TOKYO (Reuters) - Toyota Motor Corp has designs on making robot helpers for your home, and has enlisted a Japanese startup that specializes in artificial intelligence to jump-start its plan. Japan's biggest automaker and Tokyo-based Preferred Networks Inc will carry out joint research to develop so-called service robots that are "capable of learning in typical living environments", the companies said in statements on Wednesday. The two firms have already been collaborating on driverless vehicles since 2014. Eighty-year-old manufacturing giant Toyota is trying to transform itself and adapt to technology, such as ride-hailing and automated driving, that is disrupting the auto industry. Toyota sees robots as part of that effort, particularly in Japan, where it aims to have them in homes and hospitals to support one of the world's fastest ageing populations.
Toyota is enlisting the help of startup Preferred Networks, a Japanese company founded in 2014 with a focus on artificial intelligence and deep learning, to help move forward its goal of developing useful service robots that can assist people in everyday life. The two companies announced a partnership today to collaborate on research and development that will use Toyota's Human Support Robot (HSR) robotics platform. The platform, which Toyota originally created in 2012 and has been developing since, is a basic robot designed to be able to work alongside people in everyday settings. Its primary uses involve offering basic car and support assistance in nursing and long-term care applications. Equipped with one arm, a display, cameras and a wheeled base, it can collect and retrieve items, and provide remote control and communication capabilities.
Natural language understanding(NLU) is one of the richest areas in deep learning which includes highly diverse tasks such as reaching comprehension, question-answering or machine translation. Traditionally, NLU models focus on solving only of those tasks and are useless when applied to other NLU-domains. Also, NLU models have mostly evolved as supervised learning architectures that require expensive training exercises. Recently, researchers from OpenAI challenged both assumptions in a paper that introduces a single unsupervised NLU model that is able to achieve state-of-the-art performance in many NLU tasks. The idea of using unsupervised learning for different NLU tasks has been gaining traction in the last few months.
TOKYO (Reuters) - Miniature remote controlled cars have proved to be a crowd pleaser at track and field throwing events, but for the Tokyo 2020 Olympics Toyota Motor Corp is upping the game with a hi-tech way to fetch javelins and hammers: pint-sized, self-driving A.I. robot cars. The Japanese automaker on Monday unveiled a prototype of its next-generation field support robot, a miniature shuttle bus-shaped contraption based on its "e-Palette" ride-sharing vehicle under development, to be used at the Tokyo Games. The vehicle, roughly the size of a toddler's ride-on toy car, can travel at a maximum speed of 20 kilometers per hour and sports three cameras and one lidar sensor which enable it to "see" its surroundings. Draped around the top of its body is a band of LED lights which illuminate when the vehicle uses artificial intelligence to follow event officials toward the equipment hurled by athletes onto the pitch during shot put, discus throw, hammer throw and javelin events. After the equipment, which can weigh as much as eight kilograms for hammers, is loaded into the vehicle by the official, a press of a button located toward its front sends the car zipping back to athletes for later use.
In partnership with British Triathlon, we have created the'Athlete Genome'; a technology solution aimed at enhancing athletic performance, with the ambition to ensure British Triathletes are the best prepared athletes at the Olympic and Paralympic Games in Tokyo. The Athlete Genome is an industry-first, developed through the application of Accenture thinking and leading-edge technologies and in partnership with British Triathlon. The solution, a platform which integrates performance data with psychological data in sport, creates a hyper-personalised view of the impact of cognitive state on performance, and gives British Triathlon's athletes and coaches the ability to make meaningful decisions based on this interaction. Working alongside British Triathlon and the world-leading English Institute of Sport, we are developing and validating the use of sentiment analysis in elite performance sport. By integrating technologies including artificial intelligence, machine learning, the cloud, wearables and cognitive and performance data from TrainingPeaks, the Athlete Genome seeks to understand the relationship between cognitive state and performance.
When thousands of people converge in Tokyo for the 2020 Olympic and Paralympic Games, the city's infrastructure will be tested. Toyota is getting into the mix to handle some of the ways people will get around the city and the Olympics venue. Toyota unveiled Thursday a new product called APM or Accessible People Mover that is designed for the Olympics and Paralympic Games. The aim, according to Toyota, is for this vehicle to provide "mobility for all" and to solve the so-called "last mile" problem. In Toyota's view, that means a vehicle that can transport as many people as possible, including elderly, pregnant women, families with young children and people with disabilities.
The formalism of anchor words has enabled the development of fast topic modeling algorithms with provable guarantees. In this paper, we introduce a protocol that allows users to interact with anchor words to build customized and interpretable topic models. Experimental evidence validating the usefulness of our approach is also presented.
There is a simple riposte to anyone who doubts an Olympics can truly transform a city: Tokyo. When Japan's capital first won the right to host the Games, in 1959, it suffered from a desperate shortage of housing and functional infrastructure – and the lack of flush toilets meant most waste had to be vacuumed daily out of cesspits underneath buildings by "honey wagon" trucks. But within five years Japan's capital had undergone such a metamorphosis that visitors to the 1964 Olympics responded with stunned awe. "Out of the jungle of concrete mixers, mud and timber that has been Tokyo for years, the city has emerged, as from a chrysalis, to stand glitteringly ready for the Olympics," the Times' correspondent swooned, citing a long list of buildings and accomplishments "all blurring into a neon haze … that will convince the new arrival he has come upon a mirage." As Japan's capital enters a year in the spotlight, from the Rugby World up to the 2020 Olympics, Guardian Cities is spending a week reporting live from the largest megacity on Earth.
A defence company has invented a new futuristic'rifle' that stops rogue drones by hacking into them - and forcing them to fly back to their pilots. DroneShield has developed a software similar to'Google Maps' for drones that instantly locates any drones - and sends them back to their pilots. The firm has previously worked with the British Army and provided assistance to the 2018 Korean Winter Olympics, and their tech is in use at airports. CEO Oleg Vornik remains tight-lipped on the exact cost of the system, but confirmed it ranges from five to seven figures. Mr Vornik also says the system could be used to protect airports from drone incursions - such as the one that brought chaos to Gatwick Airport, bringing it to a standstill for 33 hours before Christmas.
NEC Corp. gave a demonstration of its facial recognition system at its headquarters in Tokyo on Friday that it says will help passengers board planes faster without having to present passports or boarding passes. Narita will be the first airport in the country to deploy the system, called OneID, ahead of an expected spike in foreign arrivals for the 2020 Tokyo Olympic and Paralympic Games. In the media presentation, NEC showed how the system streamlined the boarding procedure. First, at the self check-in machine, passenger consent was obtained, then their passport was scanned and a barcode on their smartphone screen provided the flight details. A camera was used to capture their facial image during the process.