Aseem, A bit of friendly unsolicited advice: if you're taking the class, learn what they're teaching, even if it seems obsolete or irrelevant. This is a good general rule, but especially for this case: I think the CLA's a really interesting model, but it is after all another in a long line of brain-inspired learning algorithms. I suspect it gets some things right that others have missed, and I'm excited to see where it will lead over the next 10-20 years, but it is after all a stripped-down model built on some of what 5, maybe 10% of the cells in neocortical gray matter are doing--the easy ones to monitor. It's almost certainly not the whole story of building an intelligent system.
Even in a CLA system, as things start getting complicated, I suspect there will be moments of "oh, that part's just a high-D-distribution-with-sparse-covariances/regression problem/linear classifier, I can throw a PGM/Gaussian process/SVM at it to save a bunch of cycles." Sometimes it will be useful to have some solid ML and stats history and theory because you need to know what a part of a CLA-based system is and is not. Deploy your cynicism late if at all. - Kevin p.s. of course this advice is more for past-undergrad-me, and to some extent to today-still-making-the-same-mistakes-me, than for you, not that I'm sure I would have followed it if I could have heard it way back when. bonus advice for long-ago-me: pay more attention during statistical mechanics. you'll want that later. p.p.s. sorry to all for the slight digression from usual topics on the list. I'll behave. On Sep 12, 2013, at 6:10 PM, Aseem Hegshetye wrote: > Hi, > I have grown up reading ON INTELLIGENCE and neuroscience and jeff hawkins has > shown how artificial perceptrons are incapable of achieving what our brain > does. Its weird to sit in a machine learning class which always starts with > gradient descents and then some classifying algorithms. > And everyones busy taking down notes to score good grades. > > Aseem Hegshetye > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org ________________________________ The material in this message is private and may contain Protected Healthcare Information (PHI). If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ nupic mailing list [email protected] http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
