Hawkins also has a new book coming. His first book (as said in other comments) is a fantastic read.
https://www.amazon.com/Thousand-Brains-New-Theory-Intelligen...
Not to be too mean about it, but I feel like this is an instance of brilliant marketing more than anything. The founder of Numenta knows how to communicate to Engineers in a convincing way. Neuroscientists (and Science in general) has a way of politely ignoring outsiders and in any case Computational neuroscience doesn’t have terribly high standards of rigor and quality anyways.
Lex Fridman has a fantastic interview with the Numenta's (and Palm's) founder, Jeff.
I fiddled around with it before Google open sourced tensorflow. Seems like the project is almost entirely abandoned-no commits for a year now. I suppose this may have something to do with the death of the lead developer Matt Taylor several months ago(R.I.P.) but I could be wrong. It would be interesting to see if someone could get it up to speed.
Python 2 only, project in maintenance mode? Why post this what's the hacker news?
As part of this older project, there is a nice benchmarking/comparison example for several types of anomaly detection for sequence data. If you need to do that, looking at this example is worthwhile.
Why would I want to mess with that now when it depends on Python 2.7?
Wouldn't that be like basing something on the LuaJIT-based Torch7?
For people wanting to look into HTM (Hierarchical Temporal Memory), do check out Numenta's main website [1], in particular the papers [2] and videos [3] sections.
Otherwise, HTM inventor Jeff Hawkins' book "On Intelligence" is one of the top 3 or so most fascinating books I've ever read. It doesn't cover HTM though, just how the brain works at a conceptual level, but in a way I haven't seen anyone else explain. Jeff clearly has an ability to see the forest through the trees in a way that is not too commonly found. This is one of the reasons I think HTM might be on to something, although it of course has to prove itself in real life too.
But we should remember for how long classic Neural Networks was NOT overly successful, and almost dismissed by a lot of people (including my university teacher who was rather skeptical about them, when I took an ML course on like 12 years ago and personally believed a lot in them). We had to "wait" for years and years until enough people were eventually throwing enough work on finding out how to make them really shine.
[1] https://numenta.org/
[2] https://numenta.com/neuroscience-research/research-publicati...
[3] https://www.youtube.com/user/OfficialNumenta
[4] https://www.amazon.com/Intelligence-Understanding-Creation-I...
Edit: Fixed book link.