On the Internet, "nobody knows you're a dog," as the old meme goes, and today, the same can increasingly be said of robots. There are already scheduling robots that are virtually indistinguishable from humans, and recently students at the Georgia Institute of Technology learned that "Jill Watson" -- a teaching assistant they had relied upon all semester -- was in fact artificially intelligent. "The world is full of online classes, and they're plagued with low retention rates," said Ashok Goel, a Georgia Tech professor who teaches a class entitled Knowledge-Based Artificial Intelligence. "One of the main reasons many students drop out is because they don't receive enough teaching support. We created Jill as a way to provide faster answers and feedback."

Amazon is making a bigger leap into open-source technology with the unveiling of its machine-learning software DSSTNE. The newly released program is competing with Google's TensorFlow, which the search giant open-sourced last year. Amazon says DSSTNE (which stands for Deep Scalable Sparse Tensor Network Engine and is pronounced "Destiny") excels in situations where there isn't a lot of data to train the machine-learning system, whereas TensorFlow is geared for handling tons of data. DSSTNE is also faster than TensorFlow, with Amazon claiming up to 2.1 times the speed in low-data situations. The software comes from Amazon's need to make recommendations in its retail platform, which required the company to develop neural network programs.

Move over, Siri and Tay, and make room for a new female virtual agent set to invade the enterprise: Amelia. Things are happening fast in the new world of artificial intelligence (AI) development, and a new industry partnership just announced today aims to help enterprises adopt the complicated and potentially game-changing technology with Amelia. Accenture, a professional services consultancy, is teaming up with IPsoft, an autonomic and cognitive computing specialist that invented Amelia, "to accelerate client adoption of artificial intelligence to improve business outcomes and create new growth opportunities for their businesses." The importance of AI in the enterprise -- along with ancillary technologies like machine learning (ML) and cognitive computing -- was highlighted recently by no less than Microsoft CEO Satya Nadella and Facebook CEO Mark Zuckerberg in keynote addresses at their respective developer conferences. Their companies are helping to spearhead AI programming, with early efforts centered around bots, or chatbots, or virtual agents.

Law school, the default location for America's brightest unemployed Liberal Arts graduates and the worst decision a 20-something can make in the modern era just became an even worse bargain, if that's possible. We're not talking about a surge in LSAT applicants, beginning in 2008, that led to the creation of InfiLaw Corporation scam-law-schools like Charlotte, Florida Coastal, or Arizona Summit, the latter of which boasts an average bar passage rate of below 31% and an average cost of attendance exceeding 250,000. We are not even speaking about a profession that requires the completion of at least seven years of college,followed by an expensive test and an invasive background check, just for the benefit of staring down the barrel of a 15.5 percent unemployment rate and roughly 200,000 in non-dischargeable student debt. One might even guess that we're talking about how recent studies show that over 40% of law school students suffer from clinical depression, with those unhappy figures only becoming worse as graduates enter a profession with a suicide rate nearly ten times above the national norm. Instead, we are talking about the latest and greatest idea among the old-timers; those old ones who have already won the legal profession lottery, allowing them to seize an upper-middle class lifestyle after matriculating from law schools referred to as'third-tier toilets,' or attending bastions of prestigious opportunity, like Harvard and Yale.

Suzanne, a young woman in San Francisco, met a man--call him John--on the dating site OKCupid. John was attractive and charming. More notably, he indulged in the kind of profligate displays of affection which signal a definite eagerness to commit. He sneaked Suzanne's favorite snacks into her purse as a workday surprise and insisted early on that she keep a key to his apartment. He asked her to help him choose a couch and then spooned with her on all the floor models. He even accompanied her, unprompted, to the D.M.V.--an act roughly equivalent, in today's gallantry currency, to Perseus rescuing Andromeda from the sea monster. As we learn from the podcast "Reply All," which reported the tale, Suzanne was not the only woman on whom John had chosen to bestow his favor. Six months into their relationship, she discovered that he was seeing half a dozen other women, one of whom he'd been stringing along for two years. All of them had received the couch-spooning treatment.

Jill Watson has been a teaching assistant (TA) at Georgia Institute of Technology for months, responding to student's emails and forum messages. But there's a twist: Jill is a robot. She is in fact a robot powered by IBM's Watson system, but students said her emails seemed casual, personal, and to-the-point. The class of over 300 students never met Ms. Watson, but she always responded to emails quickly and casually. "She was the person –well, the teaching assistant– who would remind us of due dates and post questions in the middle of the week to spark conversations," student Jennifer Gavin told the Journal.

We believe in offering our customers choice. We are strongly committed to collaboration with a large partner ecosystem. Many of our partners already offer related APIs on the cloud: Similar technology building blocks are also available from the large and growing open source community and the vibrant academic community with which we interact. We are also committed to collaboration with our existing and emerging Service and ISV partner ecosystem to ensure all the Industries and Lines of Business which SAP serves are addressed by innovative intelligent solutions and service offerings. Our goal is to deliver superior solutions for digital transformation and help customers move quickly into the digital economy.

The Microsoft Azure Machine Learning Algorithm Cheat Sheet helps you choose the right machine learning algorithm for your predictive analytics solutions from the Microsoft Azure Machine Learning library of algorithms. Azure Machine Learning Studio comes with a large number of machine learning algorithms for your predictive analytics solutions. These algorithms fall into the general machine learning categories of regression, classification, clustering, and anomaly detection, and each one is designed to address a different type of machine learning problem. See the article How to choose algorithms for Microsoft Azure Machine Learning for a detailed guide to using this cheat sheet. Download the Machine Learning Algorithm Cheat Sheet and get help figuring out how to choose a machine learning algorithm for your solution.

Organisations, big and small, have recognised the significance of digital impact and are gearing up for transformational changes in their business models by redefining processes, technologies and people capabilities aligned with the emerging needs of their customers. When it comes to people and the need for change, the focus seems to be on equipping them with the skills required to function effectively in the digital world. While this is indeed an essential pre requisite for the success of the transformation programme, with the realisation that'business as usual' would have to change in every aspect of business functioning, in order to be counted in as an effective partner in the transition process and beyond, learning and development function has to rethink its approach to learning design and outcomes. Gone are the days when learning and development function used to be viewed as a tool primarily for motivating employees and despite the frequent discussions on the ROI from the investment made in the learning initiatives, it was generally accepted that measurement of effectiveness and outcomes are difficult to establish. Hence the surveys and feedbacks from learners and their supervisors were the main sources to establish the relevance and the usefulness of the programme.

Many of us fear that the machines will slowly take over and from the looks of it, there might be a time when they will even replace humans in the courtroom, perhaps making it harder for fresh law graduates to find a job straight out of law school. That can be the norm when law firms start hiring "lawyers" powered by artificial intelligence like veteran law firm BakerHostetler did recently. BakerHostetler has "hired" ROSS, it's first digital attorney, who will be performing duties as a legal researcher at the law firm. ROSS is attached with the firm's bankruptcy team and will be helping them with researching cases and facts as they build their cases. This may not be the only law firm that sees that digital lawyers powered by artificial intelligence can prove to be more competent researchers.