@Rich_Morin great response! Thanks for jumping in here and answering @yahavka12 questions 
I don’t have a lot more to add to this, just a few more thoughts and links:
- Rich is correct in that the TBP implementation is currently focused on modeling static objects and learning and recognizing them by moving a sensor. We are planning to incorporate a time component into our models but this is work in progress (some more thoughts on this in @nleadholm post here Extending and Generalizing TBT Learning Models - #27 by nleadholm ).
- If your application is focused on anomaly detection in time series data, not sensorimotor learning, then HTM is currently the better approach to look into. There is a separate HTM forum here. Numenta recently changed the license of the associated code to an MIT license but the code is not being actively maintained.
- For more details on your first question you can check out the question on differences between HTM and TBP in our FAQ.
- There is a practical implementation of TBT. You can find it in our GitHub repository called tbp.monty. We also have extensive documentation on the approach and instructions on getting started with the code as well as tutorials and capabilities of the system.
- If you want to read more about the TBP approach, you can check out our whitepaper. For more info on HTM and anomaly detection work from Numenta (The TBP is a non-profit separate from Numenta now), you can have a look at Numenta’s papers.
I hope this helps!
-Viviane