Sharp Corp. on Monday released three new models of its RoBoHon humanoid robot with a wider range of use for families and corporate clients. The new lineup -- two walking models and one that remains seated -- focuses more on family users with small children, who can experience "life with robots," the company said during an event in Tokyo. The number of apps that can be loaded on the robots will gradually increase to 46 from the current 30, the company said. These include an app that sends an image taken by the robot of a family member returning home to a user's email address. Users can try real-time monitoring of their homes through the app for an extra monthly charge of ¥300 plus tax.

It was one of the most infamous companies in Japan, rocking the nation with a corporate scandal that ousted a prime minister and then nearly collapsing under a mountain of debt. Now, Recruit Holdings Co. is back, reinvented by a group of employees who quietly turned the magazine publisher and job placement firm into an internet giant that touches the lives of almost every consumer in the world's third-biggest economy. If Recruit were a U.S. company, it would be like having LinkedIn, Zillow, Yelp, eHarmony, Booking.com, "We are there, every time people choose to do things," said Masumi Minegishi, Recruit's 55-year-old chief executive officer. As the biggest internet companies compete for world domination with apps that track consumers and use artificial intelligence to crunch data and provide tailored services, Recruit is Japan's leading contender.

UAE-based automotive company W Motors' has announced the unveiling of MUSE at Auto Shanghai 2019 on April 16. The fully-electric MUSE features a Level 4 / Level 5 autonomous driving system, innovative user interfaces and cloud-computed connectivity, as well as several interior configurations catering to different business needs and consumer requirements. It will be fully produced in Dubai, UAE by W Motors at the all-new production facility of which the first phase is set to be completed in the last quarter of 2019. Pioneers of the future of driving, W Motors is the first and only automotive developer in the Middle East - in partnership with sister company ICONIQ Motors - to release a self-driving vehicle, designed to be on the road for EXPO 2020 in Dubai. MUSE was developed by W Motors and ICONIQ Motors in collaboration with international partners AKKA Technologies, Magna Steyr and Microsoft USA, each offering highly specialized and cutting-edge technologies in the realm of advanced autonomous driving solutions.

Will artificial intelligence make most people better off over the next decade, or will it redefine what free will means or what a human being is? A new report by the Pew Research Center has weighed in on the topic by conferring with some 979 experts, who have, in summary, predicted that networked AI "will amplify human effectiveness but also threaten human autonomy, agency and capabilities." When the experts were asked whether AI and related technology will by the year 2030 enhance human capacities or allow them to deteriorate, the majority (63 percent) said most people will be better off. The opportunities cited in "Artificial Intelligence and the Future of Humans" were far-ranging: "smart systems" built into cities, vehicles and buildings "will save time, money and lives," and AI-driven uses in healthcare will advance diagnosis and treatment of patients or help people who need daily aid to "live full and healthier lives." At the same time, as decision-making is turned over to "black box tools," people will sacrifice their "independence, privacy and power over choice" -- an outcome that will "deepen" as automation becomes "more prevalent and complex."

The government plans to use a facial recognition system at a ceremony later this month to mark the 30th anniversary of Emperor Akihito's accession to the throne, officials said. The use of facial recognition technology, a first for a government-sponsored event in Japan, is designed to reduce the time required for participant identification and help prevent terrorism. Using images of the faces of participants registered in advance, the system authenticates recognized faces in some 10 seconds per person with an accuracy rate of more than 99 percent, the officials said. More than 1,000 people are expected to attend the ceremony set to take place at Tokyo's National Theatre on Feb. 24. The facial recognition system will be used for hundreds of people including government officials and journalists.

Just visualize the situation, technology has improved right from inventing the wheel to the artificial intelligence of today. But yes, there has been a big gap in the adaptation of technology. Even in India and other developed countries, you can find a sizable chunk of the population not knowing the method to do digital transactions. As of now, artificial intelligence, cloud computing, and cryptocurrency have become the recent buzzwords in the finance industry. The scope of AI is very vast, ranging from automating machines to the very process of preparation of humanoid robots and their management.

