If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
As populations age, more and more people are asking how best to organise care for the elderly in future. Trained staff will be important, as will technology and innovation – which may include artificial intelligence (AI). Some people get fearful when talk turns to AI, a topic riddled with misconceptions. At the end of the day, what it means is the attempt to map human decisions using computers, says Andreas Hein, an expert in assistance systems at Oldenburg University in Germany. In a medicine or health care setting, that means providing doctors and nurses suggestions that a computer has created based on data.
Despite its huge empirical success, deep learning still preserves many features of alchemy [Rahimi, 2017]: progress in this field is obtained mainly by trial and error, and our intuition about how do neural networks actually work often misleads us. Alchemy, in order to become usual chemistry, needs a theoretical ground. For now, a solid theoretical ground for deep learning is lacking, however, fortunately, many pieces of theory appeared from different directions during several past years. The purpose of this essay is not to provide a comprehensive review, but to draw connections between some works on this topic. The list of works mentioned here is by no means representative, or, all the more so, complete. Since the theory of deep learning is lacking, some features of neural networks learning seem "mysterious". We emphasize two mysteries of deep learning: 1. Generalization mystery. It is very common for contemporary neural networks to have many more parameters than the number of training examples at hand.
Last week Obsidian dangled the smallest scraps of a new project: Tyranny, a new isometric CRPG built in the Pillars of Eternity engine. A world where the battle between good and evil already took place, and evil won. Here's the trailer again, in case you need a refresher: Pretty light on the details, eh? Luckily we got a half-hour demo of the project at GDC. The key takeaway: Tyranny might share the same engine as Pillars of Eternity, but that's about all. This is a wild project.