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Posts under ‘Machine Learning’

Natural Intelligence

Deep natural language understanding (NLU) is different than deep learning, as is deep reasoning.  Deep learning facilities deep NLP and will facilitate deeper reasoning, but it’s deep NLP for knowledge acquisition and question answering that seems most critical for general AI.  If that’s the case, we might call such general AI, “natural intelligence”. Deep learning [...]

Ending Back Pain with AI

A nationwide physical therapy business is renowned for eliminating chronic pain.  One unique aspect of this business is that it eliminates pain not by manipulation but by providing clients with expertly selected sequences of exercises that address problems in their functional anatomy.  In effect, the business helps people fix themselves and teaches them to maintain [...]

Simple, Fast, Effective, Active Learning

Recently, we “read” ten thousand recipes or so from a cooking web site.  The purpose of doing so was to produce a formal representation of those recipes for use in temporal reasoning by a robot. Our task was to produce ontology by reading the recipes subject to conflicting goals.  On the one hand, the ontology [...]

Of Kalman Filters and Hidden Markov Models

This provides some background relating to some work we did on part of speech tagging for a modest, domain-specific corpus.  The path is from Hsu et al 2012, which discusses spectral methods based on singular value decomposition (SVD) as a better method for learning hidden Markov models (HMM) and the use of word vectors instead [...]

Artificially Intelligent Physical Therapy

Over the last 25 years we have developed two generations of AI systems for physical therapy.  The first was before the emergence of the Internet, when Windows was 16 bits.  There were no digital cameras, either.  So, physical therapists would take Polaroid pictures; anterior and left and right lateral pictures or simply eyeball a patient [...]