Amid the realignment of jobs and changing business models, companies are aligning goals with the world in a quest for a global AI network. This autumn or post-monsoon, depending on which part of the world you live in, the movie Blade Runner will see a return after 35 years. If you remember the first movie, the artificial intelligence character, or the "replicant", the antagonist, played by Rutger Hauer, saves the protagonist, played by Harrison Ford, from dying. After that, the protagonist witnesses the AI character's programmes terminate themselves. Ford then says: "I don't know why he saved my life. Maybe in those last moments he loved life more than he ever had before. All he'd wanted were the same answers the rest of us want. Where did I come from? How long have I got? All I could do was sit there and watch him die."

Metro Manila (CNN Philippines, September 6) -- The Trade Department is sounding the alarm on the threat posed by artificial intelligence (AI) on hundreds of thousands of jobs in the country's $25-billion business process outsourcing (BPO) industry. "AI has presented itself more than just as a new technology, but as a threat to the current employees servicing the service export industry and the BPO, including the contact centers," the Department of Trade and Industry (DTI) said in a statement Wednesday. It warned that AI can "potentially diminish 45 to 50 percent of the approximately 1.2 million Filipino employees of the BPO industry." Trade Secretary Ramon Lopez called on the academe, business, and technology sectors to step up the retraining in higher value-added skills of BPO employees. "Let us retool and reposition the nature of the current jobs in the industry," he said in the statement.

In the past few years, China has dived head first into artificial intelligence (AI) research, with the goal of becoming the de facto world leader in this game-changing technology. According to The Economist, from 2012 to 2016, Chinese AI companies received US$2.6 billion in funding while US peers received US$17.9 billion, but this is quickly changing. China, earlier seen as a technology development laggard, is now grasping AI as an opportunity to leapfrog foreign peers. Over 40 per cent of the top AI-related academic papers published worldwide in 2015 had at least one or more Chinese researchers. Chinese AI-based patent applications grew 186 per cent between 2010 and 2014, a huge increase from the previous five-year period.

Giancarlo Zaccone has more than ten years of experience in managing research projects both in scientific and industrial areas. He worked as researcher at the C.N.R, the National Research Council, where he was involved in projects relating to parallel computing and scientific visualization. Currently, he is a system and software engineer at a consulting company developing and maintaining software systems for space and defense applications. He is author of the following Packt volumes: Python Parallel Programming Cookbook and Getting Started with TensorFlow. Rezaul Karim has more than 8 years of experience in the area of research and development with a solid knowledge of algorithms and data structures, focusing C/C, Java, Scala, R, and Python and big data technologies such as Spark, Kafka, DC/OS, Docker, Mesos, Hadoop, and MapReduce.

This paper makes two contributions to Bayesian machine learning algorithms. Firstly, we propose stochastic natural gradient expectation propagation (SNEP), a novel alternative to expectation propagation (EP), a popular variational inference algorithm. SNEP is a black box variational algorithm, in that it does not require any simplifying assumptions on the distribution of interest, beyond the existence of some Monte Carlo sampler for estimating the moments of the EP tilted distributions. Further, as opposed to EP which has no guarantee of convergence, SNEP can be shown to be convergent, even when using Monte Carlo moment estimates. Secondly, we propose a novel architecture for distributed Bayesian learning which we call the posterior server. The posterior server allows scalable and robust Bayesian learning in cases where a data set is stored in a distributed manner across a cluster, with each compute node containing a disjoint subset of data. An independent Monte Carlo sampler is run on each compute node, with direct access only to the local data subset, but which targets an approximation to the global posterior distribution given all data across the whole cluster. This is achieved by using a distributed asynchronous implementation of SNEP to pass messages across the cluster. We demonstrate SNEP and the posterior server on distributed Bayesian learning of logistic regression and neural networks. Keywords: Distributed Learning, Large Scale Learning, Deep Learning, Bayesian Learn- ing, Variational Inference, Expectation Propagation, Stochastic Approximation, Natural Gradient, Markov chain Monte Carlo, Parameter Server, Posterior Server.

Item cold-start is a classical issue in recommender systems that affects anime and manga recommendations as well. This problem can be framed as follows: how to predict whether a user will like a manga that received few ratings from the community? Content-based techniques can alleviate this issue but require extra information, that is usually expensive to gather. In this paper, we use a deep learning technique, Illustration2Vec, to easily extract tag information from the manga and anime posters (e.g., sword, or ponytail). We propose BALSE (Blended Alternate Least Squares with Explanation), a new model for collaborative filtering, that benefits from this extra information to recommend mangas. We show, using real data from an online manga recommender system called Mangaki, that our model improves substantially the quality of recommendations, especially for less-known manga, and is able to provide an interpretation of the taste of the users.

Dubai: Artificial intelligence (AI) will play a stronger role in the cyber security space in the future and the key purpose is to initially help automate mundane tasks, like prioritising security logs, so that companies can reduce the human time and effort. Unfortunately, what mostly happens today is cyber blindness, essentially because there is no way to manually check the huge amount of data that cyber experts process every day. The industry is faced with two options again: to leave the data as it is, leaving the possibility open of looking back to the past to verify data or to develop something, which could help solutions providers to analyse real time logs and take decisions. The second option is called machine learning or AI. More and more organisations are choosing machine learning and artificial intelligence today.

Smartphone makers are betting on camera features to help their flagship devices stand out. Samsung launched its first dual-cameras on the Note 8, Sony introduced super slow-mo video-recording on its XZ Premium and XZ1 series, while LG equipped the V30 with a glass lens that boasts a wide f/1.6 aperture. But Huawei has chosen a different route. In lieu of a new phone, the company showed off its Kirin 970 chip at IFA 2017, calling attention to the chipset's AI capabilities. The Kirin 970 will power Huawei's next flagship phone, the Mate 10, which is set to launch at a separate October event in Munich.

In this special guest feature, David McLaughlin, CEO and Founder of QuantaVerse, discusses how advancements in data science, including artificial intelligence (AI), machine learning and big data, promise to stifle money laundering and change outcomes for victims around the globe. Financial institutions have begun working smarter through the use of AI and machine learning to help banks dramatically improve the efficiency and effectiveness of money laundering investigations. David McLaughlin is CEO and founder of QuantaVerse, an innovator of data science and artificial intelligence (AI) solutions purpose-built for identifying financial crimes. David spent six years as a naval officer, starting in 1986 as an Ensign in the U.S. Navy and attending flight school in Pensacola, FL. He is a graduate from the highly regarded TOPGUN program, and completed a combat tour in the Persian Gulf where he was awarded the Distinguished Flying Cross and two Air Medals for bravery in combat. Prior to founding QuantaVerse, David held senior executive positions with IPR International, NES Financial and SEI.

Hacks are often caused by our own stupidity, but you can blame tech companies for a new vulnerability. Researchers from China's Zheijiang University found a way to attack Siri, Alexa and other voice assistants by feeding them commands in ultrasonic frequencies. Those are too high for humans to hear, but they're perfectly audible to the microphones on your devices. With the technique, researchers could get the AI assistants to open malicious websites and even your door if you had a smart lock connected. The relatively simple technique is called DolphinAttack.