# TM’s ability to generalize

**URL:** <https://discourse.numenta.org/t/tm-s-ability-to-generalize/3630>\
**Category:** Numenta Theory\
**Created:** [March 8, 2018, 7:48pm UTC](https://discourse.numenta.org/t/tm-s-ability-to-generalize/3630 "2018-03-08T19:48:08Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![sunguralikaan](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.numenta.org/sunguralikaan/32/585_2.png) [@sunguralikaan](https://discourse.numenta.org/u/sunguralikaan)\
**Post date:** [March 12, 2018, 12:02pm UTC](https://discourse.numenta.org/t/tm-s-ability-to-generalize/3630/2 "2018-03-12T12:02:56Z")

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> [@Why is HTM Ignored by Google DeepMind?](https://discourse.numenta.org/t/why-is-htm-ignored-by-google-deepmind/2589/38):
>
> There’s a serious lack in TM’s ability to generalize among semantically similar contexts.

I thought that semantic similarity is handled by Spatial Pooler (the minicolumns). Same column but different neurons would mean similar contexts. If something is represented by the same exact neurons, it would qualify as the same context not similar. Firing same or overlapping neurons would not be generalization. In the current theory, mini-columns generalize not individual neurons. Either it is not the TM’s job to do that, or we should change our approach as you suggest to incorporate that to TM. It is also important to note that we have not mastered our hypothesized best solution to generalization yet; Temporal Pooling.

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