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Archive for the ‘Amazon’ tag

Apr 14, 2019

Dr. Oliver Harrison MD, MPH, CEO, Telefonica Innovation Alpha — IdeaXme — Ira Pastor

Posted by in categories: aging, biotech/medical, business, computing, disruptive technology, genetics, health, information science, innovation, internet

Jun 15, 2017

What is a Drone? (Future A to Z)

Posted by in categories: automation, computing, drones, electronics, military, nuclear weapons, robotics/AI

Drones. Drone is a word you see pretty often in today’s pop culture. But drones seem to be an extremely diverse species. Even flightless vehicles are occasionally referred to as drones. So what exactly is a drone?

In this video series, the Galactic Public Archives takes bite-sized looks at a variety of terms, technologies, and ideas that are likely to be prominent in the future. Terms are regularly changing and being redefined with the passing of time. With constant breakthroughs and the development of new technology and other resources, we seek to define what these things are and how they will impact our future.

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May 12, 2016

Recommendation Engines Yielding Stronger Predictions into Our Wants and Needs

Posted by in categories: computing, disruptive technology, economics, information science, innovation, internet, machine learning, software

If you’ve ever seen a “recommended item” on eBay or Amazon that was just what you were looking for (or maybe didn’t know you were looking for), it’s likely the suggestion was powered by a recommendation engine. In a recent interview, Co-founder of machine learning startup Delvv, Inc., Raefer Gabriel, said these applications for recommendation engines and collaborative filtering algorithms are just the beginning of a powerful and broad-reaching technology.

Raefer Gabriel, Delvv, Inc.

Raefer Gabriel, Delvv, Inc.

Gabriel noted that content discovery on services like Netflix, Pandora, and Spotify are most familiar to people because of the way they seem to “speak” to one’s preferences in movies, games, and music. Their relatively narrow focus of entertainment is a common thread that has made them successful as constrained domains. The challenge lies in developing recommendation engines for unbounded domains, like the internet, where there is more or less unlimited information.

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