Every post I read that says it is going to explain the relationship between artificial intelligence, machine learning, and deep learning goes way off the deep end into extremely technical terms and huge amounts of detail.
So I decided to take a crack at a simple 2-minute explainer. Here it is, in one pic:
And … a couple of written details:
Replicating part, all, or more than human intelligence.
Enabling computers to learn, usually “on their own,” often with big datasets.
Building multiple layers of abstractions on datasets to construct higher-level meaning.
Sometimes, of course, it’s easier to understand by walking through an example.
AI might be a system for recognizing dogs in pictures. Machine learning would feed the system hundreds of thousands of pictures of dogs. Deep learning would help the system recognize patterns (shapes that form a more complex shape that we call legs, multiple instantiations of legs on a creature, four legs is one signifier that you might be looking at a dog).
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This is certainly simplified and almost certainly oversimplified. But hopefully it helps any who have been wondering.