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Lectures

Ken goldberg 242x262 ks photo
May 31, 2013 20:00 Forecast For Tomorrow – the technology of the near future
Ken Goldberg
Where Will Robots Learn?

On May 31 the Digital October Center begun a brand-new collaborative effort with IBS: a cycle of lectures focused on tomorrow’s remote technology. The creator of the first robot with a web interface, the UC Professor Ken Goldberg discussed cloud robotics, something that is bringing us closer to the day when everyone will have their own personal robot.

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July 17, 2013 20:00 Forecast For Tomorrow – the technology of the near future
Seth Lloyd
Thinking of the Universe as a Quantum Computer

He believes that the universe is one gigantic computer, and that therefore there is somebody behind it. On July 17 Knowledge Stream  hosted a pioneer in the creation of quantum computers, MIT Professor Seth Lloyd.

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September 23, 2013 20:00 Forecast For Tomorrow – the technology of the near future
Brian Kennedy
Aging 2.0

Today, he works on extending the lives of mice, but, once he’s done with these model animals, it will be humankind’s turn. On September 23rd, the Digital October Center hosted a lecture from Brian Kennedy, the director of the first US institution to specialize in anti-aging research.

Stephen wolfram 242x262 ks photo
November 25, 2013 20:30 Forecast For Tomorrow – the technology of the near future
Stephen Wolfram
A New Kind of Science

On November 25th, ‘little Einstein’ Stephen Wolfram offered a lecture at the Digital October Center on a project that has been compared with Google and that is already being used by Apple, as well as the unique language in which the project was written.

Viktor mayer sch nberger 242x262 ks photo
December 02, 2013 20:00 Forecast For Tomorrow – the technology of the near future
Viktor Mayer-Schonberger
Big Data Revolution

Why do orange cars break down less frequently than other kinds? On December 2nd, the Oxford Internet Institute-based coauthor of Big Data, offered a lecture at the Digital October Center in which he discussed how 'raw' masses of data can help us to find the ideal solutions to business, industrial, and everyday problems.