Why Machine Learning May Disappoint Investors

Over the last six or seven years, the rise of big data paralleled progress in machine learning, supported by the availability of relatively cheap cloud computing services. Hence the emergence of powerful systems that excel at recognizing patterns, extracting signals from noise, and retaining knowledge from the experience. A natural outlet is cybersecurity, where machine intelligence can detect threats lurking within computer networks or gathering outside. Cases in point include BluVector, a threat hunting offering of McLean, Virginia-based Acuity Solutions Corp., which came out in 2015 after five years of development; and San Diego s DB Networks, which took four years to bring out machine-learning database security technology, in 2013, and in March announced a capability to detect credential abuse in real time. The future of AI, says DB chairman and CEO Brett Helm, is to not only block attacks but also automatically heal the vulnerabilities.