University of Colorado Boulder neuroscientists have combined machine learning and neuroscience to create a brain-inspired computer that can tell the difference between sad and happy images. "Machine learning technology is getting really good at recognizing the content of images -- of deciphering what kind of object it is," said senior author Tor Wager, who worked on the study while a professor of psychology and neuroscience at CU Boulder. "We wanted to ask: Could it do the same with emotions? The experiment is an important development in "neural networks," computer systems modeled after the human brain. It also highlights that what we see could have a more severe impact on our emotions than we might think. "A lot of people assume that humans evaluate their environment in a certain way and emotions follow from specific, ancestrally older brain systems like the limbic system," said lead author Philip Kragel, a postdoctoral research associate at the Institute of Cognitive Science. "We found that the visual cortex itself also plays an important role in the processing and perception of emotion." For their study, the researchers used a neural network called AlexNet designed to enable computers to recognize objects and retooled it to predict how a person would feel when they see a certain image using previous research. The researchers dubbed the new network EmoNet and proceeded to show it 25,000 images. The computer was then asked to categorize them into 20 sections such as craving, sexual desire, horror, awe, and surprise. The program was found to better at recognizing some emotions better than others. Craving or sexual desire, for instance, were categorized with more than 95 percent accuracy. However, more nuanced discreet emotions such as confusion, awe, and surprise were harder to pinpoint. EmoNet proved very reliable in rating the intensity of images. It was also rather good at rating brief movie clips. When asked to categorize them as romantic comedies, action films or horror movies, it got it correct 75% of the time. The researchers then used 18 human subjects and had a functional magnetic resonance imaging (fMRI) machine measure their brain activity when they were shown the same 112 images as EmoNet. Surprisingly, the neural network patterns were the same for human and computer. "We found a correspondence between patterns of brain activity in the occipital lobe and units in EmoNet that code for specific emotions.

For decades, Hava Siegelmann has explored the outer reaches of computing with great curiosity and great conviction. The conviction shows up in a belief that there are forms of computing that go beyond the one that has dominated for seventy years, the so-called von Neumann machine, based on the principles laid down by Alan Turing in the 1930s. She has long championed the notion of "Super-Turing" computers with novel capabilities. And curiosity shows up in various forms, including her most recent work, on "neuromorphic computing," a form of computing that may more closely approximate the way that the brain functions. Siegelmann, who holds two appointments, one with the University of Massachusetts at Amherst as professor of computer science, and one as a program manager at the Defense Advanced Research Projects Agency, DARPA, sat down with ZDNet to discuss where neuromorphic computing goes next, and the insights it can bring about artificial intelligence, especially why AI succeeds and fails.

Coming soon to Alexa speakers, X2 Games and Atari founder Nolan Bushnell will introduce'St. If you own an Amazon Echo, Google Home or other "smart speaker," you're likely aware you can use your voice to play music, order a product, and control your smart home gadgets. But you might not know you can also use your voice to play games, whether you're home alone or with family or friends. "There has never been a more natural way to communicate with technology than using your voice," says Katherine Prescott, founder and editor of VoiceBrew, a digital media company dedicated to helping people get the most out of Alexa, with articles, blog posts, and email newsletters. What dog is the one for you?: How I Met My Dog will tell you RCA's 100th anniversary: How a Russian immigrant changed our communication methods forever Smart speaker usage is growing.

Microsoft and digital energy management and automation solution provider Schneider Electric have partnered to launch AI for Green Energy, a new accelerator programme for Microsoft's AI Factory. Through the programme, Microsoft and Schneider will help start-ups use artificial intelligence (AI) to transform the energy sector in Europe, decreasing consumption and increasing energy efficiency. These entrepreneurs will be able to learn from the technical and business expertise of the two companies during a three-month acceleration period. "We are delighted to leverage our ecosystem of partners to serve the most important causes to society, thanks to the start-ups of tomorrow," said Agnès Van de Walle, director of Microsoft's One Commercial Partner group. "Schneider Electric will bring in-depth expertise and personalised support, accelerating innovation across the energy sector."

Washington, DC - These days, the latest developments in artificial intelligence (AI) research always get plenty of attention, but an AI researcher at the U.S. Naval Research Laboratory believes one AI technique might be getting a little too much. Ranjeev Mittu heads NRL's Information Management and Decision Architectures Branch and has been working in the AI field for more than two decades. "I think people have focused on an area of machine learning--deep learning (aka deep networks) -- and less so on the variety of other artificial intelligence techniques," Mittu said. "The biggest limitation of deep networks is that a complete understanding of how these networks arrive at a solution is still far from reality." Deep learning is a machine learning technique that can be used to recognize patterns, such as identifying a collection of pixels as an image of a dog.

They grabbed his jaw to force his head in front of his iPhone. It all failed: Mr. Cheung had disabled his phone's facial-recognition login with a quick button mash as soon as they grabbed him. As Hong Kong convulses amid weeks of protests, demonstrators and the police have turned identity into a weapon. The authorities are tracking protest leaders online and seeking their phones. Many protesters now cover their faces, and they fear that the police are using cameras and possibly other tools to single out targets for arrest.

VI's vary greatly depending on how they are deployed. Virtual intelligence (VI) programs that make intelligent decisions based on the virtual environments built around them, or merely interact with their environments in some manner. Below are the Critical Components to Creating a VI Platform. Artificial Intelligence is a technological term which deals with machines demonstrating intelligence like humans. Artificial intelligence makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.Most common day to day examples of AI is voice assistants (Siri, Alexa), self-driving cars, text and other predictions, smart email filtering.

A lot of startups in the San Francisco Bay Area claim that they're planning to transform the world. San-Francisco-based, Elon Musk-founded OpenAI has a stronger claim than most: It wants to build artificial general intelligence (AGI), an AI system that has, like humans, the capacity to reason across different domains and apply its skills to unfamiliar problems. Today, it announced a billion dollar partnership with Microsoft to fund its work -- the latest sign that AGI research is leaving the domain of science fiction and entering the realm of serious research. "We believe that the creation of beneficial AGI will be the most important technological development in human history, with the potential to shape the trajectory of humanity," Greg Brockman, chief technology officer of OpenAI, said in a press release today. Existing AI systems beat humans at lots of narrow tasks -- chess, Go, Starcraft, image generation -- and they're catching up to humans at others, like translation and news reporting.

On 18 July, the House of Commons select committee on science and technology published an assessment of the work of the biometrics commissioner and the forensic science regulator. My guess is that most citizens have never heard of these two public servants, which is a pity because what they do is important for the maintenance of justice and the protection of liberty and human rights. The current biometrics commissioner is Prof Paul Wiles. His role is to keep under review the retention and use by the police of biometric material. This used to be just about DNA samples and custody images, but digital technology promises to increase his workload significantly.

Blink twice to zoom in. A new soft lens can be controlled by your eye movements, pivoting left and right as you look around and zooming in and out when you blink. The human eyeball is electric – there is a steady electrical potential between its front and back, even when your eyes are closed or in total darkness. When you move your eyes to look around or blink, the motion of the electrical potential can be measured.