Occasionally we receive questions about our publishing strategy, such as why we share papers that have not yet been published in a scientific journal, or what is our stance on open science. Our co-founder, Jeff Hawkins, recently responded to a question about this topic that was posted on our HTM Forum. For those of you who are not active there, you can read a consolidated version of Jeff’s thoughts in this post.
Numenta has launched a new podcast series called Numenta On Intelligence-a monthly podcast about how intelligence works in the brain, how to implement it in non-biological systems and how to think about the implications. VP of Marketing Christy Maver describes the new podcast and how to subscribe to it in this blog post.
After AWS announced its Random Cut Forest algorithm (RCF) for anomaly detection, we were curious to see how it would score on the Numenta Anomaly Benchmark (NAB), a benchmark we designed to test anomaly detection algorithms. We share the results in this blog and ask one of our engineers to walk us through the process.
The discovery of grid cells won the Nobel Prize in 2014, but do you know how they work? Working together in populations, grid cells create a cognitive map of space. Each cell responds to certain areas of space. Groups of grid cells called modules have the same projection properties onto space. Many grid cell modules working together can map a virtually infinite amount of space.
In 2016, Numenta co-founders Jeff Hawkins and Donna Dubinsky wrote a blog about the three major approaches to building machine intelligence: Classic AI, Simple Neural Networks, and Biological Neural Networks. This piece revisits each one and looks at the machine intelligence landscape today. Discover the state of the art, compare and contrast approaches, and understand fundamental limitations. Read why brain theory will be the future of machine intelligence.