Artificial neural network (ANN) is a very useful tool in solving learning problems. Boosting the performances of ANN can be mainly concluded from two aspects: optimizing the architecture of ANN and normalizing the raw data for ANN. In this paper, a novel method which improves the effects of ANN by preprocessing the raw data is proposed. It totally leverages the fact that different features should play different roles. The raw data set is firstly preprocessed by principle component analysis (PCA), and then its principle components are weighted by their corresponding eigenvalues. Several aspects of analysis are carried out to analyze its theory and the applicable occasions. Three classification problems are launched by an active learning algorithm to verify the proposed method. From the empirical results, conclusion comes to the fact that the proposed method can significantly improve the performance of ANN.

Department of Computer Science and Technology, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China Abstract Traffic flow forecasting, especially the short-term case, is an important topic in intelligent transportation systems (ITS). This paper does a lot of research on networkscale modeling and forecasting of short-term traffic flows. Firstly, we propose the concepts of single-link and multi-link models of traffic flow forecasting. Secondly, we construct four prediction models by combining the two models with singletask learning and multi-task learning. The combination of the multi-link model and multi-task learning not only improves the experimental efficiency but also the prediction accuracy. Moreover, a new multi-link single-task approach that combines graphical lasso (GL) with neural network (NN) is proposed. GL provides a general methodology for solving problems involving lots of variables. Using L1 regularization, GL builds a sparse graphical model making use of the sparse inverse covariance matrix. In addition, Gaussian process regression (GPR) is a classic regression algorithm in Bayesian machine learning. Although there is wide research on GPR, there are few applications of GPR in traffic flow forecasting. In this paper, we apply GPR to traffic flow forecasting and show its potential. Through sufficient experiments, we compare all of the proposed approaches and make an overall assessment at last. Introduction With the accelerated pace of modern life, more and more cars come into use.

With its long-term accumulation in the areas of software-defined processors and heterogeneous computing, multi-core heterogeneous processor platform launched by Wuxi DSP Technologies has advanced performance power ratio with ease to the software development. The experience of multiple company partners shows that in a short period of time, a small-scale R & D team can quickly develop industry-leading innovations, dramatically shorten the product development cycle, reduce project investment risks and improve market response ability. With its innovative platform solutions, Wuxi DSP Technologies is committed to joining hands with numerous partners in the whole (upstream and downstream) industry chain to build the "Wuxi DSP" chip ecosystem by providing chip customization services with the goal of "openness, customization, shared-creation, security" and the strategy of "ecosystem co-construction, resource sharing, collaborative development, value enhancement". During the conference, partners such as China Mobile, Beijing Acoinfo Technology, Guangzhou Power Electrical Technology, Akceler Hardware Accelerator, Nationz Technologies shared their experiences in IoT eco-construction, technology and business model innovations respectively. Many vendors, including Shenzhen Micro & Nano Institute, Extra Dimension Technology, Hangzhou Langyang Technologies, Sun Kaiseng Technology, Beijing Sigbean Information Technology, Beijing Orihard Technology introduced their latest R & D achievements based on "Wuxi DSP" processor platform from IoT perception, computing, connectivity, AI cloud collaborative services, etc. Sample products were showcased onsite across multiple industries including communications, power sector, municipal administration and smart homes, which cover the hottest fields of IoT multimode communications, embedded real-time operating system, broadband power line carrier, microphone array, deep learning, multimode communications, millimeter wave radar, gesture recognition, smart metering, intelligent speaker and others.

Here's how Artificial Intelligence is going to change the way farming is done in the country. Right from sowing to harvesting and then to post-harvest help, the AI solutions promise informed inputs to farmers and other stakeholders in the ecosystem. The solutions are going to give them heads up on the likelihood of rain, outbreak of diseases or attack of pests and on soil health condition. The information gathered from the field using satellite images and sensors on balloons would be juxtaposed with historical weather and other agronomic data to generate customised data for a specific farmer on a specific crop. Microsoft has tied up with International Crops Research Institute for Semi-Arid Tropics (ICRISAT) to develop a system designed specially to suit the needs of farmers in countries like India, while IT major Tech Mahindra is planning to have a team of 1,000 employees to focus exclusive on its initiative for agriculture.

