What do ‘neural network,’ ‘machine learning,’ and ‘deep learning’ actually mean?


Artificial intelligence seems to have become ubiquitous in the technology industry. AIs, we’re told, are replying to our emails on Gmail, learning how to drive our cars, and sorting our holiday photos. Mark Zuckerberg is even building one to help out around the house. The problem is that the concept of ‘artificial intelligence’ is way too potent for its own good, conjuring images of supercomputers that operate spaceships, rather than particularly clever spam filters. The next thing you know, people are worrying about exactly how and when AI is going to doom humanity.

Tech companies have partly encouraged this elision of artificial intelligence and sci-fi AI (especially with their anthropomorphic digital assistants), but it’s not useful when it comes to understanding what our computers are doing that’s new and exciting. With that in mind, this primer aims to explain some of the most commonly used terms in consumer applications of artificial intelligence — as well as looking at the limitations of our current technology, and why we shouldn’t be worrying about the robot uprising just yet.

Read the source article at The Verge