To Understand AI, We Must Understand Human Intelligence

Machines as Partners in Their Own Development

“May you live in interesting times”: it’s a famous back-handed blessing. And yet… here we are, living in interesting times. Technology is changing the way we live, work and play. Time to insight and frequency of innovation are being fueled by the ease of data sharing, collaboration and productivity.

The convergence of infotech and biotech is increasingly driving more disruptions in new industries and businesses. Underlying this phenomenon is the high availability and non-compromising security of the cloud. In his CloudFest 2019 keynote, Yuval Dvir, Head of Online Partnerships at Google Cloud, looked into the building blocks of the future organization, enabling everyone to build, innovate and scale via the cloud.

Now the Google Cloud Platform reaches over a billion people—not bad for a company that started as a Stanford University research project in 1995. Dvir said that Google has nurtured innovation, both in-house and through acquisition, since that first year: “When we think about scale and enabling that, we have a lot of experience!”

The best way to understand machine learning is to understand human intelligence, said Dvir. Telling a machine to recognize a dog’s face, for example, gets complicated when you start switching breeds and ages, or have images of dogs facing in different directions. Or dogs that look like rats. (Not that we’re judging anybody’s dog—just pointing out how difficult machine vision is.) Human intelligence has disadvantages, too, though, noted Dvir: humans can have a bad day. They can get angry or sad, which affects their cognition. You’d probably not want your surgeon to be furious when she’s about to make that first incision…

Find out more—and discover more insights into the world of the Cloud—in the CloudFest 2019 Trend Report. Download it for free!

Check out our Flickr Profile for more HQ pictures. To watch Yuval’s presentation click on the video:

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