Putting aside contested definitions of what artificial intelligence actually is (Digital Journal has discussed this recently), the new Google projects are orientated towards pushing forward the concept of the thinking machine or, as the head of research Emmanuel Mogenet puts it, "teaching machines common sense." The projects form the core part of Google's significantly expanded European research center. Mogenet is head of Google's Zürich Search Team. He is credited with developing the application Shake (software), before being headhunted by the U.S. tech firm. The Google projects focus on three research areas: machine learning, natural language understanding and computer perception.

Diabetes can result in a common complication--known as diabetic retinopathy--that damages the back of the eye, known as the retina. The chronic disease can cause vision loss if left untreated. But, if caught early, patients can significantly reduce the risk of blindness. Google's DeepMind, which specializes in artificial intelligence, is partnering with Britain's National Health Service (NHS) to do just that. The NHS is Britain's publicly funded healthcare system--free to use, treating a million patients every 36 hours, and consisting of one of the largest workforces in the world.

Even the also-rans fared better, TechRepublic notes. Despite tougher demands, only four competitors failed to score (versus half in the 2015 challenge). Nearly half of the entries managed over 40 points, which would have been good enough to get third place a year ago. TU Delft and other entrants aren't about to replace people any time soon. Human workers typically pick 400 items per hour, and they won't suffer the 16.7 percent failure rate of the Picking Challenge leader.

Google DeepMind has announced a brand new research project in partnership with the NHS. The collaboration will see Google's artificial intelligence division working with London's Moorfields Eye Hospital to develop a machine learning system that will detect the early signs of degenerative eye conditions which humans might miss. Though this is the second project DeepMind is embarking on with the NHS, it's the first time the company has used machine learning in purely medical research and DeepMind co-founder Mustafa Suleyman says he thinks "one day this work will be a great benefit to patients across the NHS." Moorfields says that analysing complex eye scans is a time consuming process and traditional analysis tools have been unable to explore them fully. It hopes the research with DeepMind will lead to earlier detection and more effective treatment for patients and ultimately help to avoid cases of preventable eye disease.

In the construction industry, many projects involve remodeling or refurbishing existing buildings, and such jobs often face delays or cost overruns when hidden problems emerge. "Renovation projects live and die by the quality of information," according to Martin Fischer, a Stanford professor of civil and environmental engineering. New software can analyze this point cloud to automatically extract details to plan a remodel or other purposes. Newer buildings often have computerized blueprints and records, including details such as the number of rooms, doors and windows, and the square footage of floors, ceilings and walls. But such information may not exist for older buildings, necessitating the time-consuming and difficult task of collecting these details manually.

A new Guardian report shows where AI is headed next, in a joint venture between Google's Deep Mind and the British NHS … The British team behind Google's AI efforts is teaming up with the UK's National Health Service and London's Moorfields Eye Hospital to build a machine learning system capable of recognizing potentially sight-threatening conditions by simply identifying symptoms from a digital scan of the eye. The core of the research will see about a million eye scans (all coming from anonymous patients) being analysed by an AI-fuelled computer, which Deepmind researchers will use to train a special algorithm. The algorithm will then allow the machine to spot early signs of eye conditions, such as wet age-related macular degenerations and diabetic retinopathy; diabetes, in fact, apparently makes it "25 times more likely to go blind", as per Mustafa Suleyman, Deepmind's co-founder. "If we can detect this, and get in there as early as possible, then 98% of the most severe visual loss might be prevented," Mustafa said. And indeed, allowing a computer to do most of the hard work would help immensely in increasing both the speed and the accuracy of a diagnosis, potentially helping the sight of thousands to be saved.

The Otto Group Product Classification Challenge made Kaggle history as our most popular competition ever. Alexander Guschin finished in 2nd place ahead of 3,845 other data scientists. In this blog, Alexander shares his stacking centered approach and explains why you should never underestimate the nearest neighbours algorithm. I have some theoretical understanding of machine learning thanks to my base institute (Moscow Institute of Physics and Technology) and our professor Konstantin Vorontsov, one of the top Russian machine learning specialists. As for my acquaintance with practical problems, another great Russian data scientist who once was Top-1 on Kaggle, Alexander D'yakonov, used to teach a course on practical machine learning every autumn which gave me very good basis. Kagglers may know this course as PZAD.

Therefore, SendPulse will add Italian, French, German, Turkish, Simple Chinese, Indonesian, Korean, Japanese, Arabic, and by the way, Spanish (LatAmerica), Brazilian Portuguese localization. Currently we've used pre-launch product for English and Russian audience. In total we will be have 13 foreign language groups. The language detection are based on geolocation. The modeling technology is based on math method, behavioral analyses to find lookalike audiences (digital twins) to create on behavior models in consuming content, clicks, design, social demographics - the simple comparison will be Facebook Artificial Intelligence for native advertising.

'We have arrived,' the personal assistant announced as the automated share car pulled up outside Turing & Partners, one of London's best-known AI-powered law firms. Elon Turing looked up from his notes that were projected before him and got out at the curb on Gresham Street, not far from the Bank of England. It was very warm, as it always was these days, though there was a heaviness in the air that promised a thunder storm. Elon nodded to the car, which zipped away into the pollution free morning and disappeared into a sea of auto-taxis, self-driving buses and other share cars. He took a deep breath and marched up to the front door of the building. The door scanned his face and opened, greeting him politely as he walked into the cooled lobby. At the reception desk was Albert.

One million anonymised eye scans from Moorfields Eye Hospital will be used to train an artificial intelligence (AI) system from Google. Machine learning algorithms will scour the images for signs of diseases such as macular degeneration and diabetes-related sight loss. Moorfields is teaming up with Google's AI division DeepMind during the scheme. Previously, DeepMind faced criticism over a little-known data sharing agreement with three London hospitals. An agreement to share patient data from the Royal Free, Barnet and Chase Farm hospitals over the past five years and continuing until 2017 was revealed by the New Scientist in May.