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Posts Tagged ‘deep 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 [...]

Common sense about deep learning

I regularly build deep learning models for natural language processing and today I gave one a try that has been the leader in the Stanford Question Answering Dataset (SQuAD).  This one is a impressive NLP platform built using PyTorch.  But it’s still missing the big picture (i.e., it doesn’t “know” much). Generally,  NLP systems that [...]

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 [...]

It’s hard to reckon nice English

The title is in tribute to Raj Reddy’s classic talk about how it’s hard to wreck a nice beach. I came across interesting work on higher order and semantic dependency parsing today: Turning on the Turbo: Fast Third-Order Non-Projective Turbo Parsers. Priberam: A turbo semantic parser with second order features So I gave the software [...]

Smart Machines And What They Can Still Learn From People – Gary Marcus

This is a must-watch video from the Allen Institute for AI for anyone seriously interested in artificial intelligence.  It’s 70 minutes long, but worth it.  Some of the highlights from my perspective are: 27:27 where the key reason that deep learning approaches fail at understanding language are discussed 31:30 where the inability of inductive approaches [...]

Deep Learning, Big Data and Common Sense

Thanks to John Sowa’s comment on LinkedIn for this link which, although slightly dated, contains the following: In August, I had the chance to speak with Peter Norvig, Director of Google Research, and asked him if he thought that techniques like deep learning could ever solve complicated tasks that are more characteristic of human intelligence, [...]

Deep Parsing vs. Deep Learning

For those of us that enjoy the intersection of machine learning and natural language, including “deep learning”, which is all the rage, here is an interesting paper on generalizing vector space models of words to broader semantics of English by Jayant Krishnamurthy, a PhD student of Tom Mitchell at Carnegie Mellon University: Krishnamurthy, Jayant, and [...]