SAPPORO – The development of artificial intelligence software that can write haiku based just on images is underway, with researchers hoping the project will improve how technology understands human emotion. A team of researchers and software developers led by Hidenori Kawamura, a 44-year-old professor at Hokkaido University's graduate school, is aiming to create AI that can analyze a vast amount of poetry to generate a haiku written about a subject or scene. The AI has been learning masterpieces composed by renowned Japanese poets such as Kobayashi Issa (1763-1827) and Masaoka Shiki (1867-1902), and analyzing pictures picked by volunteers that correspond to the poems. According to the team, the AI checks whether it is following structural rules and is using appropriate seasonal references. Haiku are defined by the use of a set number of syllables and traditionally use words that describe the season in which the work is set.

Gait recognition technology, a method to identify people by characteristics shown unconsciously in the ways they walk, is being utilized in criminal investigations in Japan. The technology enables the identification of individuals even from images taken from a distance and low-resolution footage. According to advocates, a video image of only two strides is sufficient to identify a person with a high rate of accuracy, based on arm swings, length of stride and other characteristics. Researchers are working to improve the accuracy of the technology with the use of artificial intelligence. In a brazen daytime attack in Tokyo's upscale Ginza district in April 2017, a man was robbed of some ¥40 million on a street after he had converted gold into cash.

SINGAPORE: Crafted to resemble human-likeness with natural looking skin and hair, Nadine, described by its makers as a social humanoid, greets a person when he enters the room, makes eye contact and remembers his face. She smiles and listens intently as one speaks, cracking a joke occasionally. But when provoked, she gets upset too. Made in Singapore, the artificial intelligence robot, which was unveiled by the Nanyang Technological University's (NTU) Institute for Media Innovation in 2015, has made significant strides in the past three years, including the ability to recognise faces and remember conversations. Plans are underway for another public showcase next month, and researchers hope that before long, Nadine will be able to walk as well as identify and grasp objects with her hands.

In its ongoing effort to ensure quality food reaches passengers travelling on trains, the Indian Railways has equipped 16 of its base kitchens with high definition CCTVs to track anomalies, in real-time, during the cooking and packaging of meals. The camera feed is routed to an Artificial Intelligence module set up at IRCTC's headquarters in New Delhi. A member of the Railways Board visited IRCTC's first surveillance-oriented intelligence kitchen control room in New Delhi on Tuesday morning. M Jamshed, member (traffic), was given a tour of the central control, from where authorities can monitor kitchens. The move comes following a Comptroller and Auditor General audit report last July, which termed food served in railways "unsuitable" for human consumption.

Nokia has acquired SpaceTime Insight to expand its Internet of Things (IoT) portfolio and IoT analytics capabilities, and accelerate the development of new IoT applications for key vertical markets. Based in San Mateo, California, with offices in the U.S., Canada, U.K., India and Japan, SpaceTime Insight provides machine learning-powered analytics and IoT applications for some of the world's largest transportation, energy and utilities organizations, including Entergy, FedEx, NextEra Energy, Singapore Power and Union Pacific Railroad. Its machine learning models and other advanced analytics, designed specifically for asset-intensive industries, predict asset health with a high degree of accuracy and optimize related operations. As a result, SpaceTime Insight's applications help customers reduce cost and risk, increase operational efficiencies, reduce service outages and more. The acquisition supports Nokia's software strategy by bringing SpaceTime Insight's sales expertise and proven track record in IoT application development, machine learning and data science to the Nokia Software IoT product unit. It will strengthen Nokia's IoT software portfolio and IoT analytics capabilities, and accelerate the development of Nokia's IoT offerings to deliver high-value IoT applications and services to new and existing customers.

Facial recognition technology is likely to be among innovations on the agenda when bankers, financial regulators and officials from across Asia gather in Hong Kong on Wednesday for a landmark summit. The high-powered meeting comes as the race to regulate the fintech (financial technology) revolution is intensifying amid fears that a regulatory "vacuum" could be exploited by money launderers, fraudsters and underground bankers whose activities threaten national, regional and international financial stability. Organisers of the summit to launch the Alliance for Financial Stability with Information Technology, also known as AFS-IT, say speakers and guests will include top-level representation across the banking, financial, technology and regulatory sectors as well as government officials from China, Hong Kong, Macau, the Philippines, Thailand, Cambodia, Myanmar, Vietnam and Singapore. A key focus will be the fostering of innovation in regulation technology, or regtech, a new field in which information technology is used to enhance regulation. Innovative fintech can be used and adapted to benefit both service providers and regulators, and it includes know-your-customer facial recognition technology recently installed across the ATM network of casino hub Macau as part of an ongoing crackdown on money laundering and capital flight from China.

China is changing how we think of surveillance and facial recognition as a unique universal identifier. This is the kind of infrastructure China requires to build its nascent social credit system that will go live for all of China by 2020. Powerful facial recognition systems like the ones built by Shanghai-based start-up Yitu Technology, also promotes more security for China to police its huge population. YITU Tech integrates state-of-the-art AI technologies with industrial applications to build a safer, faster and healthier world. For those of you who remember the show Person of Interest, it's fond memories for going back to the future.

Today we are launching the 2018 edition of Cutting Edge Deep Learning for Coders, part 2 of fast.ai's Just as with our part 1 Practical Deep Learning for Coders, there are no pre-requisites beyond high school math and 1 year of coding experience--we teach you everything else you need along the way. This course contains all new material, including new state of the art results in NLP classification (up to 20% better than previously known approaches), and shows how to replicate recent record-breaking performance results on Imagenet and CIFAR10. The main libraries used are PyTorch and fastai (we explain why we use PyTorch and why we created the fastai library in this article). Each of the eight lessons includes a video that's around two hours long, an interactive Jupyter notebook, and a dedicated discussion thread on the fast.ai

Despite cultural and religious exclusions, pork is the most widely eaten meat in the world, accounting for 36% of all meat consumed. Asia is the biggest consumer; China alone accounts for one quarter of global pig trade, and its middle class is expected to double in the next 15 years, increasing even more the market for pork. While trade will certainly be a consideration among top producing countries, such as China itself, the US, Brazil, Spain and Russia, there are challenges for the industry that could be reduced, or even eliminated, with the implementation of digital and other data driven technologies. Processors focus on employee safety and welfare priorities even while trying to improve meat production efficiencies. For producers and farmers disease mitigation, animal health and performance are top of mind.

We consider big spatial data, which is typically produced in scientific areas such as geological or seismic interpretation. The spatial data can be produced by observation (e.g. using sensors or soil instrument) or numerical simulation programs and correspond to points that represent a 3D soil cube area. However, errors in signal processing and modeling create some uncertainty, and thus a lack of accuracy in identifying geological or seismic phenomenons. Such uncertainty must be carefully analyzed. To analyze uncertainty, the main solution is to compute a Probability Density Function (PDF) of each point in the spatial cube area. However, computing PDFs on big spatial data can be very time consuming (from several hours to even months on a parallel computer). In this paper, we propose a new solution to efficiently compute such PDFs in parallel using Spark, with three methods: data grouping, machine learning prediction and sampling. We evaluate our solution by extensive experiments on different computer clusters using big data ranging from hundreds of GB to several TB. The experimental results show that our solution scales up very well and can reduce the execution time by a factor of 33 (in the order of seconds or minutes) compared with a baseline method.