Google's efforts to apply machine learning to search and voice recognition means that advances in these two areas are about to grown exponentially. In turn, this means that spontaneous inquiries via mobile devices will yield better and faster answers. It also means that these answers and anticipated follow up information or related information will be delivered with greater depth and accuracy.
But Google can't anticipate every question because it won't always know what's most relevant just by knowing your physical location or who's nearby. This makes the ability to frame meaningful, relevant questions a primary skill for the 21st century. Questions that lead to actions that in turn lead to positive, "Empowered Wealth Mindset" outcomes are empowering questions.
Computer Brain Escapes Google’s X Lab to Supercharge Search | Wired Enterprise | Wired.com
Andrew Ng built models for processing the human voice and Google StreetView images. The company quickly recognized its potential and shuffled it out of X Labs and into the Google Knowledge Team. And now this type of machine learning could shake up everything from Google Glass, to Google Image Search to the company’s flagship search engine.
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