If you are (or were) confused on the various variations of Artificial Intelligence (AI) and what the differences are, here is a quick read on the basic differences. So, AI, AGI, ML & DL won’t just sound like some cool codes on social networks after you check these definitions. I know I just learned something new.
These are three terms that are heard all the time now, but often people still get confused about what each one really entails. Below is a quick rundown of each that will hopefully things out a little and give you a real insight as to what these interchangeable terms mean.
Artificial Intelligence, or AI for short, is the broadest way in which to describe computer intelligence. Back in1956 it was described as “Every aspect of learning or any other feature of intelligence can in principle is that a machine can be made to simulate it” at the Dartmouth Artificial Intelligence Conference. AI can come in various forms including game-playing computer programs and voice recognition systems.
To further break down the definition of AI it can be split into three subgroups: Narrow AI, artificial general intelligence (AGI), and superintelligent AI…
Machine learning (ML) is a subdivision of AI that involves machines deciphering data and learning for themselves. It’s used a lot throughout the businesses of today as is very efficient when used in areas such as speech, object, and facial recognition, translation, and other tasks…
That then leads us to Deep Learning, which is a subdivision of ML. It too makes use of certain ML techniques by tapping into neural networks that mimic a human’s decision making. The problem with deep learning is that it requires an enormous amount of data to train itself with which can often be very expensive….
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