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AI, ML and DL: Unlocking the Jargons

AI, ML and DL: Unlocking the Jargons

Artificial Intelligence, Machine Learning, and Deep Learning have made significant contributions to the modern world that we live in. Some of its applications that we use on a daily basis might have been inconceivable to mankind at some point. From healthcare to self-driving cars, everything seems possible with this trio. We are living in exciting times.

The goal of AI was to get computers to perform tasks that required intelligence. AI solved problems using many techniques, one of them was machine learning. When researchers found that there were certain problems that AI couldn’t fix, the solution was not to copy human behavior (which is what AI did) but copy the way humans think and learned something.

Humans consume a lot of data and learn from it, which is exactly what ML does. The ML algorithm is fed data which it processes to come up with a solution. Even though the ML algorithms became smarter, there were certain things that were still hard for it. The next step was to copy how the human brain works- neural networks. That’s what Deep Learning does, try to copy the human brain in all its glory. Although we have not been able to mimic the human brain fully yet, we are powering through and solving difficult problems.

Deep Learning is a subset of Machine Learning, which is a subset of AI.

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Lini Susan John

Chatty & gregarious, you can find her with her baby plants when not with her marketing team.