The IBM Watson Studio platform provides an end-to-end data science solution that quickly puts AI to work, helping your organization stay ahead of fraudsters. As a single platform for collaborative model development, Watson Studio makes it possible for cross-functional business and technical teams to work together quickly and seamlessly. Watson Studio enables different sets of users to work together regardless of the types of users they are. It supports teams with easy tooling to help automate tasks and with more advanced tools such as deep learning and neural networks. To learn more, watch this video showing IBM Watson Studio at work in a fraud prediction scenario.

American physician and surgeon William J. Mayo, one of the founders of the famed Mayo Clinic, stated, "The aim of medicine is to prevent disease and prolong life, the ideal of medicine is to eliminate the need of a physician." Emerging applications of artificial intelligence (AI), as well as medical research trends, suggests that we are moving toward fulfilling medicine's aim and achieving its ideal. Health care organizations appear to be preparing themselves for the next technological step. For instance, in 2014 health care providers spent 4.2 percent of their revenues on IT, compared to a 3.3 percent cross-industry average. Penetration of electronic health care records grew from 40 percent in 2012 to 67 percent in 2017. With its wealth of smart machines, health care is expected to be among the fastest growing industries in terms of data generated.

Artificial intelligence (AI) is the stuff of the real world today. Your Google computer search, your Netflix movie choices, and your Amazon-supplied selection of buying options "made just for you" all employ AI based techniques. The application of AI pioneered by Cylance has transformed endpoint protection before our very eyes. Organizations are completely changing the way they operate, using greater security with fewer resources. Their staff was previously stretched thin, running around fixing problems, and trying to catch up with never-ceasing tickets.

Machine learning security offers many advantages over signature-based detection, but the technology can be as difficult to explain as it is for malware to beat. During an interview with SearchSecurity, Brett Hansen, executive director of data security solutions at Dell, offered insight into his company's investment in machine learning security and its partnership with advanced threat protection startup Cylance Inc. In part one of the interview, Hansen discussed the problems with traditional antivirus and antimalware programs relying on signature-based detection methods. In part of two of the interview, Hansen talks about the advantages of machine learning for smaller businesses, why it's a struggle to discuss the technology behind it, and how machine learning security serves as a better defense against ransomware attacks and other emerging threats. Here are excerpts from the conversation with Hansen. Is the move to machine learning security more about the shortcomings with signature-based detection and the frustrations people have had with it, or the benefits and value of machine learning?