Computers could soon be helping to diagnose cancer in patients with the help of artificial intelligence that has been trained to spots the early signs of the disease. An AI machine capable of accurately diagnosing breast cancer 92 per cent of the time has been developed by researchers. While it is still not quite as good as human specialists – who are correct 96 per cent of the time – it suggests that AI could soon be used to speed up and improve cancer screening. Scientists have used machine learning to create an artificial intelligence system capable of diagnosing breast cancer from lymph node biopsies with 92 per cent accuracy (cancer cells in a lymph node pictured). When combined with a human pathologist this accuracy increased to 99.5 per cent The system was developed by computer scientists at Harvard Medical School gave a machine learning algorithm slides of lymph nodes from breast cancer patients.

Twitter has added another machine learning startup to its flock. London-based Magic Pony Technology was purchased by the social media network for a reported 150 million. This move will enhance Twitters's strength in video, as the startup's technology improves the quality of videos captured with low-resolution cameras by recognizing patterns and textures. Twitter has purchases London-based Magic Pony Technology for a reported 150 million. This move will enhance Twitters's strength in video, as the startup's technology improves the quality of videos captured with low-resolution cameras by recognizing patterns and textures Magic Pony Technology is a London-based startup that has been building and training neural networks to process and improve videos for just a little less than two years.

Scientists have discovered a'chatty' gene which makes people sociable. Researchers say chemical tags that attach to this gene can change how sociable we are - and the discovery could lead to new treatments for autism and other social disorders. A study of 129 people found those with less of the protein had more difficulty recognising emotional facial expressions - and tended to have more anxiety about their relationships with loved ones. Sociability (stock image) may be determined by modifications to a single gene for oxytocin - the hormone that helps us bond with others. The genetic information that is bound up in our DNA is continually decoded by genetic machinery that uses it to produce proteins.

Microsoft is pushing its analytics credentials by detailing how its platforms can be used together to produce output in a way that chief information officers and others can act on, specifically using Power BI to visualise results from the Azure Machine Learning service, now part of the broader Cortana Intelligence Suite. The company said that there has been a lot of interest among customers in using Power BI to visualise the output of an Azure Machine Learning model, and the firm recently published a tutorial showing exactly how this can be accomplished, providing useful pointers for Microsoft customers looking to make the best use of such tools to analyse data. "Imagine if you could have Power BI regularly bring in the latest output of your fraud model or the sentiment for recent tweets about your products," said Justyna Lucznik, programme manager for Microsoft's Power BI team. Microsoft's tutorial naturally assumes that customers are already using multiple Microsoft platforms, such as a cloud-hosted Azure SQL database instance as the source of their data and subscriptions to the PowerBi and Azure ML services, and also use the R language, one of Microsoft's favoured tools for statistical computing, to script all the actions together. The tutorial walks customers through the process of using an R script to extract data from Azure SQL, then calling the Azure ML web service to score the data and write the output back to the SQL database.

National Harbor, MD - 16 Jun 2016: Local Motors, the leading vehicle technology integrator and creator of the world's first 3D-printed cars, today introduced the first self-driving vehicle to integrate the advanced cognitive computing capabilities of IBM (NYSE: IBM) Watson. Starting today, Olli will be used on public roads locally in DC, and late in 2016 in Miami-Dade County and Las Vegas. "Olli offers a smart, safe and sustainable transportation solution that is long overdue," Rogers said. "Olli with Watson acts as our entry into the world of self-driving vehicles, something we've been quietly working on with our co-creative community for the past year. We are now ready to accelerate the adoption of this technology and apply it to nearly every vehicle in our current portfolio and those in the very near future. I'm thrilled to see what our open community will do with the latest in advanced vehicle technology."

If you write marketing or advertising text for a living, you may want to get a second job skill. That's because software that writes text is here, and it is tackling a growing list of assignments. Several companies offer software that regularly churns out thousands of stories and reports based on structured data, like financial results. Ads that literally write themselves emerged last week, as IBM announced a new service based on its Watson supercomputer. A program called Quakebot has generated earthquake stories for the LA Times.

Physicists are putting themselves out of a job, using artificial intelligence to run a complex experiment. The experiment, developed by physicists from The Australian National University (ANU) and UNSW ADFA, created an extremely cold gas trapped in a laser beam, known as a Bose-Einstein condensate, replicating the experiment that won the 2001 Nobel Prize. "I didn't expect the machine could learn to do the experiment itself, from scratch, in under an hour," said co-lead researcher Paul Wigley from the ANU Research School of Physics and Engineering. "A simple computer program would have taken longer than the age of the Universe to run through all the combinations and work this out." Bose-Einstein condensates are some of the coldest places in the Universe, far colder than outer space, typically less than a billionth of a degree above absolute zero.

What if computers could take the words we type on the internet and convert them into a language that describes what they actually mean? Analyzing data pulled from social media would reveal insights into the deeper questions about our real motives and feelings, instead of mere statistics. Pierre Lévy, a French philosopher who's been writing about cyberspace since the 1990s and who is the Canada research chair in collective intelligence at the University of Ottawa, is working on software that can do just this. He's done the math and annotated the entire French dictionary with a language--or, as he calls it, a hyper-language, since it describes words that already form a language of their own--that he calls IEML, or the Information Economy MetaLanguage. All that's left is to do the actual coding to turn it into an automatic system.

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

A research team from Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School (HMS) recently developed artificial intelligence (AI) methods aimed at training computers to interpret pathology images, with the long-term goal of building AI-powered systems to make pathologic diagnoses more accurate. "Our AI method is based on deep learning, a machine-learning algorithm used for a range of applications including speech recognition and image recognition," explained pathologist Andrew Beck, MD, PhD, Director of Bioinformatics at the Cancer Research Institute at Beth Israel Deaconess Medical Center (BIDMC) and an Associate Professor at Harvard Medical School. "This approach teaches machines to interpret the complex patterns and structure observed in real-life data by building multi-layer artificial neural networks, in a process which is thought to show similarities with the learning process that occurs in layers of neurons in the brain's neocortex, the region where thinking occurs." The Beck lab's approach was recently put to the test in a competition held at the annual meeting of the International Symposium of Biomedical Imaging (ISBI), which involved examining images of lymph nodes to decide whether or not they contained breast cancer. The research team of Beck and his lab's post-doctoral fellows Dayong Wang, PhD and Humayun Irshad, PhD, and student Rishab Gargya, together with Aditya Khosla of the MIT Computer Science and Artificial Intelligence Laboratory, placed first in two separate categories, competing against private companies and academic research institutions from around the world. The research team today posted a technical report describing their approach to the arXiv.org