According to CIO Magazine, May 2nd, 2018, major brands are intensely searching for explainable AI solutions for several reasons spanning guarding against ethical and regulatory breaches to understanding when to override machine based decisions or how to improve them in the future.
In Cognilytica Research’s briefing note on simMachines, January, 2018, it highlights the black box challenge of today’s AI machine learning technologies and the fundamental problems lack of explainability causes.
simMachines, Inc., the leader in Explainable AI / Machine Learning applications, announces the launch of their latest product—Dynamic Predictive Audiences designed for data companies, publishers and media platforms.
Today’s digitally-empowered customers have high expectations for relevant, highly personalized customer experiences. Companies must keep pace with these growing demands or they will be left behind by their more perceptive competition.
Similarity is a machine learning method that uses a nearest neighbor approach to identify the similarity of two or more objects to each other based on algorithmic distance functions.
Market segmentation is one of the most basic arms of business strategy. Firms bundle customers to understand their preferences, manage relationships with them, improve product and service offerings, and assess risk.
Most marketers are just beginning to explore machine learning applications. Machine learning is already providing tremendous analytic efficiency gains and increased precision.
Demand for explainable AI over the last year has started to ramp up from a variety of perspectives. DARPA, the Defense Advanced Research Projects Agency, for example, has been calling for more explainable machine learning models that human users can understand and trust.