Intel's RealSense platform was the star of its Intel Developer's Forum conference in San Francisco last month and it seems the company is only looking to grow the scale and capabilities of its computer vision tech. Today, the company announced that it is acquiring the computer vision startup behind Google's Project Tango 3D-sensor tech, Movidius. In a blog post, Movidius CEO Remi El-Ouazzane announced that his startup will continue in its goal of giving "the power of sight to machines" as it works with Intel's RealSense technology. Movidius has seen a great deal of interest in its radically low-powered computer vision chipset, signing deals with major device makers, including Google, Lenovo and DJI. The eight-year old company has about 180 employees with offices inSilicon Valley, Ireland and Romania.

Artificial Intelligence (AI) or machine learning can be used to help improve the accuracy of the diagnosis in lung diseases, finds a study. Machine learning utilises algorithms that can learn from and perform predictive data analysis. The team developed an algorithm process in addition to the routine lung function parameters and clinical variables of smoking history, body mass index (BMI) and age. Based on the pattern of both the clinical and lung function data, the algorithm makes a suggestion for the most likely diagnosis. "We have demonstrated that AI can provide us with a more accurate diagnosis. The algorithm can simulate the complex reasoning that a clinician uses to give their diagnosis, but in a more standardised and objective way so it removes any bias," said Wim Janssens from the University of Leuven in Belgium.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Artificial Intelligence (AI) or machine learning can be used to help improve the accuracy of the diagnosis in lung diseases, finds a study. Machine learning utilises algorithms that can learn from and perform predictive data analysis. The team developed an algorithm process in addition to the routine lung function parameters and clinical variables of smoking history, body mass index (BMI) and age. Based on the pattern of both the clinical and lung function data, the algorithm makes a suggestion for the most likely diagnosis. "We have demonstrated that AI can provide us with a more accurate diagnosis. The algorithm can simulate the complex reasoning that a clinician uses to give their diagnosis, but in a more standardised and objective way so it removes any bias," said Wim Janssens from the University of Leuven in Belgium.

Of the many misconceptions about machine learning, the idea that they can't be prejudiced is likely the most harmful. As stated by Moritz Hardt in How big data is unfair, machine learning is not, by default, fair or just in any meaningful way. Even though many researchers and practitioners have noted this repeatedly in the past, the message is still lost. It's not uncommon to hear variations of "algorithms don't have in-built bias" even when there is an entire field of research dedicated to fighting that very issue. To make this clearer, prejudice in machine learning will haunt us for years to come.

The end of work-as-we-know-it, and radical longevity: The imminent clash between technology and humanity is already rushing towards us. What moral values are you prepared to stand up for--before being human alters its meaning forever? This is not me saying this. This is Gerd Leonhard a new kind of futurist schooled in the humanities as much as in technology. A musician by origin, Gerd connects left and right brains for a 360-degree coverage of the multiple futures that present themselves at any one time.

Berlin - 03 Sep 2016: at IFA Berlin – one of the world's leading trade shows for consumer electronics – IBM (NYSE: IBM) was joined by some of the biggest names in the industry to highlight how Watson IoT technologies are poised to drive a new wave of innovation in the home and play a key role in one of the biggest technological transformations in the history of the world. According to Harriet Green, Global Head of IBM Watson IoT: "millions of sensors are giving appliances and devices eyes and ears, increasing their inbuilt intelligence and enabling them to interact with us better." "The challenge is that over next few years, the Internet of Things will become the biggest source of data on the planet. That's where IBM's Watson cognitive computing system comes in. Watson uses machine learning and other techniques to understand this data and turn it into insight, which can help automate tasks, enable manufacturers to design better products, innovate new services and enhance our overall quality of life – especially in the home. And with cognitive technologies, interactions with'things' through natural language and voice commands will dramatically improve," added Green during her keynote at IFA. Examples of companies tapping IBM's Watson IoT platform include: Whirlpool is using Watson technologies to help deliver superior customer service and enhance people's lives at home by enabling its home appliances to connect with and interact with one another and their users.

There's an emerging market called Dataism, which venerates neither gods nor man - it worships data. From a Dataist perspective, we may interpret the entire human species as a single data-processing system, with individual humans serving as its chips. A city of 100,000 people has more computing power than a village of 1,000 people. Different processors may use diverse ways to calculate and analyse data. Using several kinds of processors in a single system may therefore increase its dynamism and creativity. A conversation between a peasant, a priest and a physician may produce novel ideas that would never emerge from a conversation between three hunter-gatherers. There is little point in increasing the mere number and variety of processors if they are poorly connected. A trade network linking ten cities is likely to result in many more economic, technological and social innovations than ten isolated cities. 4. Increasing the freedom of movement along existing connections. Connecting processors is hardly useful if data cannot flow freely.

The word Artificial Intelligence has been thrown around in the start-up world over the past few months, with phrases like Machine Learning and Natural Language Processing following shortly after. That said, can these rapidly evolving technologies really be used to influence the travel industry, and if so, by how much? Machine learning, in its many forms, has allowed computers to build an understanding of who we are, by making use of the data that we provide. As a result, advertising has become more specific, algorithms have got more intelligent, and the background processing of mobile applications and computer software has become more tailored to the user. Remember the last time you saw that advert pop up onto your computer screen after having a look for something?

Beauty contests are slightly computational to begin with. While the notion of beauty is of something ephemeral and unquantifiable, a beauty pageant asks that we categorize and rank it: determining rules that let us objectively measure an idea which must be, at its root, mysterious and subjective. No surprise, then, that here in 2016 we have just witnessed the first beauty contest judged by AI, as a jury of decidedly non-human bots picked out what they considered to be the best-looking people from a dataset of 6,000 entries. "New tools like machine learning let us analyze images in a way that was never available to us before," Anastasia Georgievskaya, co-founder and research scientist at Youth Laboratories, the company behind Beauty.AI, told Digital Trends. "Our goal was to investigate methods that would show new approaches to beauty evaluation."