Research in Artificial Intelligence has seen dramatic growth over the last few years, and the trajectory is only aiming higher for this industry. Interest has grown in data-driven AI and machine learning development, all due to better computer technology. With applications in almost every industry, the use of different types of AI computer algorithms is only on the rise. Research shows that in 2020 the AI market was at $51.08 billion and is estimated to go up to $641.30 billion at a CAGR of 36.1% by 2028. AI is already implemented in applications used daily by people, be it health, law, transport, finance, or any other.

AI which stands for artificial intelligence, is the result of applying cognitive science techniques to artificially create something that performs tasks that only humans can perform, like reasoning, natural communication, and problem-solving. There are different types of AI systems. Some systems are designed to simulate human intelligence, while others are designed to complement or enhance human intelligence. AI systems can be categorized by their level of capability, which includes narrow AI and general AI. Narrow AI is an AI system that is trained and programmed to perform a specific task.

Cortana (Jen Taylor) is one of the first characters that comes to mind when you think of the Halo universe. With a live-action Halo series on the way on Paramount, we thought a guide to Cortana (without giving too much away for those who haven't made their way through all the games) was in order. Cortana serves as a guide and ally to the player throughout Halo gameplay, and in that sense and many others, she is essential to the Halo experience. Her mannerisms as an AI make for a sort of dry humor that makes her stand out among other recurring characters in the game. It will be interesting to see how this character, who fits so easily into the video game format, will be adapted to a live-action television series.

My grandpa recently discovered that I've been writing medium articles. After reading a few that I wrote about AI, he sent me a text asking for me to write an article explaining it to "seniors" like him. This is my best attempt at that. Artificial Intelligence (AI) is a phrase used by computer scientists to describe programs that can do things that require applying knowledge. But isn't any computer program'applying' the knowledge given to it in its own programming?

There are many great articles about Artificial Intelligence (AI) and its benefits for business and society. However, many of these articles are too technical for the average reader. I love reading about AI, but I sometimes think to myself, 'Gee, I wish the author had explained this in simple English.' I will try and explain AI and its related technologies in simple terms, using real-life examples, as though I were talking to someone at a party. Your colleagues or your (close) friends may tolerate your endless and complex ramblings, but I guarantee you that people at parties are far less forgiving.

There are many great articles about Artificial Intelligence (AI) and its benefits for business and society. However, many of these articles are too technical for the average reader. I love reading about AI, but I sometimes think to myself, 'Gee, I wish the author had explained this in simple English.' I will try and explain AI and its related technologies in simple terms, using real-life examples, as though I were talking to someone at a party. Your colleagues or your (close) friends may tolerate your endless and complex ramblings, but I guarantee you that people at parties are far less forgiving.

The field of artificial intelligence (AI) is fast-moving, and new breakthroughs are regularly made. One of the more recent terms rising to prominence is Generative Adversarial Network (GAN) – but what does it mean? The principle behind the GAN was first proposed in 2014, and at its most basic level, it describes a system that pits two AI systems (neural networks) against each other to improve the quality of their results. To understand how they work, imagine a blind forger trying to create copies of paintings by great masters. To start with, he has no idea what a painting should look like – but he happens to have a friend who has a photographic memory of every masterpiece that's ever been painted.

The field of artificial intelligence (AI) is fast-moving, and new breakthroughs are regularly made. One of the more recent terms rising to prominence is Generative Adversarial Network (GAN) – but what does it mean? Artificial Intelligence Explained: What Are Generative Adversarial Networks (GANs)? The principle behind the GAN was first proposed in 2014, and at its most basic level, it describes a system that pits two AI systems (neural networks) against each other to improve the quality of their results. To understand how they work, imagine a blind forger trying to create copies of paintings by great masters.

The field of artificial intelligence (AI) is fast-moving, and new breakthroughs are regularly made. One of the more recent terms rising to prominence is Generative Adversarial Network (GAN) – but what does it mean? Artificial Intelligence Explained: What Are Generative Adversarial Networks (GANs)? The principle behind the GAN was first proposed in 2014, and at its most basic level, it describes a system that pits two AI systems (neural networks) against each other to improve the quality of their results. To understand how they work, imagine a blind forger trying to create copies of paintings by great masters.

This playlist focuses on showing cutting edge machine learning and artificial intelligence research with a clear connection to business use and easy to understand for a fairly technical business audience. Key about all of these fascinating research presentation is to understand that today there is no such thing as "artificial intelligence." This is not to say that the concepts, algorithms, and models we are exploring today are not tremendously valuable, but to effectively find and evaluate use cases, we need to be clear about what AI can do and, as importantly, what it cannot do. This playlist focuses on showing cutting edge machine learning and artificial intelligence research with a clear connection to business use and easy to understand for a fairly technical business audience.