Watson knows the definition of “brake” –
the device that stops something; or the act of stopping something. But what
about the hundreds of ways that the car-driving public describes problems with
their brakes to a mechanic? The brakes might “squeal,” or “judder.” Or maybe
they’re “soft.” All of those descriptors could indicate a different issue that
aren’t understood by a computer. Until now. Thanks to IBM Research’s Dan Gruhl,
Watson can help the mechanic and the car manufacturer pinpoint the problem,
based on common, even slang descriptions.
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| Dan Gruhl at 2015 Cognitive Colloquim |
Watson Concept Expansion, on demonstration
at the Cognitive Computing Colloquium in San Francisco, expanded the cognitive
system’s dictionary of related words, concepts, euphemisms, and colloquialisms
to better-understand context across any industry or field. Dan’s team feeds
Watson unstructured data from blogs and news articles, to Twitter’s firehose,
among other sources.
Then, because this is a human-machine partnership, meant
to augment one another’s intelligence, the human expert begins to tell Watson
what is relevant (squeaky brakes), and not (I need a break). While Watson
gathers and organizes by relevance online documents and discussions about how
to fix various kinds of brake problems.
“It's a game of patterns. If I start with
'apple' and 'blackberry' in the tool, it needs to interact with me a few times
before it realizes I am talking about fruits and not cell phone manufacturers.”
Dan said.
That context from such a wide and diverse
source that only Watson could gather and comprehend (in seconds) gives domain
experts a new way to understand their industry, brand, or product. Try it out
on Bluemix, now.
Labels: bluemix, cognitive computing, cognitive era, IBM Watson, machine learning
