The benefits of any technology should be felt by all of us.
Pointing to exactly what counts as AI and where it is being used is a surprisingly hard thing to do. This is because many examples of AI aren’t about the creation of entirely new things. Instead, they are about adding AI to existing things. Adding AI can speed up a process, eliminate the need for humans to do something, or make a system more efficient.
One way to think of AI is as salt rather than its own food group
Hopefully the examples in the previous section have shown that AI isn’t just one thing. This is exactly why AI is so powerful: because it is a number of different technologies that can be incorporated into almost any digital space to make things work more efficiently.
AI is present in most of our everyday lives. It doesn’t look like the robots we see on TV— instead, it’s the name for a broad field with lots of applications that can take many forms. Let’s explore what AI in our everyday life looks like and identify what the potential impact of it can be.
We can’t talk about AI or machine learning without talking about algorithms. This is because algorithms are the basic building blocks of AI. In fact, algorithms are the building blocks of computer programs in general. But even more than that, they’re the building blocks of how many of us live our lives.
So far we’ve been talking about personal algorithms. But the main space where you are likely to hear about algorithms is in relation to computers. The programs that computers run are full of algorithms. Like the personal algorithms that humans use, these computational algorithms exist to solve problems or perform tasks.
AI and machine learning difference
When we talk about AI, sometimes we are actually talking about a field called “machine learning.” These two concepts are often grouped together because machine learning makes up part of the field of artificial intelligence. Just as every cat is an animal, but not every animal is a cat, every machine learning algorithm is an example of AI, even though not everything in AI is machine learning. But the real difference between the two comes down to the different algorithms that make them up, and what those algorithms try to do
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ONEZYPHER © LTD-2021: All rights reserved.