Application of "Hierarchical Temporal Memory" with hAPP

Hierarchical Temporal Memory Model for Intelligence

HTM is based on neuroscience principles drawing upon physiological interaction of pyramidal neurons in the neocortex of the mammalian human brain.

At the core of HTM are learning algorithms that can store, learn, infer, and recall high-order sequences. Unlike most other machine learning methods, HTM continuously learns in an unsupervised time-based patterns in unlabeled data.

HTM is robust to noise, and has high capacity it can learn multiple patterns simultaneously. When applied to computers, HTM is well suited for prediction, anomaly detection, classification, and ultimately sensorimotor applications.


How can distributed application developer leverage concepts such as HTM?

Sharing some thoughts to stimulate this discussion thread.

Someone like myself who take keen interest in paradigm shifting FinTech trends, drawing inspiration from online resources such as Digital Bank Manifesto, stare at this image for hours pondering, imagining Digital Banks of Future (DBF).

Following thoughts surface in ones mind to assess promise of holochain and HTM in following context:

  • DatabaseDesign - schema of datum as hAPP - could make users to own, maintain and be responsible for their own data backed with hashed copy on holo.cloud thus enabling peer to pay or offer credits - to peers they trust without verification and verify credit worthiness of those they arent familiar with.
  • DataAnalytics - distributed schema with public accounts - where transactions are pushed out every time by design to be captured by information and advice service providers i.e. DBF who can make sense of that to offer services.
  • ArtificialIntelligence - exponential nature of information - both for peer to access, as well as service provider to process. Thus meriting constructs offering large scalability built in it. This is where HTM offers huge advantages to meet provider’s need of understanding “Patterns” to offer advice and services, while peers need “Global Views” patterned for simplicity.
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I found this article interesting: memory has roots in viruses https://medium.com/microbial-instincts/the-human-mind-has-its-roots-in-retroviruses-4500d84b4134

@mikeg it would be helpful if you could elaborate or maybe pull a quote or two from the article you were directing our attention to. This helps keep our forum and threads within them organized.

For example check out HTM Forum their mission is scientific and many of the participants are doctoral students working on thesis. Where they discuss about the complexity and nuance of human mind and the associated mathematical and computer model they are building.

Thus it is a best practice on our part to keep each others Focus of Attention focused such that we can give each other concentrated bolus of information.

For example: One can go re-edit their post if they would like to rephrase their comments, or maybe one can embed a link within a word rather than calling out the entire url (for we trust each other!), highlighting with bold, italics also help.

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Hi @Aryabhatta, is there any kind of practical implementation of HTM in github or anywhere. As far as understand this is unsupervised learning. Is it like https://en.wikipedia.org/wiki/Local_outlier_factor