience at the task that it has been assigned.

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This is a paradigm shift that has serious implications for all of us. It has heightened fears of jobless growth on the one hand but holds out the promise of a better quality of life on the other. The lesson of history is quite clear. Progress of technology cannot be denied, but society must find ways to curtail the negative fallout as well.

To get a sense of where AI is today and the long journey still ahead, listen to this TED talk by Fei-Fei Li Director of Stanford’s Artificial Intelligence Lab. A heartening feature of current research in AI is that most of it is open source.

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