If you consider just the evolution of data management it has been a rocky road. Computers helped but there is still worldwide allot of paper. We move atoms more then bits. The history of big data efforts has not always delivered productive outcomes. Then came data warehousing where we digitize all of the information in paper files and put that in discs or databases.

Every week, Moorfields Eye Hospital in London performs 3,000 optical coherence tomography scans to diagnose vision problems. The scans, which use scattered light to create high-resolution 3D images of the retina, produce large quantities of data, and its analysis is slow. Understanding the images requires trained and experienced human eyes to identify problems specific to each case, leaving little or no time to identify broader, population-wide trends that could make early detection easier. That's just the kind of task that artificial intelligence can be used to tackle, though. So it's perhaps not surprising that Google's AI wing, DeepMind, has decided to partner with the hospital to apply machine learning to the problem as part of its Health program.

It's a beautiful introduction ... Try not to drool too much! Read "A Few Useful Things to Know about Machine Learning" by Prof. Pedro Domingos. It's densely packed with valuable information, but not opaque. The author understands that there's a lot of "black art" and folk wisdom, and they invite you in. Take your time with this one.

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.