Article | June 20, 2016

Using Deep Learning To Predict Foot Traffic In Retail

Scott Roberts, ShopperTrak

By Scott Roberts, ShopperTrak

DeepMind – an artificial intelligence (AI) company that Google acquired in 2014 – recently garnered headlines with its groundbreaking AI achievement. DeepMind succeeded in creating a machine learning program, called AlphaGo, that recently crushed one of the one of the world’s top players, Lee Sedol, at an ancient strategic board game called “Go.” Go, a game of profound esteem in East Asia, consists of two players moving black and white stones around a square board. The game takes a lifetime to master, is considered exponentially more complex than chess, and is considered to be a game of more than mental acumen – “It’s also psychology, philosophy – it’s art.”

Certain intangible qualities, such as wisdom and intuition, that all masters of Go acquire through years of intense training, make it extremely difficult for an AI system to beat a human master. In fact, even only a few years ago, it was predicted that an AI program’s slashing of a Go master would take decades. AlphaGo’s success, however, highlights the power and potential capabilty of a specific type of machine learning system, deep learning.