Leading the New Era of Machine Intelligence

Numenta has developed a cohesive theory, core software technology, and numerous applications all based on principles of the neocortex. This technology lays the groundwork for the new era of machine intelligence. Our innovative work delivers breakthrough capabilities and demonstrates that a computing approach based on biological learning principles will make possible a new generation of capabilities not possible with today’s programmed computers.

Win Big $$ in the Numenta Anomaly Benchmark (NAB) Competition

Do you have an algorithm that detects anomalies in streaming data? Or a real-world, time-series dataset with labeled anomalies?
Learn more: http://numenta.org/nab/

What Is Machine Intelligence?

Because today’s computers are programmed, they can only do exactly as they are told. In stark contrast, intelligent machines continuously and automatically learn patterns in their environment without being programmed, enabling them to tackle problems in entirely new ways. Intelligent machines that learn and act will have an enormous beneficial impact in the coming decades.

Brain as a Blueprint

The brain is the best example of an intelligent system and provides a roadmap for building intelligent machines. The brain’s center of intelligence, the neocortex, controls a wide range of functions using a common set of principles. Numenta has made significant progress discovering these principles and using them to create learning algorithms. Numenta is unique in its understanding and adherence to neocortical principles.


We’ve created the first benchmark designed to evaluate real-time anomaly detection algorithms. The Numenta Anomaly Benchmark is an open-source framework, with real-world data files, that rewards early detection and offers a controlled method for measuring and comparing performance.
Learn more about NAB.


Our machine intelligence technology is called Hierarchical Temporal Memory (HTM), which is a detailed computational theory of the neocortex. At the core of HTM are time-based learning algorithms that store and recall spatial and temporal patterns. HTM is well suited to a wide variety of problems, particularly those with the following characteristics:

  • Streaming data rather than static databases
  • Underlying patterns in the data change over time
  • Many individual data sources where hand crafting separate models is impractical
  • Subtle patterns that can’t always be seen by humans
  • Time-based patterns
  • Simple techniques such as thresholds yield substantial false positives and false negatives

Our technology has been tested and implemented in software, all of which is developed with best practices and is suitable for deploying in commercial applications. Our core learning algorithms are fully documented and available in an open source project called NuPIC.


Like the brain, Numenta’s machine intelligence technology can be applied to many types of problems. We have tested it on a variety of applications to validate its broad applicability. A few of these applications are described below.

Video: Intro to our Applications
Please note: Avik Partners has licensed the Grok for IT Analytics application. Learn more about Grok and sign-up for their beta program at http://grokstream.com. For more information, read our press release.
  • HTM for Stocks

    HTM for Stocks Screenshot

    Detects anomalies in publicly traded companies. Models stock price, stock volume, and Twitter volume related to top market companies. Get example application via Google Play Store, and register to give feedback.

  • Grok for IT Analytics

    Grok for IT Analtyics Screenshot

    Detects anomalies in servers and applications. Learns continuously, automatically discovers time-based patterns in data, and generalizes from experience.

    Avik Partners has launched their beta program for Grok for IT Analytics 2.0, sign up here.

  • Rogue Behavior Detection

    Rogue Behavior Detection Screenshot

    Models normal behavior of individuals. Detects changes in behavior indicative of unauthorized file access or unauthorized trading. You can experiment with this application using your own data by downloading our sample application code below.

  • Geospatial Tracking

    Geospatial Tracking Screenshot

    Detects anomalies in the movement of people, objects, or material using speed and location data. Enables logistics optimization. You can experiment with this application using your own data by downloading our sample application code below.

Numenta Anomaly Benchmark (NAB)

Early anomaly detection in streaming data is as difficult as it is important. Yet no tools exist for comparing detection techniques for real-time, streaming data.

That’s why we’ve created the Numenta Anomaly Benchmark (NAB). NAB is an open source framework that anyone can use to test and compare real-time anomaly detection algorithms. It consists of:

  • A dataset with 58 real-world, labeled data files
  • A scoring mechanism that rewards early detection and on-line learning

Get Started


Interested in exploring our technology or developing your own application? Our machine intelligence algorithms, encoders, and application code are all available on NuPIC (Numenta Platform for Intelligent Computing), our open source project.


Numenta aims to make it easy for business to develop and distribute applications that harness the power of our machine intelligence technology. Learn about licensing opportunities below or contact Numenta to inquire about potential partnerships.

For videos and whitepapers, go to our Learning Center.


Image Numenta at the Computational and Systems Neuroscience Conference (COSYNE) Numenta at the Computational and Systems Neuroscience Conference (COSYNE)
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Numenta Image Numenta Press Release

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Sat, Apr 23, 2016 10:00 AM — 4:00 PM
Infor, 641 Avenue of the Americas
New York City, NY USA
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