# What is a "hyperparameter" in HTM vs Deep Learning?

**URL:** https://discourse.numenta.org/t/what-is-a-hyperparameter-in-htm-vs-deep-learning/4484
**Category:** Lounge
**Created:** [September 4, 2018, 12:22pm UTC](https://discourse.numenta.org/t/what-is-a-hyperparameter-in-htm-vs-deep-learning/4484 "2018-09-04T12:22:56Z")
**Posts on this page:** 1
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### Author: ![nbro](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.numenta.org/nbro/32/2864_2.png) [@nbro](https://discourse.numenta.org/u/nbro)
#### Post date: [September 4, 2018, 9:07pm UTC](https://discourse.numenta.org/t/what-is-a-hyperparameter-in-htm-vs-deep-learning/4484/10 "2018-09-04T21:07:14Z")

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> [@HTM and Deep learning](https://discourse.numenta.org/t/htm-and-deep-learning/4470/12):
>
> Don’t forget that HTM is biologically constrained, which means that it’s not allowed to do anything the brain doesn’t do. So this is off the cards, unless the brain is able to tweak its chemistry/topology in response to different inputs (my understanding is it doesn’t).

But every brain is (slightly) different from all other brains. I don’t see why tweaking these hyper-parameters would be against nature (i.e. it would be like finding the best brain to perform a certain task). Anyway, we can still optimize these hyper-parameters using constraints.

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