While Numenta does not build commercial applications, we have created example HTM applications in several fields such as monitoring stock performance, detecting unusual human behavior, and finding patterns in geospatial data. Additionally, our partners have created commercial applications in the field of monitoring IT infrastructure and understanding natural language. We are confident that many additional applications will be created in the future.
HTM is well suited for applications that have the following characteristics:
- Data flowing through time: the data can be in the form of numbers, dates, text, or GPS points
- A data sampling rate from once per minute to once per hour, with the “sweet spot” being between once per minute and once every five minutes (faster velocity data can be aggregated or sampled as well)
- Data that has inherent structure, i.e. not entirely random
- Many models are required rather than one large model
- Focus of the application is prediction or anomaly detection
The following applications are examples that fit these characteristics:
- Highlighting anomalies in the behavior of moving objects, such as tracking a fleet’s movements on a truck by truck basis
- Understanding if human behavior is normal or abnormal on a securities trading floor
- Predicting energy usage for a utility on a customer by customer basis
- Predicting failure in a complex machine based on data from many sensors
In order to demonstrate these capabilities, we have created several tools and example applications.
HTM Studio for Anomaly Detection
HTM Studio for Anomaly Detection is a tool that makes it easy to experiment with using HTM to detect anomalies in your own scalar data. Designed for the business-focused user, this tool makes it easy to develop a proof of concept with HTM technology without doing any coding.
Rogue Behavior Detection
The example geospatial tracking application detects anomalies in the movement of people, objects, or material using speed and location data. Use this application to enable logistics optimization. You can experiment with this application using your own data by downloading our sample application code below.
HTM for Stocks
HTM for Stocks is an example application that detects anomalies in publicly traded companies. It continuously models stock price, stock volume, and Twitter volume for publicly traded companies and alerts you in real time when something unusual is happening. You can experiment with this application by downloading our sample application code below and connecting it to Twitter and metric collectors.
Grok is a commercial application offered by one of our strategic partners that detects anomalies in servers and applications. It learns continuously, automatically discovers time-based patterns in data, and generalizes from experience.
Grok is now available at http://grokstream.com.
Natural Language Processing
One of our partners, Cortical.io, has used Numenta’s technology to develop and commercialize Natural Language Processing Solutions. By representing language with highly efficient semantic fingerprints, Cortical.io has built the first semantic engine that can analyze text in real time, in any language.