Hi Dinesh,
HTM refers to the general theory developed by Jeff Hawkins and Numenta over
the past 1-15 years. You can think of HTM as the general "big idea" of how
we believe the neocortex works. The key aspects of HTM are Jeff's six
principles, which refer to hierarchy, sparse distributed representations,
online learning from streaming data, a uniform algorithm, combination of
sensory and motor function everywhere, and attention. While the theory will
accumulate detail (for example what the roles of the layers inside a region
might be doing), it grows outwards stably from this kernel.
Officially, CLA refers to the particular detailed algorithmic design for a
single layer of neurons, which is outlined in the 2011 White Paper and
(partially) implemented by NuPIC. Jeff Hawkins and Numenta have indicated
that they wish to "freeze" this meaning of CLA and use a different name for
new versions of their detailed algorithmic designs.
The rest of us have become accustomed to using "CLA" to refer to an
algorithmic design which is close to Numenta's, but might differ in some
minor or major aspects. The key features of CLA, which generalise across
most of our models, are:
- Neurons arranged in columns ("mini-columns" in neocortex) which share
feedforward inputs and have similar feedforward responses.
- Sparsity imposed by a columnar inhibition algorithm.
- Feedforward inputs appear on proximal dendrites (to a column in official
CLA, also to cells in some models).
- Neurons in a layer have axons connected to distal dendrites in the same
layer, allowing for prediction.
- Proximal dendrites perform some version of linear summing.
- Distal dendrite segments act independently as coincidence detectors.
- Layers can learn first-order transitions between feedforward patterns,
and also higher-order sequences using choices of active cells in an active
column.
- Columns which correctly predict their activity have one cell active,
otherwise several cells activate (burst).
HTM is quite general, allowing for many more detailed theories and designs
to be claimed to correspond to HTM, but It's much easier to quantify how
well a design matches up with CLA proper.
We tend to use CLA when referring to processes in some detail (at the
layer, column, neuron, dendrite, synapse levels), and HTM when talking
about how things work at the layer, region and brain levels. We'll also be
seen using "HTM" when we propose ideas which supercede or contradict
assumptions underlying Numenta's "official" CLA design.
The other thing to bear in mind is that CLA is an internal name (within the
community) which has no general currency in either neuroscience or AI/ML,
while HTM is well-known (at least by name) to researchers in both fields.
Regards,
Fergal Byrne
On Fri, Jan 9, 2015 at 12:48 PM, David Ragazzi <[email protected]>
wrote:
> Dear Dinesh,
>
> > 1.What is the difference between CLA and HTM? 2.Is CLA generalization of
> HTM as the CLA(the agorithms based on cortex) name suggests so? Explain
> if wrong.
>
> CLA => Cortical Learning **ALGORITHMS**
> HTM => Hierarchical Temporal **THEORY**
>
> As the names say, CLA tries simulate what the HTM states about how cortex
> could work. Something we use wrongly HTM acronym to refer to CLA. But the
> names are clear, one is the theory, the other is the algorithmic model of
> it. Just remember neither all features addressed on HTM are implemented on
> CLA (yet).
>
> David
>
> On 9 January 2015 at 10:08, Dinesh Deshmukh <[email protected]> wrote:
>
>> Hi
>>
>> 1.What is the difference between CLA and HTM?
>> 2.Is CLA generalization of HTM as the CLA(the agorithms based on cortex) name
>> suggests so?Explain if wrong.
>>
>> Thank you.
>>
>>
>
>
> --
> David Ragazzi
> MSc in Sofware Engineer (University of Liverpool)
> OS Community Commiter at Numenta.org
> --
> "I think James Connolly, the Irish revolutionary, is right when he says that
> the only prophets are those who make their future. So we're not
> anticipating, we're working for it."
>
--
Fergal Byrne, Brenter IT
http://inbits.com - Better Living through Thoughtful Technology
http://ie.linkedin.com/in/fergbyrne/ - https://github.com/fergalbyrne
Founder of Clortex: HTM in Clojure -
https://github.com/nupic-community/clortex
Author, Real Machine Intelligence with Clortex and NuPIC
Read for free or buy the book at https://leanpub.com/realsmartmachines
Speaking on Clortex and HTM/CLA at euroClojure Krakow, June 2014:
http://euroclojure.com/2014/
and at LambdaJam Chicago, July 2014: http://www.lambdajam.com
e:[email protected] t:+353 83 4214179
Join the quest for Machine Intelligence at http://numenta.org
Formerly of Adnet [email protected] http://www.adnet.ie
