Why Google believes machine learning is its future | Tech - Ars Technica

Timothy B. Lee, Senior tech policy reporter says, Why we heard so much about machine learning at Google I/O this year.

Google CEO Sundar Pichai speaks during the Google I/O Developers Conference on May 7, 2019.

One of the most interesting demos at this week's Google I/O keynote featured a new version of Google's voice assistant that's due out later this year. A Google employee asked the Google Assistant to bring up her photos and then show her photos with animals. She tapped one and said, "Send it to Justin." The photo was dropped into the messaging app.

From there, things got more impressive.

"Hey Google, send an email to Jessica," she said. "Hi Jessica, I just got back from Yellowstone and completely fell in love with it." The phone transcribed her words, putting "Hi Jessica" on its own line.

"Set subject to Yellowstone adventures," she said. The assistant understood that it should put "Yellowstone adventures" into the subject line, not the body of the message.

Then without any explicit command, the woman went back to dictating the body of the message. Finally she said "send it," and Google's assistant did...

Google sees machine learning as its future 
Google's mission is to organize the world's information and make it accessible and useful. Google has made a lot of progress on the first half of that mission statement—it may have access to more data than any other company on the planet. But making the information more useful will require software that understands the information in a more sophisticated way—which is exactly what machine learning technology could do.

At I/O this week, Google sent a clear signal that Google's machine learning push is only getting started. The company is pouring resources into developing new chips, algorithms, and platforms because it believes these technologies have a lot of room to improve its existing products—or allow the creation of entirely new ones. And Google believes it has a unique combination of talent and resources to fully exploit those opportunities.
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Source: Ars Technica