In the West, we rely on the grid, which provides most people with ample power. In off-grid communities such as those in large parts of rural Africa, energy is a highly valued resource and consumers are much more aware of energy efficiency. The limited energy that is available is disproportionately expensive and innovative solutions, such as small-scale renewable power, that cannot yet compete in the West, are gaining ground where, compared to the cost of the fossil fuels they replace, they are seen as a bargain. Developments such as small solar home systems are bringing power for the first time to millions of off-grid consumers in sub-Saharan Africa, thanks to technological advances in LED lights, batteries and mobile payment, creating what many are referring to as the "clean energy revolution" in rural electrification. While LED lighting and phone charging were the first volume application in this rapidly evolving market, consumers of the clean energy revolution in Africa want, and increasingly demand, more. Customers now expect to be able to access the latest technology, media and communications through the growth of the largely familiar pay-as-you-go technology, even in areas where there is no little or no grid access.

We provide a theoretical foundation for non-parametric estimation of functions of random variables using kernel mean embeddings. We show that for any continuous function $f$, consistent estimators of the mean embedding of a random variable $X$ lead to consistent estimators of the mean embedding of $f(X)$. For Mat\'ern kernels and sufficiently smooth functions we also provide rates of convergence. Our results extend to functions of multiple random variables. If the variables are dependent, we require an estimator of the mean embedding of their joint distribution as a starting point; if they are independent, it is sufficient to have separate estimators of the mean embeddings of their marginal distributions. In either case, our results cover both mean embeddings based on i.i.d. samples as well as "reduced set" expansions in terms of dependent expansion points. The latter serves as a justification for using such expansions to limit memory resources when applying the approach as a basis for probabilistic programming.

The reparameterization gradient has become a widely used method to obtain Monte Carlo gradients to optimize the variational objective. However, this technique does not easily apply to commonly used distributions such as beta or gamma without further approximations, and most practical applications of the reparameterization gradient fit Gaussian distributions. In this paper, we introduce the generalized reparameterization gradient, a method that extends the reparameterization gradient to a wider class of variational distributions. Generalized reparameterizations use invertible transformations of the latent variables which lead to transformed distributions that weakly depend on the variational parameters. This results in new Monte Carlo gradients that combine reparameterization gradients and score function gradients. We demonstrate our approach on variational inference for two complex probabilistic models. The generalized reparameterization is effective: even a single sample from the variational distribution is enough to obtain a low-variance gradient.

This paper explores the capabilities of convolutional neural networks to deal with a task that is easily manageable for humans: perceiving 3D pose of a human body from varying angles. However, in our approach, we are restricted to using a monocular vision system. For this purpose, we apply a convolutional neural network approach on RGB videos and extend it to three dimensional convolutions. This is done via encoding the time dimension in videos as the 3\ts{rd} dimension in convolutional space, and directly regressing to human body joint positions in 3D coordinate space. This research shows the ability of such a network to achieve state-of-the-art performance on the selected Human3.6M dataset, thus demonstrating the possibility of successfully representing temporal data with an additional dimension in the convolutional operation.

This is Patricia Murphy, Vice President of Investor Relations for IBM. I'd like to welcome you to our third quarter earnings presentation. The prepared remarks will be available within a couple of hours and a replay of the webcast will be posted by this time tomorrow. I'll remind you that certain comments made in this presentation may be characterized as forward-looking under the Private Securities Litigation Reform Act of 1995. Those statements involve a number of factors that could cause actual results to differ materially. Additional information concerning these factors is contained in the Company's filings with the SEC. Copies are available from the SEC, from the IBM website, or from us in Investor Relations. Our presentation also includes certain non-GAAP financial measures in an effort to provide additional information to investors. All non-GAAP measures have been reconciled to their related GAAP measures in accordance with SEC rules. You'll find reconciliation charts at the end of the presentation and in the form 8-K submitted to the SEC today. So with that, I'll turn the call over to Martin Schroeter. In the third quarter, we generated 19.2 billion in revenues, 3.7 billion in pre-tax income and 3.29 of operating earnings per share. As we think back to the discussion 90 days ago, it was around Brexit and its impact on Europe, global spending and sectors like banking and the attractiveness of investment in the emerging markets, all of these topics have the capacity to drive some volatility and results, but what you see in our third quarter results is stability in our revenue with continued strong growth and strategic imperatives and a top and bottom line consistent with what we expected. Our revenue was essentially flat relative to last year. Looking at the revenue dynamics, I want to point out a few things. Our clients are focussed on becoming digital businesses and have strong growth in cloud, security, mobile, and across our analytics portfolio reflects this. In total, we continue to deliver double-digit revenue growth in our strategic imperatives led by our cloud business. Cloud delivered as-a-service is part of a solid recurring revenue base across software and services, and our annuity revenue continued to grow. Of course, the acquisitions we made in the last 12 months contributed to growth about the same amount as last quarter and for the first time in quite a while currency was a modest tailwind to revenue growth.

