The Amazon robotic Picking Challenge is a now annual competition that searches for robots that could one day work in the company's vast warehouses and its second champion has been announced. This year's winner was a joint effort, created by TU Delft Robotics Institute from the Netherlands and the company Delft Robotics. The team's robotic arm used a combination of a suction cup, a gripper, a depth-sensing camera, and deep learning artificial intelligence to pick and stow items from a mock Amazon warehouse shelf with greater speed and accuracy than the 15 other entries in the competition. TU Delft's creation's greatest asset was its adaptive deep learning which allowed it to scan the different shapes and sizes of the objects it was picking up and adjust how it manipulated them accordingly. The robot was able to pick items from the shelf with a speed of over 100 items per hour which is an impressive three times faster than last year's winner, even though Amazon had made the challenges much tougher "with denser bins, occluded items, and products that are more difficult to see and grasp."

Amazon has crowned the latest champion in its robotic picking challenge -- an annual competition that looks for robots that could one day work in the company's warehouses. It's basically American Idol, but for robotic arms that can grab items off a shelf and put them back again. Competitors are asked to handle a range of products, from toiletries to clothes, and then scored on speed and accuracy in stocking shelves. This year's contest was won by a joint team from the TU Delft Robotics Institute in the Netherlands and the company Delft Robotics (both named after the city of Delft). The team's robot managed to pick items from a mock Amazon warehouse shelf at a speed of around 100 an hour, reports TechRepublic, with a failure rate of 16.7 percent.

Lecture Title: Machines that learn: big data or explanatory models? Abstract: A leading question about machines that learn concerns two distinct styles of learning. Will they turn out to depend more on probabilistic models that explain the data, or on networks that react to data and are trained on data at ever greater scale? In machine vision systems, for instance, this boils down to the comparative roles of two paradigms: analysis-by-synthesis versus empirical recognisers. Each approach has its strengths, and empirical recognisers especially have made great strides in performance in the last few years, through deep learning.

Clifford Chance (CC) has become the latest firm to sign a deal with an artificial intelligence (AI) provider, with the magic circle firm partnering with Kira Systems. The deal means CC's lawyers will be able to use the AI software for tasks such as document review in M&A due diligence. The firm said it has already used AI technology in several other applications but declined to provide details. The Kira deal, which is aimed at reducing costs for clients, was led by the firm's head of innovation and business change, Bas Boris Visser. He said CC's clients are "under substantial pressure to reduce legal spend", adding: "At the same time, they need more support to manage the increasing risks and complex issues that their companies are facing."

DeepMind, the London-based artificial intelligence lab acquired by Google in 2014, has accomplished more than a few spectacular stunts of machine learning. Its neural networks bested a human champion at the notoriously tough game of Go, inculcated the basic rules of soccer on a digital ant-like creature, and teased out winning strategies for more than 49 Atari 2600 games. But now, the outfit's robots are being tasked with a more humanistic pursuit: eye disease research. On Tuesday, DeepMind announced a long-term project that will see the company's machine-learning algorithms parse "millions" of eye scans to tease out early warning signs that human doctors might otherwise miss. The new project, which is based out of the U.K.'s Moorfields Eye Hospital in east London, is the fruit of DeepMind's ongoing partnership -- dubbed DeepMind Health -- with the country's National Health Service.

Magic circle giant Clifford Chance is the latest City outfit to embrace the mysterious world of artificial intelligence (AI), striking a deal with Canadian software provider Kira Systems. According to the Canary Wharf based firm, the intelligent software will help its lawyers quickly analyse contracts, identify potential legal issues, improve speed, and, as a result, increase all round efficiency. Furthermore -- according to the software designer -- not only can Kira be put to work straight away, requiring very little set up time, she it can actually learn on the job, growing in intelligence through training provided by the firm's lawyers. Our clients are under substantial pressure to reduce legal spend. At the same time, they need more support to manage the increasing risks and complex issues that their companies are facing.

When our robot overlords launch the nukes and seize control of the planet, chances are they'll rise up first in the United States. And they definitely won't deliver evil speeches when they're running the place. Those are the conclusions a technophobe might draw from a new study identifying a possible flaw in the Turing Test, which is considered a means for evaluating artificial intelligence. The study found that a machine can successfully masquerade as a thinking entity during a blind conversation, if it is allowed to remain silent whenever it chooses (i.e. The Turing test, or imitation game, was developed by famed mathematician Alan Turing to evaluate whether a machine can present itself as a thinking entity by simulating the quirks, imperfections and thought processes that people demonstrate in conversation.

Fresh off a stunning victory in a nearly-impossible-to-master board game, Google's DeepMind artificial intelligence project is bringing its brainpower to the humble eye scan. Google, which acquired British startup DeepMind in 2014, is partnering with the UK's state-run National Health Service. The mission: to create a system whereby sight-threatening conditions can be diagnosed from just a single scan of the eye, the company said Tuesday. Together, these diseases affect more than 100 million people worldwide, according to Google. Google will investigate how DeepMind's technology can be taught to analyze scans for the two diseases --the diagnoses of which have been time-consuming efforts for eye doctors due to their complexity.

Google's DeepMind division has announced a partnership with the NHS's Moorfields Eye Hospital to apply machine learning to spot common eye diseases earlier. The five-year research project will draw on one million anonymous eye scans which are held on Moorfields' patient database, with the aim to speed up the complex and time-consuming process of analysing eye scans. The hope is that this will allow diagnoses of common causes of sight loss, like diabetic retinopathy and age-related macular degeneration, to be spotted more rapidly and hence be treated more effectively. For example, Google says that up to 98 percent of sight loss resulting from diabetes can be prevented by early detection and treatment. Mobile app called "Streams" provides medical staff with latest clinical information.

Farber goes on, "Reflecting Intel's very strong commitment to open source, the CPU optimized MKL-DNN library for machine learning has been open sourced. Rounding out a cornucopia of machine learning technology announcements, the company has created a single portal for all their machine learning efforts at http://intel.com/machinelearning. Through this portal, Intel hopes to train 100,000 developers in the benefits of their machine learning technology. They are backing this up by giving early access to their machine learning technology to top research academics. Interest in machine learning is accelerating as commercial and scientific organizations are realizing the tremendous impact it can have across a wide range of markets ranging from Internet search, to social media, to real-time robotics, self-driving vehicles, drones and more."