20 February, 2015
Myth Busting Artificial Intelligence
We’ve all been seeing hype and excitement around artificial intelligence, big data, machine learning and deep learning. There’s also a lot of confusion about what they really mean and what’s actually possible today. These terms are used arbitrarily and sometimes interchangeably, which further perpetuates confusion.
So, let’s break down these terms and offer some perspective.
Artificial Intelligence is a branch of computer science that deals with algorithms inspired by various facets of natural intelligence. It includes performing tasks that normally require human intelligence, such as visual perception, speech recognition, problem solving and language translation. Artificial intelligence can be seen in many every day products, from intelligent personal assistants in your smartphone to the X-box 360 Kinect camera, allowing you to interact with games through body movement. There are also well-known examples of AI that are more experimental, from the self-aware Super Mario to the widely discussed driverless car. Other less commonly discussed examples include the ability to sift through millions of images to pull together notable insights.
Big Data is an important part of AI and is defined as extremely large data sets that are so large they cannot be analyzed, searched or interpreted using traditional data processing methods. As a result, they have to be analyzed computationally to reveal patterns, trends, and associations. This computational analysis, for instance, has helped businesses improve customer experience and their bottom line by better understand human behavior and interactions. There are many retailers that now rely heavily on Big Data to help adjust pricing in near-real time for millions of items, based on demand and inventory. However, processing of Big Data to make predictions or decisions like this often requires the use of Machine Learning techniques.