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Thursday, December 28, 2017

AI, machine learning, and deep learning: What they are and how they differ | TechGenix - Big Data & Machine Learning

Photo: Rahul Sharma
"AI, machine learning, and deep learning are terms often used interchangeably. But it’s crucial to understand the nuances before you can harness their power" says Rahul Sharma, accomplished copywriter/blogger. 
Photo: TechGenix

Artificial intelligence is no longer the stuff of science fiction flicks. It’s a reality, and chances are you’re interacting and being impacted by AI technology-powered applications every day. AI seems to be the phrase on everybody’s lips these days, right from makers of autonomous trucks that can travel thousands of miles without requiring human intervention to truck drivers who fear they’ll be out of a job if these AI-powered trucks make it to the roads. In 2016, Google’s DeepMind AlphaGo program competed against Lee Se-dol, South Korean master of the board game Go, the program emerged victorious. Media coverage used terms such as AI, machine learning, and deep learning interchangeably as if they all meant the same thing. The truth is, they don’t. Of course, all three technologies were responsible for AlphaGo’s victory in their own way, but they are all different. And probably if it were an AI-powered press release writer program, this mistake might not have happened!

To make sure that you can make sense of the latest revolutions from the world of technology, it’s crucial that you understand the nuances that separate AI, machine learning, and deep learning. So read on.

AI: Technology that makes machines behave like intelligent humans
Of AI, machine learning, and deep learning, AI is the broadest set that encompasses technologies related to advanced computer intelligence. AI has its roots back in 1956, when the Dartmouth Artificial Intelligence Conference practically coined the term with a generally accepted meaning. The basic idea expressed in the conference was that every aspect of human intelligence could be described in such a precise manner that the behavior could be simulated using computer programming.

Three stages or categories of AI  
Narrow artificial intelligence: This is the term used to refer to programs, algorithms, and technologies that can simulate human-intelligence level behavior, but only for a specific task. For instance, chess-playing robots such as IBM’s DeepBlue are an example of narrow artificial intelligence, which is task specific.

Artificial general intelligence: This term refers to a level of computer intelligence that is at par with human intelligence, across a range of tasks. We’re still far from achieving artificial general intelligence in computers, even in the most high-tech laboratories.

Super-intelligent AI: This is a look into the future — the level of artificial intelligence that encompasses scientific thinking, creative outlooks, and general wisdom to the extent that the machine possessing it could supersede humans as the most intelligent “beings” on the face of Earth.

Source: TechGenix (blog