A team of Microsoft researchers from China and the US have developed an artificial intelligence (AI) powered translation system that can translate Chinese language news articles into English with human accuracy. Check out the latest findings on how the hype around artificial intelligence could be sowing damaging confusion. Also, read a number of case studies on how enterprises are using AI to help reach business goals around the world. You forgot to provide an Email Address. This email address doesn't appear to be valid.

This Is An extract in English of Pierre Pinna's Interview on CNN Turkey. IPFC Online Founder and CEO Pierre Pinna, one of the world-renowned names in artificial intelligence and digital transformation issues that brings together entrepreneurial companies in Turkey, national and international investors, participated at the T-Bootcamp event in Izmir, explaining the future. One of the most important meeting points of entrepreneurs and investors, the T-Bootcamp event, which emphasizes the innovation efforts in Turkey, was organized at the Selçuk Yaşar Campus in Izmir with the cooperation of Yaşar University Minerva Incubation Center and technology platform creation agency WBCONS-HD. Among the leading names in the world of artificial intelligence and digital convergence, IPFC Online Founder and CEO Pierre Pinna, Fintech and Blockchain applications that are rapidly expanding include Inclusivity Network Founder Antonio Javier Ruiz, Peak State Consulting Director Anuj Khanna, Technology and Human College Founder Zeynep Dereli and entrepreneurs from Izmir and Istanbul participated as speakers. Entrepreneurs brought in prominent projects.

Fujitsu Limited and Fujitsu Hokuriku Systems Limited announced on 13 February 2018 that, in partnership with Tokyo's Kita City, they are conducting a field trial to evaluate how AI can be used to streamline tasks associated with guidance and supervision of nursing-care benefit claims from service providers, which Kita City employees customarily process by hand. The field trial will utilize Fujitsu Human Centric AI Zinrai, Fujitsu's approach to artificial intelligence, and will be conducted from January through March 2018 as part of efforts to enhance social security benefits. As Japan's society continues to age rapidly, Kita City is working to create an environment where the elderly can live in health and safety. In recent years, however, the number of people recognized as requiring nursing care and the number of nursing-care facilities have both been increasing, which has consequently increased the volume of analysis and guidance tasks associated with payments for nursing-care benefit claims, leading to problems with increased burdens on such employees. In this field trial, machine learning technology developed by Fujitsu Hokuriku Systems, which combines customer business expertise and software development technology, is put to use by systems engineers to create a model to analyze the appropriateness of claim details.

Data quality issues have attracted widespread attention due to the negative impacts of dirty data on data mining and machine learning results. The relationship between data quality and the accuracy of results could be applied on the selection of the appropriate algorithm with the consideration of data quality and the determination of the data share to clean. However, rare research has focused on exploring such relationship. Motivated by this, this paper conducts an experimental comparison for the effects of missing, inconsistent and conflicting data on classification, clustering, and regression algorithms. Based on the experimental findings, we provide guidelines for algorithm selection and data cleaning.

Accurate demand forecasts can help on-line retail organizations better plan their supply-chain processes. The challenge, however, is the large number of associative factors that result in large, non-stationary shifts in demand, which traditional time series and regression approaches fail to model. In this paper, we propose a Neural Network architecture called AR-MDN, that simultaneously models associative factors, time-series trends and the variance in the demand. We first identify several causal features and use a combination of feature embeddings, MLP and LSTM to represent them. We then model the output density as a learned mixture of Gaussian distributions. The AR-MDN can be trained end-to-end without the need for additional supervision. We experiment on a dataset of an year's worth of data over tens-of-thousands of products from Flipkart. The proposed architecture yields a significant improvement in forecasting accuracy when compared with existing alternatives.

WASHINGTON -- The Trump administration accused Russia on Thursday of a concerted, ongoing operation to hack and spy on the U.S. energy grid and other critical infrastructure, and separately imposed sanctions on Russian officials for alleged high-tech interference in the 2016 American presidential election. U.S. national security officials said the FBI, the Homeland Security Department and American intelligence agencies determined that Russian intelligence and others were behind the attacks on the energy sector. The officials said the Russians deliberately chose U.S. energy industry targets, obtaining access to computer systems and then conducting "network reconnaissance" of industrial control systems that run American factories and the electricity grid. The U.S. government has helped energy businesses kick out the Russians from all systems currently known to have been penetrated, according to the officials. U.S. sanctions on Russia remain largely symbolic The officials, who briefed reporters on condition of anonymity to discuss sensitive national security information, left open the possibility of discovering more breaches, and said the federal government was issuing an alert to the energy industry to raise awareness about the threat and improve preparation.

In Arabic, Indian or Eastern cultures where people can't really have an open dating profile, the traditional Tinder/Happn/Bumble/Badoo etc dating apps don't work too well as they are based on images. It turns out chat bots may be the way forward in these markets if a recent VC investment is anything to go by. NearGroup, a chatbot allowing users to connect with like-minded people based on proximity, personality and their creative content has raised a $1.6m (£1.2m) seed round led by OpenOcean, with participation from Neotribe and BoostVC. NearGroup will use the funding to expand in Asia Pacific, the US and Europe. The NearGroup chatbot (open in for Messenger) allows users to read the'stories' of individuals nearby, and reply to people they want to start a conversation with.

Amid a world-wide crisis in the bee industry, two companies have formed a joint venture to produce honey sustainably in the UAE. With summer flowers out and in full bloom bees are finding lots of pollen for their hives. SAN FRANCISCO -- Birds do it. Now even educated Walmart drones may do it. The world's largest retailer has applied for a patent for drone pollinators to make up for the decline in bees and other insects that fertilize crops and make much of the food the company sells possible.

Pathway Data Science aims to address growing market demand for professional data science and machine learning expertise in Asia. Pathway Data Science ("Pathway"), a newly established data science and machine learning consultancy, today announced the launch of its services in Hong Kong. Based in Hong Kong, Pathway aims to help businesses across the Asia Pacific region achieve higher levels of performance by putting advanced data science tools into application. Core services include advising organizations on processes to become more data-driven, providing new insights on existing data, building intuitive dashboards, developing machine learning models and producing real-life applications that can be seamlessly integrated with clients' proprietary processes. Machine learning techniques make it possible for a computing system to learn from data, answer questions, make predictions, reach conclusions and solve problems without the need to specify an explicit set of rules required to achieve the desired outcome.

Researchers at the company's labs in the U.S. and Asia said they have achieved human parity when translating the newstest2017 collection of news articles from Chinese to English. The articles are commonly used when testing and benchmarking translation results. Microsoft hired third-party bilingual human evaluators to assess the suitability of its methodology. The evaluators compared the results of Microsoft's AI with translations produced by two human linguists. The human translators worked independently of each other to create their renditions of the news stories.