When we want to start computing at biological scales and speeds – evolving today’s practical machine learning forward towards long-deferred visions of a more “artificial intelligence” – we’ll need to take advantage of new forms of hardware that transcend the strictly digital.

Digital computing infrastructure, based on switching digital bits and separating the functions of persisting data from processing, is now facing some big hurdles with Moore’s law. Even if there are a couple of magnitudes of improvement yet to be squeezed out of the traditional digital design paradigm, it has inherent limits in power consumption, scale, and speed. For example, there simply isn’t enough power available to meet the desires of those wishing to reach biological scale and density with traditional computing infrastructure, whether evolving artificial intelligence or more practically scaling machine learning to ever larger big data sets.

Read the entire article directly on Taneja Group website at: http://tanejagroup.com/news/blog/blog-systems-and-technology/is-it-still-artificial-intelligence-knowm-rolls-out-adaptive-machine-learni#.VZ1afUWtapc

Is It Still Artificial Intelligence? Knowm Rolls Out Adaptive Machine Learning Stack
Taneja Group
Mike Matchett

Taneja Group

Taneja Group

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