Recent posts by Mona

In recent years, the term MLOps has become a buzzword in the world of AI, often discussed in the context of tools and technology. However, while much attention is given to the technical aspects of MLOps, what's often overlooked is the importance of the operations. There is often a lack of discussion around the operations needed for machine learning (ML) in production, and monitoring specifically. Things like accountability for AI performance, timely alerts for relevant stakeholders, the establishment of necessary processes to resolve issues, are often disregarded for discussions about specific tools and tech stacks. 

As the use of AI becomes more widespread across various industries, the need to monitor AI-driven applications for anomalies and unexpected behaviors has become increasingly important. Each use case is different and may require a unique set of fields and metrics to effectively identify and surface anomalous behaviors early before business is negatively impacted. At Mona, we are committed to providing the most advanced AI monitoring platform to improve the accuracy and reliability of AI-based systems. We have developed a one-of-a-kind insight generator designed to detect the specific data segment in which the anomaly lies, providing users with the full context of the behavior including possible explanations on why it is occurring. The key to successful AI monitoring lies in the ability to adhere to the intricacies of each use case, providing users with valuable insights to optimize their models and processes. Following numerous user requests, we just enhanced our monitoring capabilities to use geo-location and multiple timestamp fields in any monitoring context.

We recently announced our latest innovation to our intelligent monitoring platform - Mona’s new AI fairness feature. This feature assists with eliminating bias with AI-driven applications, increasing trust in your machine learning models in production to ensure compliance readiness.

In recent years, the topic of AI democratization has gained a lot of attention. But what does it really mean, and why is it important? And most importantly, how can we make sure that the democratization of AI is safe and responsible? In this blog post, we'll explore the concept of AI democratization, how it has evolved, and why it's crucial to closely monitor and manage its use to ensure that it is safe and responsible.