>>2. Will the new TM implementation be encapsulated in more
"biological-like" structures? I noticed a difference between the work Marek
has done and the current CLA implementation in terms >>of the discrete
biological modeling?


>I'm not sure I fully understand your question. It will be closer to the
white paper, without the non-biological additions that currently exist in
the TP implementation. Also, it will be a little easier to map to the
>biology than the white paper description (and will incorporate a couple
minor changes to make it more biologically feasible). But at the end of the
day, the white paper description draws almost directly from >our
understanding of the biology.

My comments could have be due to the difference in coding styles when
coding in Java vs. Python?  What I was saying was I didn't notice an overt
code files/classes named Synapse; Dendrite; DistalDendrite; Layer etc.
(within the "research" directory where TP.py and spacial_pooler.py exist)
for which there are explicit references in the white paper?

David


On Tue, Jul 15, 2014 at 12:36 PM, Chetan Surpur <[email protected]> wrote:

> Hi David,
>
> 2. Will the new TM implementation be encapsulated in more
> "biological-like" structures? I noticed a difference between the work Marek
> has done and the current CLA implementation in terms of the discrete
> biological modeling?
>
>
> I'm not sure I fully understand your question. It will be closer to the
> white paper, without the non-biological additions that currently exist in
> the TP implementation. Also, it will be a little easier to map to the
> biology than the white paper description (and will incorporate a couple
> minor changes to make it more biologically feasible). But at the end of the
> day, the white paper description draws almost directly from our
> understanding of the biology.
>
> - Chetan
>
> On July 14, 2014 at 9:58:28 PM, cogmission1 . ([email protected])
> wrote:
>
> Hi Matthew (Lohbihler), Yuwei, Chetan,
>
> I apologize for my lack of a prompt response.  Thank you all for your
> responses!
>
> @Matthew - I initially wrote about my interest in porting the existing
> implementation to Java in another thread in which Matthew (Taylor)
> suggested I have a look at Marek Otahal's project on github (listed below).
>
>  >> If you're interested in porting to Java, you might have a look at
> Marek Otahal's "htm-cla" project on Github [1]. Marek is one of our main
> community contributors, and before we open-sourced NuPIC, he wrote up his
> implementation of the CLA White Paper algorithms in Java (that's how I
> found him!).
>
> >> [1] https://github.com/breznak/htm-cla
>
> If you're interested in the Java port, you might have a look at this too.
> I'm still building my understanding of the SP/TM/(and future TP)
> mechanisms, and would like to wait for the new TM mechanism that Chetan is
> developing and as well as the new TP implementation. I think I would like
> to understand the various mechanisms very thoroughly  before "diving in" to
> code - but I'm still available for discussion in the meantime; we should
> keep in touch and thank you for your offer!
>
> In addition,  I'm still reviewing the implementation of Marek's which will
> also help build an understanding. I will probably develop an additional
> implementation, though  not as a comment or critique on Marek's efforts,
> but just so that I can "shore" up my own understanding and go beyond the
> core mechanisms into the encoders, classifiers, and other peripheral
> support modules with the Java port.
>
> @Yuwei, Chetan - thank you for your clarifications and sharing the
> progress on your current projects. I wanted to ask another question.
>
> 1. Outside of the CLA algorithm implementation there are the swarming
> mechanism, the encoders and classifiers. Are these considered to be the
> difference between the "core" algorithm and the Online Prediction Framework
> (OPF)?
>
> 2. Will the new TM implementation be encapsulated in more
> "biological-like" structures? I noticed a difference between the work Marek
> has done and the current CLA implementation in terms of the discrete
> biological modeling?
>
> Cheers,
> David
>
>
> On Mon, Jul 14, 2014 at 12:43 PM, Chetan Surpur <[email protected]>
> wrote:
>
>>  David,
>>
>>  I'd also like to mention that I'm beginning work on a simplified
>> temporal memory (what you called sequence memory) implementation, that's
>> closer to the white paper description. This work should be completed in the
>> near future. However, you can still definitely port the existing temporal
>> memory (currently called TP) implementation to Java if you don't want to
>> wait for the simplified one.
>>
>>  - Chetan
>>
>>
>> On July 14, 2014 at 9:02:58 AM, Yuwei Cui ([email protected]) wrote:
>>
>>  Hi David,
>>
>> Each layer will be implementing sequence memory (we now call it temporal
>> memory). The goal is to predict future input based on past inputs. Spatial
>> pooling and sequence memory will not be combined. If you have read the
>> white paper, the spatial pooling occurs on the proximal dendrite, which can
>> drive cells into "active states", and sequence memory relies on inputs on
>> distal dendrite, which will turn cells into "predicted states"
>>
>> Our current working hypothesis is temporal pooling occurs both between
>> layer 4 and layer 3, and across regions. The outcome of temporal pooling is
>> more stable representation higher in the hierarchy. There will be an
>> emphasis on the stability soon, we already have a working temporal pooling
>> algorithm and will release it in the near future. The inter-regional
>> feedback seems a little further down the road.
>>
>> Yuwei
>>
>>
>> On Sun, Jul 13, 2014 at 3:12 PM, cogmission1 . <
>> [email protected]> wrote:
>>
>>> Hey Matt,
>>>
>>> I just watched the "Fireside chat" about Jeff's next TP ideas, and not
>>> to be argumentative (just looking to be as clear as I can be while watching
>>> things happen from the outside), but it appears as if he's going to
>>> introduce sequence memory, and temporal pooling between each layer? I think
>>> definitely between within layers 3 and 4? Also, it appears as if the SP and
>>> the Sequence Memory will be combined? Additionally, it looks like there
>>> will be some "inter-regional" feedback/predictions introduced between a
>>> subsequent region's layer 6 back into layer 5 of the previous layer. It
>>> maybe looks like some drastic overall changes may be occurring - maybe due
>>> to an effort toward emphasizing concepts of stability and inter-regional
>>> feedback?. Any news as to when we could see these changes rolled out - I
>>> can hardly wait...?  :-P
>>>
>>>
>>>
>>>
>>>  On Sat, Jul 12, 2014 at 12:08 PM, Matthew Taylor <[email protected]>
>>> wrote:
>>>
>>>> You can definitely dive in now. The new temporal memory work isn't
>>>> going to disrupt the current architecture at all, as far as I know.
>>>>
>>>> Start here: https://github.com/numenta/nupic/wiki/Learning-NuPIC
>>>>
>>>>  ---------
>>>> Matt Taylor
>>>> OS Community Flag-Bearer
>>>> Numenta
>>>>
>>>>
>>>>  On Sat, Jul 12, 2014 at 9:42 AM, cogmission1 . <
>>>> [email protected]> wrote:
>>>>
>>>>>  Hi Everyone,
>>>>>
>>>>> I'm at the point now where I would begin to delve into the NuPIC code
>>>>> more deeply (I want to port it to Java as a way to exercise my
>>>>> understanding too), but I was wondering if there is any point to it prior
>>>>> to the new TP/Sequence Memory implementation? Should I maybe wait?
>>>>>
>>>>> Thanks
>>>>>
>>>>> David
>>>>>
>>>>>  _______________________________________________
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>>>>>
>>>>
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>>
>>
>> --
>> --
>> Yuwei Cui
>>
>>  Algorithm Internship, Numenta Inc.
>>
>> PhD Candidate, Neuroscience and Cognitive Science
>>
>> University of Maryland, College Park, MD, 20742
>>
>> Homepage: http://terpconnect.umd.edu/~ywcui/
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