PC Magazine July 2017

Machine Learning Engine to help customers train models. We help customers
execute on data with access to Kaggle’s community of 800,000-plus active data
scientists. Finally, you need the talent to be there, so on the research side of
things, we have the Brain Residency Program to train engineers on complex ML
curriculum. We see these as the building blocks to help customers build
intelligent applications.”
This all feeds into the open-source community and third-party ecosystem that
Google is building around its AI technology. The company even announced a
ML startup competition earlier this year, which awards up to $500,000 in
investment to ML startups. Uribe talked about some of the innovative
applications he’s already seen of Google’s technology and where other
possibilities might lie.
“Let’s say you’re a customer service analytics company. Think about a speech
API to transcribe the content of calls and then sentiment analysi s to improve
the quality of your customer service,” said Uribe. “Use the vision API to take a
photo of a street sign in a foreign country and then the translation API to
translate that content in real time through an app experience. It’s not just about
increasing efficiency; it’s about creating new and unique user experiences.”
Uribe sees tools such as TensorFlow as the great enabler for large-scale ML
adoption in the marketplace. Not only have these technologies become core to
what Google is and how it approaches product development, but also, Uribe
believes, widely available ML technology will help optimize businesses, open
new revenue streams, and invent a new class of intelligent apps.
“Think of it like a new industrial revolution,” said Uribe. “We’re seeing these
tools enable orders-of-magnitude increases in efficiency and experiences you’ve
never seen before. It’s amazing to see how startups are applying it. Look at the
cucumber farmer in Japan. He used TensorFlow to build a model for classifying
and sorting cucumbers based on patterns, size, textures, etc., and then built
specialized hardware to execute it. That level of democratization is incredible to
see, and we’ve barely scratched the surface.”
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