3 ms·
i've been reading about sparse distributed memory and numenta/nupid for the past few days. It sounds very interesting but I haven't actually seen any demos that
by dharma1 12y ago
i've been reading about sparse distributed memory and numenta/nupid for the past few days. It sounds very interesting but I haven't actually seen any demos that show it solving things better than other avenues (like deep learning) in AI at the moment. Are you using it for anything?
- p1esk 12y agoNumenta's primary goal is not solving practical problems (such as those typical in ML field) - it's understanding how neocortex processes information. They believe that once they understand enough, they will be able to build a system that works like a brain (and then it will be able to solve any problems that a brain can solve). Obviously, this is work in progress. They might have a breakthrough in two years, or in two decades, but the point is that not many others are trying to do that at all (definitely no one in ML field).
- dharma1 12y agoWhat do you think about the hardware centric approaches like http://news.stanford.edu/news/2014/april/neurogrid-boahen-engineering-042814.html http://news.stanford.edu/news/2014/april/neurogrid-boahen-en...
- p1esk 12y agoThose are interesting projects, and sooner or later we will need specialized hardware to speed up AI algorithms. However, today AI development is not constrained by computing power, at least not directly. If you run IBM Watson algorithms 100 times faster, it won't be much smarter. In ML, we need better algorithms. In AI, we need better theories. Brain simulations, such as Human Brain Project, is where we need more computing power. That is the field where 100 times faster can lead to major breakthroughs.