Hi, fellows.
Where can I find the last papers, the novelties on HTM and CLA?
Regards,
Sergio Soares.
Em Sexta-feira, 9 de Janeiro de 2015 22:04, Subutai Ahmad
<[email protected]> escreveu:
Very nice description Fergal! It's worth emphasizing your last point. The term
HTM is more meaningful and should be used outside the NuPIC community. We're
trying to stop using the term "CLA" altogether.
--Subutai
On Fri, Jan 9, 2015 at 5:27 AM, Fergal Byrne <[email protected]>
wrote:
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
