Whether it's logging into a closed system from halfway around the globe, or checking e-mails on your phone, the internet has removed geography as a barrier to communication. Unfortunately, recruitment faces other barriers. Posting job listings to tens or even hundreds of locations takes time, as does reviewing CVs, sorting the highly skilled from the rejection pile, before finally conducting interviews. Fortunately, smart applications, powered by artificial intelligence, are changing this. Sage reports that, in two years, the number of businesses using AI to manage operations is expected to increase sharply, from 38% in 2016 to 62% in 2018.

In this setting, we only have access to the stochastic function f(x; ξ), where the random variable ξ is sampled from an underlying distribution D. The task is to optimize the expected function f(x), which in general may be nonconvex. This framework covers a wide range of problems, including the offline setting where we minimize the empirical loss over a fixed amount of data, and the online setting where data arrives sequentially. One of the most prominent applications of stochastic optimization has been in large-scale statistics and machine learning problems, such as the optimization of deep neural networks. Classical analysis in nonconvex optimization only guarantees convergence to a first-order stationary point (i.e., a point x satisfying ‖ f(x)‖ 0), which can be a local minimum, a local maximum, or a saddle point. This paper goes further, proposing an algorithm that escapes saddle points and converges to a local minimum.

For decades, context-dependent phonemes have been the dominant sub-word unit for conventional acoustic modeling systems. This status quo has begun to be challenged recently by end-to-end models which seek to combine acoustic, pronunciation, and language model components into a single neural network. Such systems, which typically predict graphemes or words, simplify the recognition process since they remove the need for a separate expert-curated pronunciation lexicon to map from phoneme-based units to words. However, there has been little previous work comparing phoneme-based versus grapheme-based sub-word units in the end-to-end modeling framework, to determine whether the gains from such approaches are primarily due to the new probabilistic model, or from the joint learning of the various components with grapheme-based units. In this work, we conduct detailed experiments which are aimed at quantifying the value of phoneme-based pronunciation lexica in the context of end-to-end models. We examine phoneme-based end-to-end models, which are contrasted against grapheme-based ones on a large vocabulary English Voice-search task, where we find that graphemes do indeed outperform phonemes. We also compare grapheme and phoneme-based approaches on a multi-dialect English task, which once again confirm the superiority of graphemes, greatly simplifying the system for recognizing multiple dialects.

Mosquitoes are a major vector for malaria, causing hundreds of thousands of deaths in the developing world each year. Not only is the prevention of mosquito bites of paramount importance to the reduction of malaria transmission cases, but understanding in more forensic detail the interplay between malaria, mosquito vectors, vegetation, standing water and human populations is crucial to the deployment of more effective interventions. Typically the presence and detection of malaria-vectoring mosquitoes is only quantified by hand-operated insect traps or signified by the diagnosis of malaria. If we are to gather timely, large-scale data to improve this situation, we need to automate the process of mosquito detection and classification as much as possible. In this paper, we present a candidate mobile sensing system that acts as both a portable early warning device and an automatic acoustic data acquisition pipeline to help fuel scientific inquiry and policy. The machine learning algorithm that powers the mobile system achieves excellent off-line multi-species detection performance while remaining computationally efficient. Further, we have conducted preliminary live mosquito detection tests using low-cost mobile phones and achieved promising results. The deployment of this system for field usage in Southeast Asia and Africa is planned in the near future. In order to accelerate processing of field recordings and labelling of collected data, we employ a citizen science platform in conjunction with automated methods, the former implemented using the Zooniverse platform, allowing crowdsourcing on a grand scale.

The rhopoema nomadica, or nomadic jellyfish, is native to the Indian Ocean but in the eighties, they started turning up in the eastern Mediterranean, presumably through the Suez Canal. Now this jellyfish forms massive plumes, kilometers wide, along the coast of the eastern Mediterranean and Israel. For the first time, recently, a huge plume formed off Egypt's coast, and off Turkey and Lebanon. When it blooms intensely, it can get sucked into the watering systems that power plants use to cool machinery. Jellyfish are gooey, like a sink stopper, and clog the intake systems, so they have to shut down power plants until they can clear the bloom away.

The Islamic extremist group, the deadliest in Africa, has been targeted this year by nearly 30 U.S. military drone strikes after the Trump administration approved expanded operations against it and declared the southern part of the Horn of Africa nation a zone of active hostilities. The U.S. now has more than 500 military personnel in Somalia.

Dell EMC has announced the launch of its new machine learning and deep learning solutions, which according to the company is in line with it continuing its work to bring high-performance computing (HPC) and data analytics capabilities to mainstream enterprises worldwide. Dell EMC believes that this enables organisations to take advantage of the convergence of HPC and data analytics and realise advancements in areas including fraud detection, image processing, financial investment analysis and personalised medicine. According to the company, these new innovations represent the next step in the company's focus on democratising HPC, optimising data analytics with artificial intelligence (AI) technology innovations, and advancing both the HPC and AI communities. While AI techniques, such as machine learning and deep learning, being rapidly being deployed by many organisations across several industries, only a small number possess the expertise to design, deploy and manage such systems to use them effectively for rapidly gaining new insights. Dell EMC believes that by leveraging Dell's ecosystem of partnerships and internal expertise in HPC and data analytics services, the company's new solutions offer customers the ability to harness the power of the massive amounts of their collected data, delivering faster, better and deeper business insights in real-time.

We use a deep learning model trained only on a patient's blood oxygenation data (measurable with an inexpensive fingertip sensor) to predict impending hypoxemia (low blood oxygen) more accurately than trained anesthesiologists with access to all the data recorded in a modern operating room. We also provide a simple way to visualize the reason why a patient's risk is low or high by assigning weight to the patient's past blood oxygen values. This work has the potential to provide cutting-edge clinical decision support in low-resource settings, where rates of surgical complication and death are substantially greater than in high-resource areas.

The U.S. official said armed drone flights could begin as early as next week or at least by the end of December. The memorandum of understanding limits the drones to defensive missions, the official said. The official was not authorized to discuss the matter publicly and so spoke on condition of anonymity.

I don't know how many times I've said "look at the draw distance" to people since Assassin's Creed: Origins ($60 on Amazon) released, but it's a lot. After "going back to their roots" with 2014's disastrous Assassin's Creed: Unity, Ubisoft has shaken up the series again and gone back to its...non-roots? Suffice it to say, Origins channels the spirit of Unity's predecessor, the acclaimed pirate-centric Black Flag. Origins heads to Ptolemaic Egypt instead of sailing the high seas, but the design is very similar, with an enormous map (the largest in the series) dotted with mid-size cities, small towns, oases, and so on. And if you look at screenshots, it might seem like a visual downgrade from Unity and the following year's Assassin's Creed: Syndicate.