While it's not a complete fix, the new AI system, developed by Hisham Daoud and Magdy Bayoumi of the University of Louisiana at Lafayette, is a major leap forward from existing prediction methods. Currently, other methods analyze brain activity with an EEG (electroencephalogram) test and apply a predictive model afterwards. The new method does both of those things at once, with the help of a deep learning algorithm that maps brain activity and another that can predict the electrical channels lighting up during a seizure. It'll still be some time before this technique will be available for widespread use -- the team is now working on a custom chip that can help process the necessary algorithms -- but it could be life-changing news for patients with epilepsy.

While it's not a complete fix, the new AI system, developed by Hisham Daoud and Magdy Bayoumi of the University of Louisiana at Lafayette, is a major leap forward from existing prediction methods. Currently, other methods analyze brain activity with an EEG (electroencephalogram) test and apply a predictive model afterwards. The new method does both of those things at once, with the help of a deep learning algorithm that maps brain activity and another that can predict the electrical channels lighting up during a seizure. It'll still be some time before this technique will be available for widespread use -- the team is now working on a custom chip that can help process the necessary algorithms -- but it could be life-changing news for patients with epilepsy.

Called "the restless genius" by The Wall Street Journal and "the ultimate thinking machine" by Forbes magazine, he was selected as one of the top entrepreneurs by Inc. magazine, which described him as the "rightful heir to Thomas Edison." PBS selected him as one of the "sixteen revolutionaries who made America." Ray was the principal inventor of the first CCD flat-bed scanner, the first omni-font optical character recognition, the first print-to-speech reading machine for the blind, the first text-to-speech synthesizer, the first music synthesizer capable of recreating the grand piano and other orchestral instruments, and the first commercially marketed large-vocabulary speech recognition. Among Ray's many honors, he received a Grammy Award for outstanding achievements in music technology; he is the recipient of the National Medal of Technology, was inducted into the National Inventors Hall of Fame, holds twenty-one honorary Doctorates, and honors from three U.S. presidents. Ray has written five national best-selling books, including New York Times best sellers The Singularity Is Near (2005) and How To Create A Mind (2012). He is Co-Founder and Chancellor of Singularity University and a Director of Engineering at Google heading up a team developing machine intelligence and natural language understanding.

Technological Singularity is coming in 2040. Should we be scared of Artificial Intelligence? He did his PhD in Paris at Universite Pierre et Marie Curie, then became a Research Fellow and a lecturer at the University of Oxford. After returning to Poland, he took up research on artificial intelligence and mathematics, and founded a technological group ulam.ai, Within the group he co-founded multiple AI ventures ranging from logistics to the fashion market, and using cutting-edge technologies.

Zero-shot learning (ZSL) aims at understanding unseen categories with no training examples from class-level descriptions. To improve the discriminative power of zero-shot learning, we model the visual learning process of unseen categories with inspiration from the psychology of human creativity for producing novel art. We relate ZSL to human creativity by observing that zero-shot learning is about recognizing the unseen and creativity is about creating a likable unseen. We introduce a learning signal inspired by creativity literature that explores the unseen space with hallucinated class-descriptions and encourages careful deviation of their visual feature generations from seen classes while allowing knowledge transfer from seen to unseen classes. With hundreds of thousands of object categories in the real world and countless undiscovered species, it becomes unfeasible to maintain hundreds of examples per class to fuel the training needs of most existing recognition systems.

Weekends are time when things slow down a little. Your weekend shouldn't be two more regular workdays. Take time to refresh yourself. Take time for something different. Take time for some of that reading you can't find time for during the week.

I watch bad movies, a pastime and a passion I have long shared with my father. When I was a child, we would sit on one of a series of couches scavenged from yard sales or curbsides, eating microwave popcorn while watching, say, Teenagers from Outer Space (1959) or Zontar, the Thing from Venus (1962). My father would set the VCR to tape movies like these in the middle of the night from the sorts of TV channels that programmed them, with palpable desperation, between reruns of The Incredible Hulk and camcordered ads for local mattress-store chains. Amusement, like couches, had to be taken where found. Ours was neither a wholly singular nor widely shared hobby. A few years later, the television series Mystery Science Theater 3000 made text of this subtext: Its framing device consisted of a man and two robots cracking wise over the soundtrack as bad movies played onscreen. It was important that the man wasn't simply alone, and that, at the same time, he was somewhat isolated: a Crusoe-like figure alone on a satellite, forced to build himself a minisociety of talking robots. Watching bad movies was a social yet marginal activity; it was a way of watching that orbited the normal enjoyment of film. In the canon of bad films, Ed Wood's Plan 9 from Outer Space (1959) is the anticlassic. On the satellite where bad-movie watchers gather, it is our Citizen Kane, our Seven Samurai, and in the ages before Amazon, you had to really search to find it.

Through several waves of downhills and uphills in the past decades, Artificial Intelligence (AI) has now evolved into a must have new technology or tool in every domain. Furthermore, with the advent of powerful GPU, AI-related research or AI-based applications have sprouted in every corner of the world. Originated from pure internet connectivity the Internet of Things (IoT) has become a structure that can collect every piece of data from physical devices, daily activities, images or video into a data reservoir. As a result, tons of data are automatically generated into an enterprise database in a single day. This creates continuing demands on applying AI, IoT, and big data analytics to extract juicy contents from the huge databases.

Event Description: In in our "cyber" age how do we do sex, love and reproduction? This seminar is an interdisciplinary dialogue among psychoanalysts, critical and cultural thinkers, writers and those interested in how our age of technology, consumer (re)production, including pornography, and mass social media has affected what psychoanalysts call "the subject," which is how each and every one of us is uniquely human. The seminar takes place over 2 days, commencing on Friday evening with a panel of invited speakers who will give short presentations, followed by audience discussion. The seminar continues on Saturday morning with the invited keynote speaker, Isabel Millar (see talk and bio below). This is followed by a roundtable discussion with the Friday evening panellists and the invited speaker, and the seminar will conclude with an audience Q&A session.