6 areas of AI and machine learning to watch closely

6 areas of AI and machine learning to watch closely

by Nathan Benaich, Medium

Distilling a generally-accepted definition of what qualifies as artificial intelligence (AI) has become a revived topic of debate in recent times. Some have rebranded AI as “cognitive computing” or “machine intelligence”, while others incorrectly interchange AI with “machine learning”. This is in part because AI is not one technology. It is in fact a broad field constituted of many disciplines, ranging from robotics to machine learning. The ultimate goal of AI, most of us affirm, is to build machines capable of performing tasks and cognitive functions that are otherwise only within the scope of human intelligence. In order to get there, machines must be able to learn these capabilities automatically instead of having each of them be explicitly programmed end-to-end.

It’s amazing how much progress the field of AI has achieved over the last 10 years, ranging from self-driving cars to speech recognition and synthesis. Against this backdrop, AI has become a topic of conversation in more and more companies and households who have come to see AI as a technology that isn’t another 20 years away, but as something that is impacting their lives today. Indeed, the popular press reports on AI almost everyday and technology giants, one by one, articulate their significant long-term AI strategies. While several investors and incumbents are eager to understand how to capture value in this new world, the majority are still scratching their heads to figure out what this all means. Meanwhile, governments are grappling with the implications of automation in society.

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