Hi Dennis, My mistake, yes, that's the right course.
Regards, Fergal On Thu, Nov 14, 2013 at 10:57 PM, Dennis Stark <[email protected]> wrote: > > The HTM is Jeff's over-arching theory of how the neocortex works. The > CLA is a very detailed model (suitable for implementation in software right > now) which describes how Layer 3 of a single region recognises spatial > patterns and learns sequences of those patterns. The CLA (and NuPIC) > encompasses three of the six principles of HTM, namely Sparse Distributed > Representations, Online Learning, and Sequence Memory. Hierarchy, Attention > and Motor Function are TBD right now! > > Because of the lack of hierarchy in NuPIC, it cannot compete with other > "some neuroscience" approaches such as Deep Belief Nets for applications > such as yours. However, these other approaches lack the temporal sequence > learning which is one of the core attributes of NuPIC. > > Thank you for the explanation! This is exactly why I'm writing a small > library that enables hierarchy (c++ at the moment for speed). Basically I > have created some code that is relatively fast and mimics CLA in some > respect (I don't have dutyCycle watcher for boosting at the moment, and > it's currently does only spacial pooling). The reason I do this to begin > with, is for easier translation to GPU, and a little glitch of mine - for > me it's much easier to write something myself then understand how a huge > library works. It is only when I fail to achieve the result I turn back to > the library, but by then I already understand everything. > > > For categorisation of static images, I would look at Geoff Hinton's work > (he has a great, and free, course on Udemy). The system he describes looks > very much like what you're doing. > > I found one on Coursera > https://class.coursera.org/neuralnets-2012-001/lecture/index Is this the > one? Looks like it has invaluable information there! > > > Time-based learning in NuPIC would involve providing a region with a > varying input and have it learn the invariance. This would not be done by > giving it a set of real-world, unrelated images, but perhaps by using 3D > rendering software to feed it a realistic feed of successive, semantically > consistent frames, just like what we get when we perceive the world. I > still think we'll have to wait until we have a hierarchy of CLA's before we > get general vision happening here. > > 3D rendering is a great idea! > > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > -- Fergal Byrne, Brenter IT <http://www.examsupport.ie>http://inbits.com - Better Living through Thoughtful Technology e:[email protected] t:+353 83 4214179 Formerly of Adnet [email protected] http://www.adnet.ie
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