Trumpy

Embedded AI algorithms might sound complicated, but they're just a bit different from the AI you might know from general-purpose computers. These differences come from the unique needs and limitations of embedded systems, like those in your smartphone or a smart fridge. Let's explore these differences and see how they shape the way we design and use AI in these cool devices! #### 1. Working with Limited Resources **Memory and Storage:**    Embedded systems usually don't have a lot of memory or storage. Think of them like tiny apartments compared to big houses (general-purpose computers). So, when we write algorithms for them, we need to make sure they don't take up too much space. It's all about being efficient! **Processing Power:**   These devices often have less powerful processors. It's like comparing a bike to a car; you can't go as fast, but you can still get where you're going. Our algorithms need to be lightweight and quick so they can run smooth