Special Report on Succeeding with Machine Learning

Machine Learning Trends

There is no reason to think that reliance on ML will decrease going forward. As Big Data becomes the norm, the volume of available data from which a machine can learn accelerates. This, in turn, provides many opportunities for successfully implementing ML. When looking for success in ML, it’s important to recognize that it’s not a black box. You don’t just input data and expect miraculous results. Oversight and advance planning are essential. Concentrate on what you want to accomplish. You need human supervision for your knowledge base and your inference engine and you need to guard against unrealistic expectations. Then you can achieve success with your ML project....

Succeeding with Machine Learning

Access Innovations, Inc. deployed its first client instance of its artificial intelligence (AI) system in 1995. While this isn’t a StarTrek-esque “computer” that analyzes data and comes to independent conclusions, it does exactly what it is supposed to: make keyword suggestions based on inferences from the text of a document. What do you think of when you hear “artificial intelligence” or “machine learning (ML)?” Science fiction is loaded with AIs that think—or attempt to think—like humans and have—or try to have—feelings. These are entertaining, sometimes wildly so, but they are still just fiction. Artificial intelligence doesn’t have to have all the bells and whistles of robots that walk and talk and cavort on the Holodeck. At its kernel, what is artificial intelligence....