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machine learning

by   -   February 8, 2017

In this interview, Dr. Yueh-Hsuan Weng invites Prof. Ronald C. Arkin, Executive Committee Member of IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems, to share his insights on roboethics, with a focus on its technical aspects, military and caregiver applications..

by   -   February 1, 2017

Brad Knox talks bots_alive and a new form of character AI. Much like motion capture for scripted animation, this new technique may revolutionize how interactive characters are created, through observation of authentic human-generated behavior.

by   -   January 31, 2017

The webcast will take place on today from 9am-5:30pm EST and February 1st from 9am-5pm EST. Webcast participants are encouraged to submit questions for the presenters by e-mailing Michelle Schwalbe at mschwalbe@nas.edu who will read them out if time permits.

by   -   January 27, 2017
IEEE-main-AI-ethics-2016
Image: IEEE

On the 15th November 2016, the IEEE’s AI and Ethics Summit posed the question: “Who does the thinking?” In a series of key-note speeches and lively panel discussions, leading technologists, legal thinkers, philosophers, social scientists, manufacturers and policy makers considered such issues as:

  • The social, technological and philosophical questions orbiting AI.
  • Proposals to program ethical algorithms with human values to machines.
  • The social implications of the applications of AI.
by   -   January 26, 2017

With machine intelligence emerging as an essential tool in many aspects of modern life, Alan Winfield discusses autonomous sytems, safety and regulation.

by   -   January 16, 2017

machine-learning-2

In this fascinating animation from Oxford Sparks, we take a look at how statistics and computer science can be used to make machines that learn for themselves, without being explicitly programmed.

by   -   January 11, 2017

Join Professor Brian Cox as he brings together experts on AI and machine learning (including RoboHub’s own Sabine Hauert) to discuss key issues that will shape our technological future

by   -   December 16, 2016

System correlates recorded speech with images, could lead to fully automated speech recognition.

by   -   November 30, 2016

We need to do more than teach machines to learn. We need to overcome the barriers that separate machines from us – and us from them.

by   -   November 11, 2016

“Information extraction” system helps turn plain text into data for statistical analysis.

by   -   October 28, 2016

CSAIL’s new training technique would reveal the basis for machine-learning systems’ decisions.

by   -   October 21, 2016

westworld-promo-hbo

For a sci-fi fan like me, fascinated by the nature of human intelligence and the possibility of building life-like robots, it’s always interesting to find a new angle on these questions. As a re-imagining of the original 1970s science fiction film set in a cowboy-themed, hyper-real adult theme park populated by robots that look and act like people, Westworld does not disappoint.

by   -   October 17, 2016
MIT Media Lab Director Joi Ito (left), WIRED Editor-in-Chief Scott Dadich (center), and U.S. President Barack Obama confer in the Roosevelt Room of the White House. Photo: WIRED
MIT Media Lab Director Joi Ito (left), WIRED Editor-in-Chief Scott Dadich (center), and U.S. President Barack Obama confer in the Roosevelt Room of the White House. Photo: WIRED

When President Barack Obama agreed to guest-edit the November issue of WIRED, he selected MIT Media Lab Director Joi Ito for an exchange of ideas about artificial intelligence (AI). Their recent interview at the White House is featured in the latest online issue of WIRED, published on Oct. 12.

The one-on-one conversation, moderated by WIRED Editor-in-Chief Scott Dadich, ran the gamut of topics at the intersection of societal needs, ethics, and technology — from cybersecurity to self-driving cars; from the roles of government, industry, and academia to the lack of diversity in tech; from “moonshot” motivations to innovation at the margins; and from neurodiversity to Star Trek. All this was covered in the context of AI and extended intelligence (EI), which uses machine learning to augment human capabilities.

by   -   September 21, 2016
From L-R: PhD Fadel Adib, PhD Mingmin Zhao and Professor Dina Katabi demonstrating different 'emotions' like the picture. Credit: Jason Dorfman, MIT CSAIL
From L-R: PhD Fadel Adib, PhD Mingmin Zhao and Professor Dina Katabi demonstrating different ’emotions’ like the picture. Credit: Jason Dorfman, MIT CSAIL

By measuring your heartbeat and breath, this device from MIT’s Computer Science and Artificial Intelligence Lab can tell if you’re excited, happy, angry or sad
.

by   -   September 15, 2016
Images shows the aggregation behavior that the robots should learn ( final snapshot of an already aggregated system). Credit: Roderich Gross
Image shows the aggregation behavior that the robots should learn (final snapshot of an already aggregated system). Credit: Roderich Gross

We have developed a new machine learning method at the University of Sheffield called Turing Learning that allows machines to model natural or artificial systems.





Robotics Business Review
June 28, 2013


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