All of these are great suggestions, but I would have to say that Karthik's
#2 suggestion resonates most strongly for me. A demonstration of NuPIC with
a compelling application. A use case that showcases in certain terms what
NuPIC can do that no other approach can do.

- Jeff


On Mon, Jan 6, 2014 at 6:49 PM, karthikeyan S <[email protected]>wrote:

> Hi
>
> Just my 2 cents.
>
> 1. As others mentioned, complete c++  implementation
> 2. Demonstration of NuPIC with a compelling application by the community.
> I think instead of competing with other ML techniques we should try and
> exploit what's unique about NuPIC - Which, I think, is mimicking human
> thought process. Other ML techniques are fairly problem specific and we
> have a slight disadvantage competing with them. And more importantly there
> is not much point in competing since there are already tools to solve
> *those* specific problems.
> We don't want to be an yet-another.
> An example of what I mean by mimicking human thought process is math and
> physics.
>
> Math - if we "teach" NuPIC  arithmetic will it learn?
> Can it add 2+2 without an ALU.
> Physics - If NuPIC constantly gets input about its environment through its
> sensors will it form any laws or theories from it, at some point. The
> current anomaly detection (something didn't comply with nupic's internal
> theory of its environment)is close to this. But can we stretch it?
>
> As they say, sometimes it's easier to do the hard things and it's more fun.
>
> Just my 2 cents.
>
> Thanks
> Karthik
> On Jan 6, 2014 6:03 PM, "stewart mackenzie" <[email protected]> wrote:
>
>> - a core c++ implementation stripped of network manager, that consists
>> of encoders, regions and classifiers. (the community and grok can
>> extend this repo with customized regions etc forming a repo with a
>> whole bunch of different tools)
>> --- python completely stripped out
>> --- nupic-core should have no library dependencies.
>> --- temporal pooler implemented in c++
>> - each component (encoder, region classifier) knows how to read the
>> data stream coming into it. whether it be 1D or 2D etc (hopefully
>> using UBF - by J.Armstrong)
>> - CMake support.
>> - multi-time interval predictions (ie what the next 5 mins predict?
>> then what does the next 20 hours predict?)
>> - an implementation that is _easy_ to create language bindings for.
>>
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>> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
>>
>
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>
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