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Wednesday, October 16, 2019

NELL and Machine Learning

In a re-examination of 'machine learning', the broader definition that includes but is not restricted to deep learning.   I recalled our look the CMU effort called NELL,  Never Ending Language Learner'.  At the time it was insufficiently oriented to our needs, any information about the actual use of its learning?  Here is the intro to it on the Carnegie Mellon site.

NELL: The Computer that Learns,   Professor Tom Mitchell

Tom Mitchell's two daughters are grown but watching his newest 'baby' learn to read is an unprecedented achievement.

Professor Mitchell leads the team that developed the Never-Ending Language Learner – NELL – a computer system that, over time, is teaching itself to read and understand the web.
"I've been interested for many, many years in how machines learn because I'm also interested in how humans learn," explained Mitchell, who heads Carnegie Mellon's Machine Learning department – the first and only department of its kind in the world. "NELL comes naturally out of that. The current machine-learning algorithms are very different in style than how you and I learn. They analyze a single data set, output an answer, and then you turn them off. That's not like us at all! The idea of NELL is to capture a style more like the on-going learning of humans."

Understanding language – the way humans do – depends on both context and background knowledge gained over time. So NELL scans the web – attempting to "read" hundreds of millions of web pages on a fact-finding mission.

For example, the repeated combination of a phrase like "New York City Marathon" in combination with other words has taught NELL to learn that it's a "race" and a "sports event." ...  "

See also:
Project website:  http://rtw.ml.cmu.edu/rtw/
On twitter:           https://twitter.com/cmunell

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