Glossary

Algorithm

An algorithm is a set of rules or step-by-step instructions written by a programmer to be followed by a computer in order to solve a problem or perform an action. Algorithms are the basis on which computer science is founded. They not only tell a computer what to do, but also how to do it.

Digital Footprint

Your digital footprint is the trace you leave whenever you use a mobile device, laptop, or any other device to access information on the Internet. It is the information about you that exists online as a result of your online activity. For example, your digital footprint could consist of the comments you leave on an Instagram post, your app usage, or the brand of shorts you bought.

Machine Learning

Machine learning is what happens when a computer teaches itself something new. Companies that use artificial intelligence tools to collect data — social media corporations, for example — need ways to find patterns and reach conclusions about that data. Machine learning algorithms are used to sift through enormous quantities of data and then make decisions based on what they find. Netflix recommendations and Spotify playlists are generated using machine learning. The algorithms analyze your watching and listing habits and then make educated guesses about what else you might like. The more guesses it makes, the better it gets at making them.

Data Science

The field of data science is dedicated to studying, analyzing, and extracting important information out of large amounts of data. Data science is intrinsically related to machine learning and AI, since AI algorithms need large amounts of data to be any good, which is why many machine learning engineers often play the role of data scientists as well.
 
Have you ever thought about the amount of data your browsing habits deposit daily on the Internet? The average Internet user provides a constant stream of information to companies such as Google, Twitter, Facebook, and others. Every post, comment, interaction, and relationship you establish online is logged, giving these service providers huge quantities of useful information about you. According to research done by Domo, Internet users generate about 1.7MB of data for every second they are online.
 
We are living at the peak of the information era. There is way more information available to us than we know what to do with, which is why a huge part of today’s research is devoted to data science
 
Data science is undoubtedly one of the most powerful tools scientists have today for understanding the amount of information generated by our society.

Neural Network

In short, a neural network is the use of millions of artificial “cells” that learn and behave like the neurons in our brains. We have billions of neurons in our heads that transmit nerve impulses. Neural networks are inspired by these human neurons. Similar to what happens in the human brain, a neural network receives information and processes it. But unlike in a human brain, a neural network then produces an output. After a while, a neural network begins to change itself in order to make fewer mistakes. For example, the more we shop for a certain type of item, the more the machine will predict what we may want to purchase based on what the neural network has learned.

A neural network processes fairly small amounts of data at a time, then produces a summary of that data. This technology helps with advanced online searches, personalized shopping experiences, customized marketing, and so much more. Little did we know that we interact with neural networks every single day. To get the ins and outs of a neural network, read more here.

Deep Learning

Deep learning can be thought of as any artificial intelligence model with many layers — those layers are where we get ‘deep’ from. But more broadly, you can think of deep learning as the process of increasing the size of our AI models in a specific and clever way, giving us more powerful and comprehensive AI. Deep learning is a powerful tool connected to the increase in the current availability of data, and it is designed specifically to benefit from that.

Bot

A bot — short for robot — is any algorithm that repeatedly tries to mimic a human action. Bots are already common; you may have interacted with one recently. Social media platforms such as Twitter and Facebook are filled with automated accounts devoted to doing certain tasks. One famous example is Archillect, an AI devoted to discovering and sharing stimulating images and visual content on Twitter. By analyzing its followers' feedback, Archillect learns which images are more engaging, and then proceeds to improve itself in order to post better content.
 
AI has changed the power and extent to which bots can operate. AI-driven bots today do many different tasks and are often mistaken for humans. Look at news articles for an example. Believe it or not, a large percentage of news articles are currently written by bots. Machine learning models are specifically trained to write coherent and quality texts by learning from the vast amount of data that exists regarding online articles. Newspapers like the Washington Post successfully started using AI bots to write articles, a trend that is spreading quickly throughout mainstream media.
 
But such technology isn’t without its complications. Improvements in bot technology have also resulted in serious crises. The 2016 U.S. election was influenced by “fake news” regarding presidential candidates. A large number of those false news items were written and spread by skilled bots powered by AI algorithms.
 
Today, bots are a highly accessible and powerful tool for anyone interested in replicating human tasks automatically and more efficiently.

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