Scientists have used a unique computational technique that sifts through big data to identify a subset of concussion patients with normal brain scans, who may deteriorate months after diagnosis and develop confusion, personality changes and differences in vision and hearing, as well as post-traumatic stress disorder. This finding, which is corroborated by the identification of molecular biomarkers, is paving the way to a precision medicine approach to the diagnosis and treatment of patients with traumatic brain injury. Investigators headed by scientists at UC San Francisco and its partner institution Zuckerberg San Francisco General Hospital and Trauma Center (ZSFG) analyzed an unprecedented array of data, using a machine learning tool called topological data analysis (TDA), which "visualizes" diverse datasets across multiple scales, a technique that has never before been used to study traumatic brain injury. TDA, which employs mathematics derived from topology, draws on the philosophy that all data has an underlying shape. It creates a summary or compressed representation of all the data points using algorithms that map patient data into a multidimensional space.

It's safe to say the terms artificial intelligence (AI) and data science to say these terms have firmly made their way from the big screen and into the real world. There's never been more data at people's fingertips – and our enthusiasm and ability to make use of it grows every day. With more data potential, the next logical step for businesses is to focus on how we navigate through it, and understand how machines can help us use it. Every part of an organisation's infrastructure, no matter what sector, creates data – from metrics on machine performance, to software and customer interactions. Everyone has heard the hype that surrounds AI and how it's changing business, but why has this hit the mainstream now?

A secretive Canadian startup called Kindred AI is teaching robots how to perform difficult dexterous tasks at superhuman speeds by pairing them with human "pilots" wearing virtual-reality headsets and holding motion-tracking controllers. The technology offers a fascinating glimpse of how humans might work in synchronization with machines in the future, and it shows how tapping into human capabilities might amplify the capabilities of automated systems. For all the worry over robots and artificial intelligence eliminating jobs, there are plenty of things that machines still cannot do. The company demonstrated the hardware to MIT Technology Review last week, and says it plans to launch a product aimed at retailers in the coming months. The long-term ambitions are far grander.

You're sitting at home minding your own business when you get a call from your credit card's fraud detection unit asking if you've just made a purchase at a department store in your city. It wasn't you who bought expensive electronics using your credit card – in fact, it's been in your pocket all afternoon. So how did the bank know to flag this single purchase as most likely fraudulent? Credit card companies have a vested interest in identifying financial transactions that are illegitimate and criminal in nature. According to the Federal Reserve Payments Study, Americans used credit cards to pay for 26.2 billion purchases in 2012.

Voice assistants are software programs that respond to voice commands in order to perform a range of tasks. They can find an opening in a consumer's calendar to schedule an appointment, place an online order for tangible goods, and act as a hands-free facilitator for texting, among many, many other tasks. Technological advances are making voice assistants more capable. These improvements fall into two categories: improvements in AI, specifically natural language processing (NLP) and machine learning; and gains in computing and telecommunications infrastructure, like more powerful smartphones, better cellular networks, and faster cloud computing. Changes in consumer behavior and habits are also leading to greater adoption.

SYS-CON Events announced today that TechTarget has been named "Media Sponsor" of SYS-CON's 20th International Cloud Expo, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. TechTarget storage websites are the best online information resource for news, tips and expert advice for the storage, backup and disaster recovery markets. By creating abundant, high-quality editorial content across more than 140 highly targeted technology-specific websites, TechTarget attracts and nurtures communities of technology buyers researching their companies' information technology needs. By understanding these buyers' content consumption behaviors, TechTarget creates the purchase intent insights that fuel efficient and effective marketing and sales activities for clients around the world. All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020.

If you use a computer, you've probably seen that little "Intel Inside" sticker on it somewhere, letting you know that your Facebook posts and cat videos are happening due to Intel's dominance in the computer chip business. But there's another computer chip maker, Advanced Micro Devices, or AMD, that we don't hear about very much, although that may be about to change. Here at DT, Matt Smith has been putting AMD's new Ryzen 7 1800X chip through its paces, and he's here to report that the CPU has what it takes to compete against Intel, and at a price that puts it in reach of most people who like to build their own computer systems. The Ryzen 7 packs eight cores against the 10 in Intel's top Core i7 model, and while it isn't quite as fast as Intel's fastest chip, it's still pretty damn fast and at a price far below Intel's premium offerings. Is it a viable non-Intel option for computer builders and OEMs to drop into their machines?

In the high stakes world of professional poker, calculating the odds can go a long way to help win the hand. And a new bot developed by a team of computer scientists could give even James Bond a run for his money. The DeepStack system uses Artificial Intelligence to reduce an exponentially complex number of calculations to a more manageable size - then decides on its play in a matter of seconds. A combination of cool composure, a strong hand and more than a dash of luck allowed James Bond to walk off with a massive £93 million ($115 million) pot in Casino Royale. DeepStack played 3,000 hands each against eleven professional players.

While supervised neural nets trained on huge datasets can achieve impressive performances in tasks such as computer vision and speech recognition, they are often criticized because their internal representations are lacking in interpretability. In order to address some of these concerns, work by scientist Charlie Tang proposes models which add domain-specific knowledge in the form of structured latent variables to standard deep learning methods, leading to good results in one-shot face recognition under illumination variations.

The telescope offers one of the most seductive suggestions a technological object can carry: the idea that humans might pick up a thing, peer into it, and finally solve the riddle of the heavens as a result. Unraveling that mystery requires its own kind of refraction in perspective, collapsing the distance between near and far as a way to understand our planet and its place in the universe. This is why early astronomers didn't just gaze up each night to produce detailed sketches of celestial bodies. They also tracked the movement of those bodies across the sky over time. They developed an understanding of Earth's movement as a result.