Beyond that, things don't look so good, but the computer continues its four-and-a-half-year love affair with international investing, according to Mr. Mehrotra, who dutifully follows the lead of the Asset Allocation Neural Network, AANN. "I used to second-guess her, but I was wrong nine out of 10 times," he said. The use of artificial intelligence, also known as neural networks or genetic algorithms, has been described by some as the second generation of quantitative investing because it has the flexibility to get smarter through the expansion of input data. The technology, which has been in place for more than a decade at Legend Advisory and is quietly spreading throughout the money management industry, also has wide applications for use in science and medical technology. It was an artificial-intelligence program that enabled IBM's Deep Blue computer to defeat chess champion Gary Kasparov in 1997.

Gordon Bell will never forget what I look like. He'll never forget what I sound like, either. Actually, he'll never forget a single detail about me. That's because when I first met the affable 72-year-old computer scientist at the offices of Microsoft Research Labs, in Redmond, Washington, he was carefully recording my every move. He had a tiny bug-eyed camera around his neck, and a small audio recorder at his elbow. As we chatted about various topics--Australian jazz musicians, his futuristic cell phone, the Seattle area's gorgeous weather--Bell's gear quietly logged my every gesture and all my blathering small talk, snapping a picture every 60 seconds. Back at his office, his computer had carefully archived every document related to me: all the email I'd sent him, copies of my articles he'd read, pages he'd surfed on my blog. "Oh, I've got everything," Bell said cheerily. And when I saw him the next day, down in his cramped personal office in San Francisco, he offered to give me a glimpse of the memories he'd collected. He plunked down in front of his computer, pulled up a browser, typed in "Clive Fast Company," and there they were: Hundreds of pictures of the meeting scrolled by on his screen, and the sound of our day-old conversation filled the room. It was a deeply strange feeling. My random chitchat is being preserved? He nodded, pointing to a mundane Dell computer parked beneath his desk. Because I'm not the only thing Gordon Bell will never forget. His goal is never to forget anything.

It may look like a video game, but the new computer simulation developed by a team of researchers in Barcelona could one day train autonomous cars to be better drivers. Called'Synthia,' the program creates a virtual city complete with pedestrians, traffic signs and other components of an urban environment, automatically annotated at the pixel-level. This allows for a more efficient method of training AI systems, and can be used to teach them to recognize and behave in response to the less predictable aspects of city driving, like a nearby cyclist or adverse weather. A new computer simulation could one day train autonomous cars to be better drivers. Called'Synthia,' the program creates a virtual city complete with pedestrians, traffic signs and other components of an urban environment, automatically annotated at the pixel-level Researchers hope programs like Synthia can be used to improve the abilities of AI to recognize different objects, to make autonomous driving more reliable.

Where and how in the cerebral cortex do single neurons process more than one sensory modality during perceptual judgments?

Initiating joint attention (IJA), the behavioral instigation of coordinated focus of 2 people on an object, emerges over the first 2 years of life and supports social-communicative functioning related to the healthy development of aspects of language, empathy, and theory of mind. Deficits in IJA provide strong early indicators for autism spectrum disorder, and therapies targeting joint attention have shown tremendous promise. However, the brain systems underlying IJA in early childhood are poorly understood, due in part to significant methodological challenges in imaging localized brain function that supports social behaviors during the first 2 years of life. Herein, we show that the functional organization of the brain is intimately related to the emergence of IJA using functional connectivity magnetic resonance imaging and dimensional behavioral assessments in a large semilongitudinal cohort of infants and toddlers. In particular, though functional connections spanning the brain are involved in IJA, the strongest brain-behavior associations cluster within connections between a small subset of functional brain networks; namely between the visual network and dorsal attention network and between the visual network and posterior cingulate aspects of the default mode network. These observations mark the earliest known description of how functional brain systems underlie a burgeoning fundamental social behavior, may help improve the design of targeted therapies for neurodevelopmental disorders, and, more generally, elucidate physiological mechanisms essential to healthy social behavior development. The emergence of joint attention (JA), the coordinated orienting of 2 people toward an object or event, occurs during the first 2 years of life, arguably the most dynamic and important period of early child development (Scaife and Bruner 1975). It is theorized that engaging in JA lays the foundation for prosocial cooperative behavior, from basic social-communicative functioning and language development (Premack 2004) to sophisticated forms of empathy (Mundy and Jarrold 2010) and theory of mind (Adolphs 2003). In fact, early exhibition of joint attention is strongly associated with later language ability (Morales et al. 2000; Mundy et al. 2007), and atypical development of the initiation of joint attention (IJA) is strongly indicative of autism spectrum disorder (ASD) (Bruinsma et al. 2004). The neural substrates underlying IJA in early childhood are poorly understood (Barak and Feng 2016), due in part to significant methodological challenges in imaging localized brain function that supports social behaviors in children during the first 2 years of life.

The past decade or so has seen a strong focus on risk and compliance technologies that make use of analytics in financial services. These technologies, which might be called "defense" technologies--in contrast to "offense" technologies that involve marketing and revenue growth--include applications and infrastructure for risk management, fraud prevention, regulatory, and anti-money laundering (AML) compliance. They bring the power of analytical insights--initially used for identifying marketing opportunities in many companies--to risk mitigation in banking. While these distinctions are somewhat blurred by integrating risk-based insights into "offense" activities, they are a useful shorthand. The Great Recession of the late 2000s drove both a greater focus on risk management and substantial new regulation for financial firms.

Billions of workers around the world are paid to perform easy-to-automate or repetitive tasks. Whether it's administrative work, scheduling, decision making, inventory or most, a robot could usually do it better... and faster. Artificial intelligence develops more and more each given year, promising to redefine the way we live, move and work. The AI analytics research industry funding has rising from an $8.2 billion investment in 2013 to a predicted $70 billion by 2020, according to a Bank of America report citing IDC research. A recent Harvard Business Review study found that managers currently spend about 54% of their time handling administrative coordination and control when they could be making higher judgement calls.

Customers should approach online reviews of health products with caution, say University of Aberdeen researchers. An analysis of clinical trial data and user-generated online reviews has shown that customers are prone to exaggerating the effects of weight loss and cholesterol treatments, especially when they have positive results. The researchers examined more than 1,600 Amazon.com The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric ...

A new exhibition at Science Gallery Dublin is exploring what an automated world might look like. There's a lot of discussion around the future of work, particularly when it comes to AI and robotics becoming more integrated into the workplace. Many experts are confident that advances in AI will, contrary to popular belief, actually create more jobs than it will get rid of. Those experts have also quelled our fears about certain elements of human behaviour being usurped by intelligent, human-like bots. Sure, they can analyse data at the drop of a hat and a lot of monotonous administration can be automated, but robots don't have the level of creativity or emotional intelligence that humans have, right?

The new year has arrived and it's going to be one big year for wearable tech. Evey year I look into my connected crystal ball and peek into the future to predict what might happen in the world of wearables. Here is how I think 2017 will shake down for the wearable world. The biggest buzzword of 2017 is AI, and it's set to be the saving grace of IoT and wearables. Deep learning is a massive missing piece when it comes to our connected world -- wearable tech included -- as cognitive computing and machine learning will make use of big data and connect the dots for users.