Some approaches to machine learning have yielded overly aggressive models that give way to false positives. False positives create negative user experiences that prevent new protection from deploying. IBMs Ronan Murphy and Martin Borrett also noted that one of Watson’s critical goals is to present security issues to researchers without drowning them in false alarms The Ponemon Institute recently reported that over 20 percent of endpoint security investigation spending was wasted on these false alarms. To provide maximum value while reducing pressure on overworked staff, security based on machine learning must balance blocking malicious malicious software with avoiding impact of regular use of business applications.”]