Stanford professor Andrew Ng teaching his course on Machine Learning (in a video from 2008)
“New Brainlike Computers, Learning From Experience,” reads a headline on the front page of The New York Times this morning. The article focuses on machine-learning algorithms, known as a neural networks, that are becoming increasingly important in computer science. And in 2014 Qualcomm will release the first commercial version of a neuromorphic processor that transforms this software technique directly into hardware to increase performance for intensive machine learning tasks.But buried in the last paragraph of the story was the fact that “The largest class on campus this fall at Stanford was a graduate level machine-learning course covering both statistical and biological approaches, taught by the computer scientist Andrew Ng. More than 760 students enrolled.” And several previous versions of the course are available online for free. The most recent is from Coursera (which Ng cofounded with Daphne Koller last year) but the 2008 course is on iTune U, YouTube and Stanford’s Engineering Everywhere.What’s going on here? Simply put, machine learning is the part of artificial intelligence that actually works. You can use it to train computers to do things that are impossible to program in advance. Ng uses the example of handwriting recognition as a classic example of a problem that can only be achieved through machine learning. In his introductory lecture on Coursera, Ng refers to search engines like Google and Bing, Facebook and Apple’s photo tagging application and Gmail’s spam filtering as everyday examples of machine learning at work. Ng is the director of the Stanford Artificial Intelligence Lab and one of the founders, with Jeff Dean, of Google Brain, a deep learning research project at Google. He is using machine learning as a step towards the “AI dream of someday building machines as intelligent as you or I.”...MORE