Beijing: With its economy slowing down, China is seeking to reorganize its manufacturing platforms from cheap products to cutting edge technology like AI. China plans to expand its artificial intelligence (AI) products market to over US 15 billion by speeding up the manufacturing of products like robots, home appliances and mobile phones as part of efforts to develop new technologies to reorient its sluggish economy. Under the plan, China will cultivate and develop emerging artificial intelligence industries, promote innovation in intelligent products and enhance the intelligence level of terminal products. The programme will involve key projects such as intelligent home appliances, smart automobiles, intelligent unmanned systems, intelligent wearable devices and robots. By 2018, China shall build platforms for fundamental AI resources and innovation and make breakthroughs on basic core technology, the three-year implementation programme for'Internet Plus' artificial intelligence said.

In the beginning of 2016 Jill Watson, an IBM-designed bot, has been helping graduate students at Georgia Institute of Technology solve problems with their design projects. Responding to questions over email and posted on forums, Jill had a casual, colloquial tone, and was able to offer nuanced and accurate responses within minutes. A robot has been teaching graduate students for 5 months and none of them realized. Here are just a few of artificial intelligence tools and technologies that will shape and define the educational experience of the future. Duolingo is the world's most popular platform to learn a language.

This year it feels like robots are suddenly everywhere. Geneva airport is trialling a robotic "baggage butler". Adidas has announced it will make shoes at a German facility populated overwhelmingly by machines. We are already driving cars that make split-second corrections to our poor decisions, and Google and others are advancing ever closer to allowing us to simply sit back and let the vehicle do all of the work. There are retailers and logistics companies investigating the potential of drones delivering everything from groceries and takeaways to vital medicine and emergency aid, while various stories of robotic doctors, robotic bankers and robotic artificial intelligence are a newsfeed staple. This is really all as the science fiction of the 20th century predicted.

Welcome to our 11th addition of The FR. This week, we discuss the coming of the robots to financial services and the Bitcoin civil war. We also take a look at "stack fallacy," Max Levchin's Affirm, IEX, Cornell's tech-infused MBA and the little digital bank on the prairie. Is Wall Street destined for Planet of the Robos? According to George Mason University's Robin D. Hanson, it's not a question of if but when the jobs of highly skilled, specialized workers are automated, since computers eventually will have the "mental powers" to do everything humans now do and more (See here).

QUETTA, PAKISTAN – The family of a driver who was killed alongside Taliban chief Mullah Akhtar Mansour in a U.S. drone strike in Pakistan has filed a case against U.S. officials, seeking to press murder charges, police said Sunday. Mansour had entered Pakistan from Iran using a false name and fake Pakistani identity documents on May 21, when his car was targeted by a U.S. drone. The driver, who was also killed, was later identified as Mohammed Azam. The police filed a case on behalf of Azam's family, police official Abdul Wakil Mengal said. It was not immediately clear what legal avenues the family can realistically pursue.

Three years later in 2016, enough time has passed to discern patterns from trends. In that time the industry has experienced seismic shifts and a sweeping wave of consolidation. So let's take another look at the state of the digital nation and why, for the bold, great opportunity lies ahead. There's plenty of additional reading in the links for those who want to go down the rabbit hole, as well as a reference table at the end. Happy to continue the discussion on Twitter using the hashtag #DigitalNation at @ezyjules and @marvelapp. A sweeping wave of acquisitions has decimated the ranks of independent agencies and formed two clashing clans. On the one side are the giants of advertising and marketing and on the other the titans of management consultancy. Meanwhile the market over which they are fighting is in the midst of a multi-faceted existential crisis. Over the last four years the design consultancy industry has experienced an unprecedented period of consolidation, building to a ...

We show that the climate phenomena of El Nino and La Nina arise naturally as states of macro-variables when our recent causal feature learning framework (Chalupka 2015, Chalupka 2016) is applied to micro-level measures of zonal wind (ZW) and sea surface temperatures (SST) taken over the equatorial band of the Pacific Ocean. The method identifies these unusual climate states on the basis of the relation between ZW and SST patterns without any input about past occurrences of El Nino or La Nina. The simpler alternatives of (i) clustering the SST fields while disregarding their relationship with ZW patterns, or (ii) clustering the joint ZW-SST patterns, do not discover El Nino. We discuss the degree to which our method supports a causal interpretation and use a low-dimensional toy example to explain its success over other clustering approaches. Finally, we propose a new robust and scalable alternative to our original algorithm (Chalupka 2016), which circumvents the need for high-dimensional density learning.

This paper proposes CF-NADE, a neural autoregressive architecture for collaborative filtering (CF) tasks, which is inspired by the Restricted Boltzmann Machine (RBM) based CF model and the Neural Autoregressive Distribution Estimator (NADE). We first describe the basic CF-NADE model for CF tasks. Then we propose to improve the model by sharing parameters between different ratings. A factored version of CF-NADE is also proposed for better scalability. Furthermore, we take the ordinal nature of the preferences into consideration and propose an ordinal cost to optimize CF-NADE, which shows superior performance. Finally, CF-NADE can be extended to a deep model, with only moderately increased computational complexity. Experimental results show that CF-NADE with a single hidden layer beats all previous state-of-the-art methods on MovieLens 1M, MovieLens 10M, and Netflix datasets, and adding more hidden layers can further improve the performance.

Malignant mesothelioma is a rare form of cancer that affects the thin cell lining(mesothelium) of the body's internal organs and structures. The most common area affected is the lining of lungs and the chest wall, less commonly the lining of the abdomen and rarely, the sac surrounding the heart or the testis. More than 80% 0f Mesothelioma are a result of exposure to Asbestos. However, it may also be related to previous simian virus(SV40) infections, and to some extent, genetic predisposition. Molecular mechanism can also be implicated in the development of mesothelioma.