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Deep Learning Institute Workshop hosted by Dedicated Computing, NVIDIA and Milwaukee School of Engineering

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Dedicated Computing is co-hosting a Deep Learning Institute workshop in collaboration with NVIDIA and Milwaukee School of Engineering (MSOE). The workshop will take place at MSOE on April 13, 2017. Deep learning is a new area of machine learning that seeks to use algorithms, big data, and parallel computing to enable real-world applications and deliver results. Machines are now able to learn at the speed, accuracy, and scale required for true artificial intelligence. This technology is used to improve self-driving cars, aid mega-city planners, and help discover new drugs to cure disease.


*Applause* YouTube's caption upgrade shows how machine learning is helping the disabled

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FCC rules require TV stations to provide closed captions that convey speech, sound effects, and audience reactions such as laughter to deaf and hard of hearing viewers. YouTube isn't subject to those rules, but thanks to Google's machine-learning technology, it now offers similar assistance. YouTube has used speech-to-text software to automatically caption speech in videos since 2009 (they are used 15 million times a day). Today it rolled out algorithms that indicate applause, laughter, and music in captions. More sounds could follow, since the underlying software can also identify noises like sighs, barks, and knocks.


Using Big Data to analyse images and video better than the human brain – Concord Register

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Training neural network for object recognition (a car with front lights) in action. Improving traffic safety, better health services and environmental benefits – Big Data experts see a wide range of possibilities for advanced image analysis and recognition technology. "Advanced image recognition by computers is the result of a great deal of very demanding work. You have to mimic the way the human brain distinguishes significant from unimportant information," says Eirik Thorsnes at Uni Research in Bergen, Norway. Thorsnes heads a group in the company's Centre for Big Data Analysis focus area, which develops strategies for use of big data for research and commercial purposes.


*Applause* YouTube's caption upgrade shows how machine learning is helping the disabled

#artificialintelligence

FCC rules require TV stations to provide closed captions that convey speech, sound effects, and audience reactions such as laughter to deaf and hard of hearing viewers. YouTube isn't subject to those rules, but thanks to Google's machine-learning technology, it now offers similar assistance. YouTube has used speech-to-text software to automatically caption speech in videos since 2009 (they are used 15 million times a day). Today it rolled out algorithms that indicate applause, laughter, and music in captions. More sounds could follow, since the underlying software can also identify noises like sighs, barks, and knocks.


*Applause* YouTube's caption upgrade shows how machine learning is helping the disabled

#artificialintelligence

FCC rules require TV stations to provide closed captions that convey speech, sound effects, and audience reactions such as laughter to deaf and hard of hearing viewers. YouTube isn't subject to those rules, but thanks to Google's machine-learning technology, it now offers similar assistance. YouTube has used speech-to-text software to automatically caption speech in videos since 2009 (they are used 15 million times a day). Today it rolled out algorithms that indicate applause, laughter, and music in captions. More sounds could follow, since the underlying software can also identify noises like sighs, barks, and knocks.


*Applause* YouTube's caption upgrade shows how machine learning is helping the disabled

#artificialintelligence

FCC rules require TV stations to provide closed captions that convey speech, sound effects, and audience reactions such as laughter to deaf and hard of hearing viewers. YouTube isn't subject to those rules, but thanks to Google's machine-learning technology, it now offers similar assistance. YouTube has used speech-to-text software to automatically caption speech in videos since 2009 (they are used 15 million times a day). Today it rolled out algorithms that indicate applause, laughter, and music in captions. More sounds could follow, since the underlying software can also identify noises like sighs, barks, and knocks.


*Applause* YouTube's caption upgrade shows how machine learning is helping the disabled

#artificialintelligence

FCC rules require TV stations to provide closed captions that convey speech, sound effects, and audience reactions such as laughter to deaf and hard of hearing viewers. YouTube isn't subject to those rules, but thanks to Google's machine-learning technology, it now offers similar assistance. YouTube has used speech-to-text software to automatically caption speech in videos since 2009 (they are used 15 million times a day). Today it rolled out algorithms that indicate applause, laughter, and music in captions. More sounds could follow, since the underlying software can also identify noises like sighs, barks, and knocks.


Machine learning makes a human-centric society a reality

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Imagine being surrounded by technologies, and hardly being aware of them. For instance, a person walks into a room and without doing anything, the entire atmosphere is fine-tuned to his or her current mood or expectations. Measurements are taken, personal data is sensed and recorded, and the room adjusts to integrate with the person's countenance. All this occurs without turning a switch or adjusting an appliance--simply walk into the room. We're beginning to move in this direction, with recent advances in medical technology, with personal fitness devices, and with smart home systems.


Global Bigdata Conference

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News concerning Artificial Intelligence (AI) abounds again. The progress with Deep Learning techniques are quite remarkable with such demonstrations of self-driving cars, Watson on Jeopardy, and beating human Go players. This rate of progress has led some notable scientists and business people to warn about the potential dangers of AI as it approaches a human level. Exascale computers are being considered that would approach what many believe is this level. However, there are many questions yet unanswered on how the human brain works, and specifically the hard problem of consciousness with its integrated subjective experiences.


The Thinking Machine

AITopics Original Links

"When you are born, you know nothing." This is the kind of statement you expect to hear from a philosophy professor, not a Silicon Valley executive with a new company to pitch and money to make. A tall, rangy man who is almost implausibly cheerful, Hawkins created the Palm and Treo handhelds and cofounded Palm Computing and Handspring. His is the consummate high tech success story, the brilliant, driven engineer who beat the critics to make it big. Now he's about to unveil his entrepreneurial third act: a company called Numenta.