Welcome on board! In this chapter, we’ll be taking a comprehensive tour of the edge AI world. We’ll define the key terms, learn what makes “edge AI” different from other AI, and explore some of the most important use cases. Our goal for this chapter is to answer these two important questions:
What is edge AI, anyway?
Why would I ever need it?
Defining Key Terms
Each area of technology has its own taxonomy of buzzwords, and edge AI is no different. In fact, the term edge AI is a union of two buzzwords, fused together into one mighty term. It’s often heard alongside its siblings, embedded machine learning and TinyML.
Before we move on, we better spend some time defining these terms and understanding what they mean. Since we’re dealing with compound buzzwords, let’s deal with the most fundamental parts first.
Embedded
What is “embedded”? Depending on your background, this may be the most familiar of all the terms we’re trying to describe. Embedded systems are the computers that control the electronics of all sorts of physical devices, from Bluetooth headphones to the engine control unit of a modern car. Embedded software is software that runs on them. Figure 1-1 shows a few places where embedded systems can be found.
Figure 1-1. Embedded systems are present in every part of our world, including the home and the workplace
Embedded ...
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