Military scientists in the US have revealed a series of experiments designs to create'supersoldiers' with enhanced mental capabilities. The successful tests used electrical brain stimulators to enhance the mental skills of soldiers. It is hoped the research could lead to treatments for drone operators, air crews and others in demanding roles. The successful tests at Wright-Patterson Air Force Base in Ohio used electrical brain stimulators to enhance the mental skills of soldiers. It is hoped the research could lead to treatments for drone operators, air crews and others in demanding roles.

An Australian man acquitted of murder last month after his Tinder date plummeted off a balcony to her death faced new criticism after he acknowledged in a TV interview that the woman had screamed "no" a reported 33 times before she fell. "Yeah, she was certainly trying to make a lot of noise," Gable Tostee commented in the interview, which aired on the Nine Network's "60 Minutes." Critics also lashed out after The Courier Mail claimed Tostee was paid a six-figure sum for the interview. A senior detective called it "disgusting". The detective continued, "There's a lot of anger among police about this. Of course we respect the court's decision to find him not guilty but for him to now do a paid interview after everything this poor girl's family has been through, is horrific."

As artificial intelligence gains popularity, designers will need to adapt. Here's how to get started. It seems like everyone wants to invest in artificial intelligence (AI). And it's not just the tech giants: USAA is using AI to protect its users from identity theft and Under Armour has connected its health app, MyFitnessPal, to IBM Watson so users can get a more thorough read of their health. AI is already a $15 billion dollar industry, according to the MIT Technology Review, with more than 2,600 companies developing their own tech, and the value of AI is reported to rise to over $70 billion by 2020. Because of AI's business opportunities, hundreds of designers in digital agencies, people who were taught to create products and services that live on the Internet, are starting to build physical products that interact with us, respond to our moods, and make decisions for us.

While most of us find it easy to recognise highly familiar faces such as those of family and friends, identifying faces that we have only briefly encountered is much more difficult. In fact, some research suggests that even experienced passport control officers make a large number of errors when matching faces to identity documents. Yet, recent work reveals that a small number of people may have extraordinary face recognition skills, outperforming typical people on a range of face recognition tasks. Bath researchers found that a small number of people may have extraordinary face recognition skills, outperforming typical people on a range of face recognition tasks. 'Super recognisers' have an uncanny ability to recognise faces, remembering people they have not seen for decades, who have substantially changed in appearance, and who they have only fleetingly encountered.

More recent deep lipreading approaches are end-to-end trainable (Wand et al., 2016; Chung & Zisserman, 2016a). All existing works, however, perform only word classification, not sentence-level sequence prediction. Studies have shown that human lipreading performance increases for longer words (Easton & Basala, 1982), indicating the importance of features capturing temporal context in an ambiguous communication channel. Motivated by this observation, we present LipNet, a model that maps a variable-length sequence of video frames to text, making use of spatiotemporal convolutions, an LSTM recurrent network, and the connectionist temporal classification loss, trained entirely end-to-end. To the best of our knowledge, LipNet is the first lipreading model to operate at sentence-level, using a single end-to-end speaker-independent deep model to simultaneously learn spatiotemporal visual features and a sequence model. On the GRID corpus, LipNet achieves 93.4% accuracy, outperforming experienced human lipreaders and the previous 79.6% state-of-the-art accuracy.

Want to take your programming skills to the next level? You've come to the right place! Machine Learning can sound daunting, but I'm here to show you how it can be a very fun and rewarding journey! This course streamlines your learning of the material and how you implement it in future projects. Machine learning brings together computer science and statistics to harness predictive power. It's a great skill to have and brings a whole new perspective to problem solving.

A Barbie doll that uses artificial intelligence to communicate interactively. Oren Etzioni, a well-known AI researcher, complains about news coverage of potential long-term risks arising from future success in AI research (see "No, Experts Don't Think Superintelligent AI is a Threat to Humanity"). After pointing the finger squarely at Oxford philosopher Nick Bostrom and his recent book, Superintelligence, Etzioni complains that Bostrom's "main source of data on the advent of human-level intelligence" consists of surveys on the opinions of AI researchers. He then surveys the opinions of AI researchers, arguing that his results refute Bostrom's. It's important to understand that Etzioni is not even addressing the reason Superintelligence has had the impact he decries: its clear explanation of why superintelligent AI may have arbitrarily negative consequences and why it's important to begin addressing the issue well in advance. Bostrom does not base his case on predictions that superhuman AI systems are imminent.

Media reports say an artificial intelligence (AI) system called MogIA, developed by Sanjiv Rai, an innovator based in Mumbai, has predicted that Donald Trump will win Tuesday's presidential elections in the United States. Unveiled in 2004, the system apparently got it right in the last three presidential elections. It also predicted that Trump and Hillary Clinton will be the nominees of the Republican and Democratic Parties respectively. Rai is quoted as saying that the algorithm got even better as it has "learnt" from the last few rounds. MogIA is named after Mowgli from The Jungle Book.

Merriam-Webster's two part definition of Artificial Intelligence or AI is "an area of computer science that deals with giving machines the ability to seem like they have human intelligence; the power of a machine to copy intelligent human behavior." Make no mistake about it, AI is very much the "in term" around the marketing water coolers. And as such there is no shortage of pieces being written espousing the benefits of AI on the world of marketing. Earlier this month Google unveiled Google Assistant, that was described as being most exciting new product announcement since the iPhone in 2007. According to Geek Time "It is an AI personal assistant that chats with you and can assist you with many tasks. You can chat or talk to the Assistant and it can bring you relevant information, send messages, book events, save reminders, change the lights, play content on your TV and many other actions. Google is working hard to bring more functionality to its Assistant, so you can expect its capabilities to improve over time."

Oren Etzioni, a well-known AI researcher, complains about news coverage of potential long-term risks arising from future success in AI research (see "No, Experts Don't Think Superintelligent AI is a Threat to Humanity"). After pointing the finger squarely at Oxford philosopher Nick Bostrom and his recent book, Superintelligence, Etzioni complains that Bostrom's "main source of data on the advent of human-level intelligence" consists of surveys on the opinions of AI researchers. He then surveys the opinions of AI researchers, arguing that his results refute Bostrom's. It's important to understand that Etzioni is not even addressing the reason Superintelligence has had the impact he decries: its clear explanation of why superintelligent AI may have arbitrarily negative consequences and why it's important to begin addressing the issue well in advance. Bostrom does not base his case on predictions that superhuman AI systems are imminent.