Continuing in the line of publications of recent days, today I will talk to you about AI, that is, about Artificial Intelligence and some other related terms, since it turns out that in this matter of AI, there is already a whole terminology and philosophy about it. We cannot apply it to our daily lives (at least when we come to cifnº1 to study), but who knows, one day…
With the arrival of increasingly surprising technology, our devices are becoming much smarter. Depending on where you live, you may have seen self-driving vehicles testing around your city. You may have interacted with a chatbot if you’ve used the online help feature when placing an order.
An article published by Times Square Chronicles explains each of the terms to get a better idea of ​​what it means: Artificial Intelligence, Machine Learning and Deep Learning and how they are connected and if they are different, it is necessary to know them in more detail. :
ARTIFICIAL INTELLIGENCE
Artificial intelligence, or AI, began in 1956 when a group of scientists came up with the term at the Dartmouth Lectures. Researchers dreamed of a world where computers would have the same characteristics as human intelligence and think like us. While we’re not there yet, we have a number of technologies that certainly do a decent job of performing a specific task as well or better than we can. Great examples are facial recognition on Facebook, which will let you return to your account if you’re locked out, virtual personal assistants like Siri, and websites that suggest purchasing items based on past purchases.
MACHINE LEARNING
Machine learning takes the concept of AI and expands it a little further. While AI is based on computer programming, machine learning involves using complex algorithms to analyze a large amount of data, pick up patterns, and then make a prediction, all without having to program the device in advance. A great example of machine learning is when it is used to identify certain items. If a device capable of machine learning incorrectly says that a tomato is a pomegranate, machine learning will allow it to recognize patterns to improve over time, learn from past mistakes, and identify the fruit correctly, as a human would. Besides, machine learning can be found in wearable devices that track health. This can allow the creation of realistic and user-specific fitness goals.
DEEP LEARNING
Just as machine learning is a subset of AI, deep learning is a subset of machine learning. Deep learning is a specific class of machine learning algorithms that use complex neural networks to take the idea of ​​computer intelligence to a whole new level. Deep learning involves taking an enormous amount of data and computing to allow the computer or other device to mimic the deep neural networks we have in our brains. These allow us to classify data and find connections between them. The more data a device has, the more accurately it can predict what things are. Going back to our tomato/pomegranate example, while machine learning can determine the difference between the two types of fruit,
While artificial intelligence, machine learning, and deep learning have definite differences, they also share a common trait: helping machines work smarter and learn more about their users.
