Deep learning and artificial intelligence (AI) are rapidly evolving fields with new iterations emerging constantly. New applications for these technologies, for example, arise on a daily basis along with new variations on the technology itself. This interesting information came to us from CoinTelegraph in their article, “5 emerging trends in deep learning and artificial intelligence.”

Federated learning is a machine learning approach that allows multiple devices to collaborate on a single model without sharing their data with a central server. This approach is particularly useful in situations where data privacy is a concern.

A type of machine learning called reinforcement learning includes teaching agents to learn via criticism and incentives. Many applications including robotics, gaming, and even banking have made use of this strategy. 

Whatever the application, it has never been more important to understand the technology. Most organizations have little knowledge on how AI systems make decisions, and as a result they have little insight into how to apply the results. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Why is this important? Because explainability becomes critical when the results can have an impact on data security or safety.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.