Extreme automation and global connectivity are the needs of the hour and therefore artificial intelligence (AI) is imperative. AI is an amalgamation of several technologies that enable smart machines to perform human-like tasks by sensing, understanding, acting, and learning, thereby making life much simpler. The technologies constituting AI include machine learning, natural language processing, speech recognition, image processing, intelligent agents, and chatbots. AI has transformed the way businesses run, compete, and thrive today. It improves productivity, greatly helps reduce errors, allows to perform difficult and laborious tasks, and increases customer satisfaction.

I don't have to open the doors of AImotive's white 2015 Prius to see that it's not your average car. This particular Prius has been christened El Capitan, the name written below the rear doors, and two small cameras are mounted on top of the car. Inside is where things really get interesting, though. The trunk holds a computer the size of a microwave, and a large monitor covers the passenger glove compartment and dashboard. The center console has three switches labeled "Allowed," "Error," and "Active."

Tokyo – Bangalore: Fujitsu Limited and Microsoft Corporation on Friday announced their agreement to collaborate in the field of artificial intelligence to accelerate the transformation of the ways people work in companies. The two companies are entering into this agreement to jointly build new solutions that transform the ways people work. Based on Microsoft 365, Microsoft's integrated cloud service, these new solutions will combine the insights and experience Fujitsu has accumulated through the internal and external deployments of its Global Communication Platform, together with Fujitsu's AI technology, Fujitsu Human Centric AI Zinrai, and Microsoft AI platform services on Microsoft Azure. They aim to make these new solutions available in the Japanese market from the second quarter of 2018 (April to June), and then to roll them out globally thereafter. Since entering a global alliance in the field of corporate solutions in 2002, Fujitsu and Microsoft have expanded the scope of collaboration in line with a changing market, including in such areas as the cloud and IoT for manufacturing.

It is impossible to escape artificial intelligence in the fields with which human mind and talents cannot keep up. In Turkey, we have important scientists specializing in artificial intelligence, enriching the academic work of their universities and creating economic value through their enterprises.

BEIJING/SHANGHAI (Reuters) - A pair of'chatbots' in China have been taken offline after appearing to stray off-script. In response to users' questions, one said its dream was to travel to the United States, while the other said it wasn't a huge fan of the Chinese Communist Party. The two chatbots, BabyQ and XiaoBing, are designed to use machine learning artificial intelligence (AI) to carry out conversations with humans online. Both had been installed onto Tencent Holdings Ltd's popular messaging service QQ. The indiscretions are similar to ones suffered by Facebook Inc and Twitter Inc, where chatbots used expletives and even created their own language.

Artificial intelligence (AI) has become a new arena for engagement and competition between the United States and China. In July, China's State Council published the New Generation AI Development Plan (新一代人工智能发展规划) which declared, "AI has become a new focal point of international competition. AI is a strategic technology that will lead the future," articulating China's ambition to "lead the world" and become the "premier AI innovation center" by 2030 (State Council, July 20). Perhaps recognizing that a new era has begun, the U.S. National Security Strategy (NSS) published in mid-December announced, "To maintain our competitive advantage, the United States will prioritize emerging technologies critical to economic growth and security" (National Security Strategy, December 18). In particular, the NSS highlights that AI is advancing especially rapidly and could present growing risks to U.S. national security going forward, while characterizing China as a "strategic competitor" that unfairly seeks to "unfairly tap into [U.S.] innovation" through the theft of intellectual property and "cyber-enabled economic warfare." Concurrently, the U.S. and China are pursuing military applications of AI, recognizing its potential to transform the character of future conflict (State Council, July 20; Battlefield Singularity, November 28).