#1 The grumpy guide to AI, machine learning and deep learning by anwenwilson 27.07.2017 15:56

In 1956 those super smart people - pioneers - wanted to create complex machines that had the same characteristics as human intelligence. Today, general AI as we know it (and if you have ever watched the Terminator movie, then that's it in a nutshell) is still a science fiction thing but may not be one day.

Today we can do the "Narrow AI": a concept of weak AI that means a machine can perform specific tasks as well, or better than, a human can. Apple's Siri, Amazon's Alexa, Faceless on Facebook etc. are great examples. Others exist in all parts of our daily life.

Machine Learning (ML): an approach to achieve artificial intelligence
Machine learning is the practice of using algorithms to parse data, learn from it and make a prediction about something in the world.

No more hand coding, lots of software routines to do specific instructions to achieve something, the machine is instead trained using the large amounts of data and algorithms to give it the ability to learn how to perform a task. Cool huh? ML is in your pitch. ML is in your pitch.

So this all comes about from different algorithmic approaches, clustering, inductive logic programming, decision tree learning and the list goes on. This was a very early AI crowds and none achieved the goal of general AI and even weak / narrow was pretty hard to achieve.

But the early adopters, those crossing the chasm, were not just wrong and it was just a case of time and the right learning algorithms.


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