AI as a commonly used buzzword can be somewhat misleading. After a few years developing and managing technologies incorporating AI as a problem solving approach, our conclusion is that you should be careful when and where to apply AI in a solution.
As a baseline, AI includes machine learning and deep learning sets of algorithms and mathematical approaches to solve a problem. Soon enough, you realize the majority of the work developing and optimizing these algorithms is depending on how good, real and clean your data is. It means that you can find yourself investing the majority of your time collecting, preparing and understanding your data just so you can run your AI algorithms to understand and monitor the results over time.
Silverbolt chose the approach to use AI only where and when its value is clear. We also use the right set of algorithms rather than chase the technology no matter what. We use machine learning in part of our detection engines and deep learning in others, where it’s a must, while combining human threat hunters and AI scientists inputs.
So, why use AI?
If it is done correctly it produces great and fast results. It is scalable and future ready with its prediction approach and capabilities. It can easily accumulate big data scenarios and requires low maintenance and updates.