# Issues in BAMI

**URL:** <https://discourse.numenta.org/t/issues-in-bami/8463>\
**Category:** Numenta Theory\
**Created:** [April 20, 2021, 6:45am UTC](https://discourse.numenta.org/t/issues-in-bami/8463 "2021-04-20T06:45:16Z")\
**Posts on this page:** 1\
**Showing post:** 3

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**Author:** ![Paul\_Lamb](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.numenta.org/paul_lamb/32/2725_2.png) [@Paul\_Lamb](https://discourse.numenta.org/u/Paul_Lamb)\
**Post date:** [April 20, 2021, 3:50pm UTC](https://discourse.numenta.org/t/issues-in-bami/8463/3 "2021-04-20T15:50:52Z")

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> [@markNZed](#):
>
> This is a radical change because the predictive information is not available to other cells. HTM has shifted from being a predictive framework in _On Intelligence_ to a reactive framework

I would maybe characterize it as an “anomaly detection framework”, than a purely reactive framework. It is very good at knowing when it is predicting things incorrectly and calling that out through bursting, which is a hyper-active (less sparse, more dense) output.

I can split this to a separate thread if you think it is too off topic, but are there some scenarios that you can think of in which the view of predictions from BAMI become a difficult problem on the road to “true” machine intelligence?

The main one that I am aware of (which you also mentioned on another thread) is this one:

> [@Evolution of the neocortex](https://discourse.numenta.org/t/evolution-of-the-neocortex/8387/87):
>
> From a predictive coding perspective you generate behavior from predictions - it is the output of predictions from higher levels that ripple “down” toward muscle control etc and allow things like controlling fine motor movement.

One way that I have implemented this particular capability (which I call “Temporal Unfolding”) is by tweaking the TM algorithm so that motor cells which are predicted both distally and apically become active. Another way to implement it is that motor-related cells just don’t behave the same way as TM cells, and their predictions are “active predictions” (i.e. rather than going to predictive state from distal input, they activate). This would be even less stable though (would certainly require refinement to be added on top, as anyone who has tried this with HTM before knows – may require a model of the cerebellum, for example), and would require either a different learning algorithm or the separation of “training” and “inferring” stages (which is counter to continuous learning)

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_[View the full topic](https://discourse.numenta.org/t/issues-in-bami/8463)._