Artificial intelligence (AI) poses the greatest threat to the oil and gas industry over the next five to 10 years, according to Microsoft's oil and gas director for the Middle East and Africa.

Robots may keep Tesla's CEO up at night, but companies around the globe are interested in putting them to work, according to new research from Tractica. In a press release Tractica, the market intelligence firm, announced its forecast that more than 23,000 robots will be deployed for customer service applications from last year through 2022. During the forecast period, the robots will generate $451 million in revenue. Nearly half of all the customer service robots will be found in Asia Pacific, but there will also be growth in the U.S. and Europe. "Fewer than five years ago, hardly anyone had seen or heard of robots in public and commercial spaces, as most of the developments were restricted to research labs," says research analyst Manoj Sahi in the press release highlighting results of its latest research.

Jane Zavalishina is the CEO of Yandex Data Factory. Vyacheslav Polonski is a PhD student at the University of Oxford and the CEO of Avantgarde Analytics. For years, experts have warned against the unanticipated effects of general artificial intelligence (AI) on society. Ray Kurzweil predicts that by 2029 intelligent machines will be able to outsmart human beings. Stephen Hawking argues that "once humans develop full AI, it will take off on its own and redesign itself at an ever-increasing rate."

Data sharing and data within digital literacy were among the subjects addressed by expert witnesses during the second House of Lords select committee hearing on artificial intelligence (AI). Every conference this year contains a dead human genius reincarnated as software system or a robot. Yes, there is a lot of hype, but there is real worth in AI and Machine Learning. Read our counseling on how to avoid adopting "black box" approach. You forgot to provide an Email Address.

A team of scientists in the United Kingdom and the U.S. recently reported the discovery of pathological signs of Alzheimer's disease in dolphins, animals whose brains are similar in many ways to those of humans. This is the first time that these signs – neurofibrillary tangles and two kinds of protein clusters called plaques – have been discovered together in marine mammals. As neuroscience researchers, we believe this discovery has added significance because of the similarities between dolphin brains and human brains. The new finding in dolphins supports the research team's hypothesis that two factors conspire to raise the risk of developing Alzheimer's disease in dolphins. Those factors are: longevity with a long post-fertility life span – that is, a species living, on average, many years after the child-bearing years are over – and insulin signaling.

At HelloFresh, we want to change the way people eat. Over the past 5 years we've seen this mission spread beyond our wildest dreams. So, how did we do it? Our weekly recipe boxes full of exciting recipes and lovingly sourced, fresh ingredients have blossomed into a community of inspired, energised home cooks that expands across the globe. Our story started in Berlin.

Many efforts have been devoted to training generative latent variable models with autoregressive decoders, such as recurrent neural networks (RNN). Stochastic recurrent models have been successful in capturing the variability observed in natural sequential data such as speech. We unify successful ideas from recently proposed architectures into a stochastic recurrent model: each step in the sequence is associated with a latent variable that is used to condition the recurrent dynamics for future steps. Training is performed with amortized variational inference where the approximate posterior is augmented with a RNN that runs backward through the sequence. In addition to maximizing the variational lower bound, we ease training of the latent variables by adding an auxiliary cost which forces them to reconstruct the state of the backward recurrent network. This provides the latent variables with a task-independent objective that enhances the performance of the overall model. We found this strategy to perform better than alternative approaches such as KL annealing. Although being conceptually simple, our model achieves state-of-the-art results on standard speech benchmarks such as TIMIT and Blizzard and competitive performance on sequential MNIST. Finally, we apply our model to language modeling on the IMDB dataset where the auxiliary cost helps in learning interpretable latent variables. Source Code: \url{https://github.com/anirudh9119/zforcing_nips17}

'A stable bright light, larger than anything practical shined into my room on the second floor, not making any noise; it disappeared.' It's one of nearly 60,000 unsettling stories revealed in a new map of the contiguous United States, compiling UFO sightings from every state, dating back to 1995. While these mysterious encounters may largely have slipped out of the public eye after the Cold War-era UFO craze died down, the map shows reports have steadily grown in the last two decades, hitting a mid-summer peak each year. The map shows these reports are concentrated in major cities and dense population hubs, making places like New York and the surrounding metropolitan area hotspots for UFO sightings, along with southern and central California. The new map of reported UFO sightings in the US was created by Data Solutions Engineer Adam Crahen of the Data Duo, using data from Kaggle UFO sightings. There's little doubt that the internet has played a role in the growth of UFO reports in recent years, though most can be explained by natural or human-caused phenomena.

The pace of artificial intelligence technology adoption in healthcare varies considerably. Some medical establishments are undertaking small incremental changes; others centers have seen several years of innovation; and a proportion remain tied to the traditional healthcare model of the 1990s. This is the view of Dr. Ameet Bakhai, deputy director of research at the Royal Free London NHS Foundation Trust. Dr. Bakhai was expressing his views in advance of a major conference that is set to look at artificial intelligence in healthcare: Digital Healthcare Transformation Summit 2017, which takes place in London in December. A key theme is that although there are more advanced machines, from ultra-high-resolution imaging instruments to surgical robots, these tend to remain fully controlled by humans rather than with decisions made by artificial intelligence.