I know how terrible healthcare records theft can be. I myself have been the victim of a data theft by hackers who stole my deceased father's medical files, running up more than $300,000 in false charges. I am still disputing on-going bills that have been accruing for the last 15 years. This event led me on the path to finding a solution so others would not suffer the consequences that I continue to be impacted by, but hospitals and other healthcare providers must be willing to make the change. The writing is on the wall.

The advocates of machine learning are known to be a fiercely contentious lot, each asserting that its own approach is superior to all others, and that any evidence adduced to the contrary is propaganda, fake news of the worst sort, stemming from jealous advocates of inferior approaches. The closest approximation to the internecine warfare of the machine learning field is the human learning field, in which advocates of public, government-run and union-staffed schools exchange harsh words with advocates of charter schools, with a level of invective and passion that indicates that someone is strongly in favor of hopelessly uneducated machines and/or humans.

Do you think AI will decrease human labor? So if foreseeable technologies materialize, then then the need for human labor could decrease. Technology always puts existing jobs under strain. This doesn't immediately mean that human labor as a whole is under threat. Generally, other professions grow to fill the loss, often creating more jobs than the ones that are lost.

Intel may have cut ties with Android on smartphones and tablets, but the company's partnership with Google on Android for the internet of things is growing stronger. Google's Android Things, a slimmed down version of Android for smart devices, will be coming to Intel's Joule 570x computer board. The combination will allow makers to cook up Android-based gadgets or smart devices for use in home, retail, or industrial settings. The Intel board adds a lot of processing and graphics muscle to projects. With 4K graphics capabilities, the 570x is good for devices with screens or computer vision, like robots and drones.

A true genius, Alan Turing was played brilliantly by Benedict Cumberbatch inThe Imitation Game -- the movie about his life and role in ending WWII -- which introduced him to a whole new generation of admirers. It was Turing who predicted machine learning would play a big role in modern computing in his article the "Turing Test," way back in 1950. Indeed, Turing was way ahead of his time, which was a major theme in the movie, but now the world has caught up. The major advancements in readily accessible computing power, the quantity of data available, and algorithms that truly make machine learning possible are driving our ability to process data, analyze it, and act on it in ways that would make Mr. Turing proud. These advances have completely changed the machine learning game: The fundamental concept remains the same, but now it's far more sophisticated, efficient, and easily deployable. Beyond the big headline-grabbing examples of how machine learning will impact our lives -- such as through driverless cars -- it has exciting potential to put an end to the bland and sometimes ineffective customer experiences that many retailers are delivering to their customers.

This series of blog posts aims to provide an intuitive and gentle introduction to deep learning that does not rely heavily on math or theoretical constructs. The first part in this series provided an overview over the field of deep learning, covering fundamental and core concepts. The third part of the series covers sequence learning topics such as recurrent neural networks and LSTM. I wrote this series in a glossary style so it can also be used as a reference for deep learning concepts. The earliest deep-learning-like algorithms that had multiple layers of non-linear features can be traced back to Ivakhnenko and Lapa in 1965 (Figure 1), who used thin but deep models with polynomial activation functions which they analyzed with statistical methods. In each layer, they selected the best features through statistical methods and forwarded them to the next layer. They did not use backpropagation to train their network end-to-end but used layer-by-layer least squares fitting where previous layers were independently fitted from later layers.

The lending and credit scoring sector have more data than ever before at their disposal. How they leverage this data to create value for their clients and social impact determines the outcomes they can achieve in the financial services space. In 1959, Arthur Samuel, a pioneer in the field of machine learning (ML) and artificial intelligence during an era when computers filled an entire building, defined machine learning as "a field of study that gives computers the ability to learn without being explicitly programmed." During a recent keynote, Microsoft CEO Satya Nadella referred to data used in this context as "the new electricity," calling our current era a "fourth industrial revolution" following steam, electricity and digital technology. Scott Guthrie, Microsoft executive vice president, also acknowledged that data is "enabling every business to be the disrupters of their industry by harnessing the power to drive insight from this data."

Does your digital assistant know who it's talking to? A wearable device prototype could let voice-controlled assistants like Apple's Siri or Amazon's Alexa recognise their owner so they don't take orders from anyone else. The VAuth device, developed at the University of Michigan in Ann Arbor, uses an accelerometer hidden in a pair of glasses or earphones or worn around the neck. The accelerometer measures vibrations created as the wearer speaks. An algorithm then compares those vibrations with the audio signal received by the digital assistant. If the vibrations and the audio match, then the voice command is received as normal.

The computation model was built on CogSketch, a sketch-understanding system developed in Forbus' laboratory at Northwestern University. Sketching is a natural activity that people do while thinking or trying to communicate an idea, especially when spatial content is involved. Sketching is also heavily used in engineering and geoscience. CogSketch is used to model spatial understanding and reasoning, making it suitable for research based on sketches, but also for testing against a standardized visual intelligence test such as the Raven's Progressive Matrices test.

Apple has joined a non-profit group focused on spreading the message that artificial intelligence technologies can be used for societal good. The technology giant is now a member of Partnership on Artificial Intelligence, which debuted in September with an initial cast of participants including Amazon (amzn), Google (goog), Microsoft (msft), IBM (ibm), and Facebook (fb). Although these huge technology companies are competitors, they stand to benefit by joining forces to combat any negative public attitudes about AI. Some critics says that rapid advances in AI can lead to widespread job losses and an invasion of privacy because these companies must continuously gather massive amounts of user data to improve their AI-powered software. Companies like Apple, Google, and Microsoft have all been heavily investing in AI technologies like deep learning to improve their services.