Blog – page 9

  1. Deep learning, a history in context

    DeepMind, based on a deep learning architecture made a big impact in the tech industry. Deep learning continues to gain traction in the machine learning community and in the mainstream, both in terms of public awareness of its capabilities as well as through commercialisation. This article by Simon Winder provides a very accessible introduction to…

  2. Sparse Distributed Representations (SDRs)

    TL;DR: An SDR is a Sparse Distributed Representation, described below SDRs are biologically plausible data structures SDRs have powerful properties SDRs have received a lot of attention recently There are a few really great new resources on the topic: Presentation by Subutai Ahmad of Numenta Older introductory presentation by Jeff Hawkins Excellent summary of their characteristics in…

  3. Agency and Hierarchical Action Selection

    This post asks some questions about the agency of hierarchical action selection. We assume various pieces of HTM / MPF canon, such as a cortical hierarchy. Agency The concept of agency has various meanings in psychology, neuroscience, artificial intelligence and philosophy. The common element is having control over a system, with varying qualifiers regarding the entities…

  4. Recent HTM projects

    It’s exciting to see growing interest and participation in the AGI community. This is another brief post to share two examples. In this case, they both build on one approach to AGI, and that is HTM. FXAI – Explorations Into Computational Intelligence A blog that is pretty well described by the title. The author, Felix…

  5. A Unifying View of Deep Networks and Hierarchical Temporal Memory

    Browsing the NUPIC Theory mailing list, I came across a post by Fergal Byrne on the differences and similarities between Deep Learning and MPF/HTM. It’s a great background into some of the pros and cons of each. Given the popularity and demonstrated success of Deep Learning methods it’s good to understand how they work and how…

  6. On Predictive Coding and Temporal Pooling

    Introduction Predictive Coding (PC) is a popular theory of cortical function within the neuroscience community. There is considerable biological evidence to support the essential concepts (see e.g. “Canonical microcircuits for predictive coding” by Bastos et al). PC describes a method of encoding messages passed between processing units. Specifically, PC states that messages encode prediction failures; when…

  7. Some experimental results with NUPIC

    A quick post here to give readers an idea of HTM/CLA performance on visual object recognition tasks. Although a little out of date now, Craig’s blog gives a good idea of what NUPIC can and can’t do, and how data issues (e.g. training set, variations in object appearance) affect the results. This is a handy…

  8. Connectome browser – hierarchy viewer?

    Hierarchy Viewer? Ongoing research to map out the patterns of connectivity in the human brain continues to produce stunning visuals. Are we looking at the hierarchy as proposed in the Memory-Prediction framework? In any case, it’s fun to explore, which you can do here: http://www.humanconnectomeproject.org/data/relationship-viewer/