China is gearing up to build a technology park in Beijing entirely dedicated to the development of artificial intelligence, news first reported by Xinhua, the country's official press agency. Master plan: The endeavor is just the latest sign of China's remarkable ambition to master and dominate artificial intelligence by 2020. Last year the central government published a three-year-plan to invest huge sums in AI, and to apply the technology across the country's industries and economy (see "China's AI Awakening"). Key details: The plan will apparently establish a "national AI research center" and, interestingly, will include efforts to form partnerships with foreign research institutions and companies. This seems like a smart move given the opportunities presented by China's vast economy, and it could help strengthen the country's position as a force in AI in years to come.

Taiwan Semiconductor Manufacturing Company (TSMC) is going to provide more than 40 clients including Apple and Qualcomm with its 7nm advanced process for chipsets this year. On the contrary, Samsung is still working to find potential customers for its 7nm chip production technology. On Thursday, DigiTimes revealed that TSMC is enjoying a sure win over Samsung in their race of offering 7nm process to various manufacturers this 2018. The Taiwanese company has apparently outpaced the South Korean giant after securing orders from over 40 clients. This means TSMC would be fabricating numerous chips on its advanced 7nm process for mobile communication, high-performance computing and artificial intelligence applications for many companies this year.

Samsung Electronics is expected to unveil its highly anticipated Galaxy S9 flagship phone next month. Ahead of its launch, the South Korean tech giant has announced its new Exynos 9 Series 9810 processor, which features a powerful custom CPU, very fast gigabit LTE modem and sophisticated deep learning capabilities. Samsung's latest premium application processor is so advanced that it has already been selected as a CES 2018 Innovation Awards Honoree in the Embedded Technologies product category ahead of the big Las Vegas event next week. Built on the 10nm process, the Exynos 9810 is more advanced than its predecessors in more ways than one. The Exynos 9810 is designed to carry out seamless multi-tasking.

A lot has been said about AI and the potential it holds for us humans – it has been touted as the panacea and also called the harbinger of global Armageddon. While both these possibilities are exaggerated, one thing that is evident is that there are many benefits to AI, one of which is the role it can play in fostering better sales and marketing alignment. Companies with strongly aligned sales and marketing teams enjoy higher win rates (38%) and are better at closing deals (67%) (Forrester). However, aligning these two departments is often easier said than done. This is where artificial intelligence (AI) comes into play.

Sophia the robot has been on a roll lately. Earlier in the year, its creator David Hanson told Jimmy Fallon that the bot is "basically alive." At the beginning of October, it showed up at the United Nations, announcing to delegates: "I am here to help humanity create the future." And just last week, Sophia was awarded an honorary citizenship by Saudi Arabia. "Sophia the robot becomes first humanoid Saudi citizen."

We introduce the first system towards the novel task of answering complex multi-sentence recommendation questions in the tourism domain. Our solution uses a pipeline of two modules: question understanding and answering. For question understanding, we define an SQL-like query language that captures the semantic intent of a question; it supports operators like subset, negation, preference and similarity, which are often found in recommendation questions. We train and compare traditional CRFs as well as bidirectional LSTM-based models for converting a question to its semantic representation. We extend these models to a semi-supervised setting with partially labeled sequences gathered through crowdsourc-ing. We find that our best model performs semi-supervised training of BiDiL-STM CRF with hand-designed features and CCM(Chang et al., 2007) constraints. Finally, in an end to end QA system, our answering component converts our question representation into queries fired on underlying knowledge sources. Our experiments on two different answer corpora demonstrate that our system can significantly outperform baselines with up to 20 pt higher accuracy and 17 pt higher recall.

Languages shared by people differ in different regions based on their accents, pronunciation and word usages. In this era sharing of language takes place mainly through social media and blogs. Every second swing of such a micro posts exist which induces the need of processing those micro posts, in-order to extract knowledge out of it. Knowledge extraction differs with respect to the application in which the research on cognitive science fed the necessities for the same. This work further moves forward such a research by extracting semantic information of streaming and batch data in applications like Named Entity Recognition and Author Profiling. In the case of Named Entity Recognition context of a single micro post has been utilized and context that lies in the pool of micro posts were utilized to identify the sociolect aspects of the author of those micro posts. In this work Conditional Random Field has been utilized to do the entity recognition and a novel approach has been proposed to find the sociolect aspects of the author (Gender, Age group).

Cluster analysis and outlier detection are strongly coupled tasks in data mining area. Cluster structure can be easily destroyed by few outliers; on the contrary, the outliers are defined by the concept of cluster, which are recognized as the points belonging to none of the clusters. However, most existing studies handle them separately. In light of this, we consider the joint cluster analysis and outlier detection problem, and propose the Clustering with Outlier Removal (COR) algorithm. Generally speaking, the original space is transformed into the binary space via generating basic partitions in order to define clusters. Then an objective function based Holoentropy is designed to enhance the compactness of each cluster with a few outliers removed. With further analyses on the objective function, only partial of the problem can be handled by K-means optimization. To provide an integrated solution, an auxiliary binary matrix is nontrivally introduced so that COR completely and efficiently solves the challenging problem via a unified K-means- - with theoretical supports. Extensive experimental results on numerous data sets in various domains demonstrate the effectiveness and efficiency of COR significantly over the rivals including K-means- - and other state-of-the-art outlier detection methods in terms of cluster validity and outlier detection. Some key factors in COR are further analyzed for practical use. Finally, an application on flight trajectory is provided to demonstrate the effectiveness of COR in the real-world scenario.

The year 2017 was a watershed moment for the Indian Banking industry, defined by reform tailwinds like demonetisation, digital India drive and global changes like rapid technological advances and an exponential rise in computing power. From experimentation of use cases on the Block chain technology, Artificial Intelligence (AI) and Machine Learning to bolstering operations through Bots and RPA (robotic process automation), the industry is today geared to embrace challenges and opportunities of the future. It wouldn't, hence, be a hyperbole to define 2018 as the "Year of Cognitive Banking"; taking the industry to an inflection point by strategically blending technology with processes for real-time business impact. Banks will start meaningfully adopting machine learning tools and techniques to draw insights from various data points employed to collect customer's profile and transaction behavior, in order to predict user needs and design better customer experience. With increasing implementation of Big Data and Mobility Solutions by Banks, we could see a new wave of Analytics of Things or AOT, which would help banks analyze customer interactions with various devices on IoT and deploy this information to enhance customer experience and design better lending opportunities. As the current governing regime moves into the last year of its term, implementation of Smart Cities could see heightened activity and 2018 could herald interesting times for connected payments and IoT.

Last year at CES, LG introduced a bunch of new robots because, as near as we could tell, LG figured that robots were cool so they'd better make some robots or something. The most photogenic (and smallest) was Hub, which bore a striking resemblance to Jibo, but we also met two burly service robots designed to work at airports. For CES 2018, LG is adding three more robots to the CLOi (that's pronounced KLOH-ee, obviously) family. New this year are the Serving Robot, Porter Robot, and Shopping Cart Robot, "developed for commercial use at hotels, airports, and supermarkets," and it's definitely not a coincidence that they're just in time for the 2018 Winter Olympics in South Korea, where LG is also based. The purpose of the Serving Robot is to deliver meals and drinks to guests and customers at hotels and airport lounges quickly and efficiently. The robot can deliver food or refreshments around the clock and with its built-in sliding tray, present the tray to the customer for easy removal.