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The Science of Anomaly Detection

Jeff HawkinsJeff HawkinsFounder
The Science of Anomaly Detection

I just finished writing a new whitepaper. It is about the science of detecting anomalies.

As followers of Numenta know, we have worked for many years to understand how the neocortex works. As I described in On Intelligence, the brain is a prediction machine, one that builds models from streaming data and constantly makes predictions. A large part of our research has been to understand exactly how the neocortex learns and makes predictions. The Cortical Learning Algorithm (CLA), included in our NuPIC open source project, was a major advance in that direction.

We also feel it is imperative to find valuable applications for brain-based technology today. So for the past two years we built a prediction engine based on the CLA and started the process of investigating commercial applications. Although we found applications for prediction in many industries, and the CLA worked well in those applications, there were substantial barriers to being able to act on predictions within existing business processes. Further, we learned that there was equal or greater interest in anomaly detection, the “flip side” of prediction.

With this knowledge we looked at the state-of-the-art in anomaly detection technology. We also interviewed many people who use anomaly detection products in their daily routines. We quickly learned two things. One is that simple-to- use products, ones that don’t require machine learning experts, didn’t perform well. Every person we talked to told us about getting too many false positives and/or too many false negatives. The second thing we learned is that existing tools are designed to be used in data centers, but they caused frustration when people were away from the data center or away from the office. A surprising number of people we interviewed told us that they turned off alerts altogether.

We realized that by using the CLA and applying our understanding of neuroscience, we could take a fresh approach, and create a substantially better anomaly detection engine. We also felt we could reinvent how anomalous events are reported and explored, by creating a new type of mobile interface. Our product, Grok, is the result. Grok advances the state-of-the-art in anomaly detection technology and it replaces SMS’s, and email alerts with a fun and powerful mobile application. In just a few seconds on your mobile phone you can see which of your applications and servers are acting unusually and if they need further attention.

I’ve written a paper that explains how we have applied the science of the CLA to the technology of anomaly detection. It illustrates how a simple-to-use product can detect anomalies with subtlety and sophistication by using cortical models. I hope you’ll read it and see why I’m so excited. In my view, this is one of the first products based on neocortical principles, a system that learns patterns from its temporal data stream, makes predictions, and identifies anomalies. Just what your brain does every moment of every day.

Jeff HawkinsJeff HawkinsFounder