President TrumpDonald John TrumpGillibrand backs federal classification of third gender: report Former Carter pollster, Bannon ally Patrick Caddell dies at 68 Heather Nauert withdraws her name from consideration for UN Ambassador job MORE issued an executive order this week directing federal agencies to support the development of artificial intelligence. It couldn't have come at a better time. That's because the U.S. is in a race against China to develop cutting-edge artificial intelligence technology, and it's a race we can't afford to lose. "Artificial Intelligence" (AI) may bring to mind any number of futuristic pop culture references, from "Star Wars" to "Westworld", and it may seem like something that's decades or even centuries away. The reality is that AI is already here – it's in the apps we use to navigate through traffic, it protects us from spam emails and more nefarious online security threats, and it's what responds when we say "OK Google..." and "Alexa?"

This week we speak to Alexander Rinke, co-founder of German technology company Celonis. When Alexander Rinke wanted some of the world's biggest companies to employ his small start-up business he came up with a novel approach - he would send their bosses handwritten letters. "We knew if we sent an email it could just be deleted," he says. "And if we sent out typed letters then their secretaries would open them, and bin them as junk mail. "But with a handwritten note, it seems more personal, it could have been a letter from a family member, or a friend." Alexander launched Celonis when he was 22 with two friends, Martin Klenk and Bastian Nominacher, in 2011 after they had finished maths and computer science degrees at the Technical University of Munich. Expanding on a project they had worked on as part of their courses, Celonis is a hi-tech data mining company that uses software and artificial intelligence to monitor the performance of businesses, to help them become more efficient and work better. In very simple terms, Celonis's software will monitor a company's computer system, and find out things such as which employees are being unproductive, which suppliers are too slow, and which production processes could be streamlined. The three friends were confident about what they could offer businesses, but they just needed to get themselves noticed. They worked like a treat, leading to meetings with some of the largest companies in Europe. Today, eight years later, Celonis's customers include BMW, Exxon-Mobile, General Motors, L'Oreal, Siemens, Uber and Vodafone. And after securing an additional $50m (£39m) of investment last year, Celonis says it is now valued at more than $1bn (£780m). Born and raised in Berlin, Alexander says he started his first company when he was just 15, supplying tutors to high school students. "It was great to get my first idea of how a business ran," he says. "But ultimately I knew it wouldn't last forever." Fast-forward to 2011 in Munich, and Alexander came up with the idea for Celonis when, as part of their studies, he, Martin and Bastian were helping a real world business improve its customer service. The three students found that the firm was taking about five days to come up with fixes to problems, and they thought there must be a quicker way. "We interviewed people in the company to try and understand why it took so long," says Alexander, who is now 29. "But we quickly realised that no-one was going to take the blame.

Artificial intelligence (AI) is changing the way we live our lives; it is everywhere and here to stay. The concepts of Artificial intelligence started on the pages of science fiction, which introduced us to the notion of smart robots. With the invention of electronic digital computers in the early 1940s the pursuit of AI was made possible. The term itself was coined at a conference at Dartmouth in the summer of 1956, where scientists gathered to discuss ways to program computers to solve problems with the skills of a human. AI flourished for the next two decades and optimism was high that we would soon have machines with the general intelligence of an average human.

The objective of this work is to study the applicability of various Machine Learning algorithms for prediction of some rock properties which geoscientists usually define due to special lab analysis. We demonstrate that these special properties can be predicted only basing on routine core analysis (RCA) data. To validate the approach core samples from the reservoir with soluble rock matrix components (salts) were tested within 100+ laboratory experiments. The challenge of the experiments was to characterize the rate of salts in cores and alteration of porosity and permeability after reservoir desalination due to drilling mud or water injection. For these three measured characteristics, we developed the relevant predictive models, which were based on the results of RCA and data on coring depth and top and bottom depths of productive horizons. To select the most accurate Machine Learning algorithm a comparative analysis has been performed. It was shown that different algorithms work better in different models. However, two hidden layers Neural network has demonstrated the best predictive ability and generalizability for all three rock characteristics jointly. The other algorithms, such as Support Vector Machine and Linear Regression, also worked well on the dataset, but in particular cases. Overall, the applied approach allows predicting the alteration of porosity and permeability during desalination in porous rocks and also evaluating salt concentration without direct measurements in a laboratory. This work also shows that developed approaches could be applied for prediction of other rock properties (residual brine and oil saturations, relative permeability, capillary pressure, and others), which laboratory measurements are time-consuming and expensive.