Ebay this morning launched a new site, dedicated to shopping for furniture and other items for the home. Called eBay Collective, the site also takes advantage of technology from the company's recently announced acquisition of visual search engine Corrigon, which it bought for under 30 million. On eBay Collective, the technology has been integrated to power a "Shop the Room" feature which lets online shoppers hover over an image of a fully designed space, and then the tool will search across eBay inventory to surface items that are close matches to that portion of the image. Corrigon, which had been around since 2008, had developed a way to search and identify objects within an image, then match that with other images or links to products. In a larger photo, you can hover over a specific portion of the image and Corrigon's tech can see the object in that section, then match it with others.

A centuries-old Yemeni city stands alongside the gleaming towers of Hong Kong as one of the world's most beautiful architectural views, writes Jonathan Glancey. And, like the faces of those we hold dear, we hold certain skylines in our minds' eyes even when far … This election has been particularly noisy. Ask not what the government can do for Silicon Valley; ask what Silicon Valley can do for the government. How a tiny Florida community could influence the way we fight Zika around the world.By Graphics by Ella KoezePhotography by Erika LarsenIllustrations … The Harry Potter books have sold more than 400 million copies worldwide and been translated in over 60 languages. The books are filled with a tricky mix of wordplay, invented words, songs, allusions, British cultural references, and more.

Amazon may soon be adding'internet service provider' to its long list of skills. People familiar with the matter revealed the eCommerce giant is considering this service, first for its European customers. This new venture would let Amazon bundle internet access with its Prime video streaming, which would ultimately increase its membership base. People familiar with the matter revealed the eCommerce giant is considering this service for its European customers. A person briefed on the discussion told The Information that Amazon is considering offering internet access to its European customers.

Zürich, Switzerland / Bad Neustadt, Germany - 18 Oct 2016: Today, RHÖN-KLINIKUM AG (RKA), a private hospital group in Germany, has announced, that by the end of the year, it will begin piloting a Watson-powered cognitive assistance system to help support physicians at the group's Centre for Undiagnosed and Rare Diseases located at the University Hospital Marburg. Since it opened in 2013, the renowned Center has been contacted by more than 6,000 patients to visit Prof. Dr. Jürgen Schäfer, a leading expert in rare diseases, who is also known as the "German Dr. House," based on the character of the eponymous American medical television drama. Most of the patients he and his team meets with have year-long medical histories, which include a large amount of unstructured data, such as laboratory tests, clinical reports, drug prescriptions, radiology findings as well as pathology reports. "It's not uncommon for our patients to have thousands of medical documents, leaving us overwhelmed, not only by the large number of patients, but also by the huge amount of data to be reviewed," said Prof. Dr. Jürgen Schäfer, University Hospital Marburg. "This is especially challenging because our work is often like searching for the proverbial needle in the haystack -- even the smallest piece of information could lead to an accurate diagnosis."

Why is it that every time humans develop a really clever computer system in the movies, it seems intent on killing every last one of us at its first opportunity? In Stanley Kubrick's masterpiece, 2001: A Space Odyssey, HAL 9000 starts off as an attentive, if somewhat creepy, custodian of the astronauts aboard the USS Discovery One, before famously turning homicidal and trying to kill them all. In The Matrix, humanity's invention of AI promptly results in human-machine warfare, leading to humans enslaved as a biological source of energy by the machines. In Daniel H. Wilson's book Robopocalypse, computer scientists finally crack the code on the AI problem, only to have their creation develop a sudden and deep dislike for its creators. Is Siri just a few upgrades away from killing you in your sleep? And you're not an especially sentient being yourself if you haven't heard the story of Skynet (see The Terminator, T2, T3, etc.) The simple answer is that -- movies like Wall-E, Short Circuit, and Chappie, notwithstanding -- Hollywood knows that nothing guarantees box office gold quite like an existential threat to all of humanity. Whether that threat is likely in real life or not is decidedly beside the point. How else can one explain the endless march of zombie flicks, not to mention those pesky, shark-infested tornadoes? The reality of AI is nothing like the movies. Siri, Alexa, Watson, Cortana -- these are our HAL 9000s, and none seems even vaguely murderous. The technology has taken leaps and bounds in the last decade, and seems poised to finally match the vision our artists have depicted in film for decades. Is Siri just a few upgrades away from killing you in your sleep, or is Hollywood running away with a tired idea? Looking back at the last decade of AI research helps to paint a clearer picture of a sometimes frightening, sometimes enlightened future. An increasing number of prominent voices are being raised about the real dangers of humanity's continuing work on so-called artificial intelligence.