Kyocera Corp. has started developing a device to check human health and immunity from the odor of one's stool, aiming to put it into practical use in three years. In collaboration with AuB Inc., a Tokyo-based startup, Kyocera will analyze data from the device, which will be installed in toilet seats. The Kyoto-based electronics giant will create a system that infers the intestinal environment of the user with the aid of artificial intelligence technology and data collected by AuB, according to Kyocera officials. Kyocera will deliver the results to clients through a smartphone application and propose measures to improve diet and other elements of their lives to improve health, the officials said. As part of the development process, AuB will gather stool samples from 29 players of a youth team belonging to Kyoto Sanga F.C., a professional soccer team.
Hong Kong/Beijing/Seoul/Tokyo – Fitness-tracking gadgets are selling out, home exercise classes have never been more popular and robotics crews are pivoting to making sanitation robots. The Covid-19 pandemic has triggered a seismic wave of health awareness and anxiety, which is energizing a new category of virus-fighting tech. The fear of infection has accelerated the adoption of apps and wearables as a means to feel better protected. "Having accurate and immediate feedback about our body temperature, blood pressure and other health signals helps to restore people's sense of control," said Andy Yap, a social psychologist at the INSEAD business school. Consumers, insurers and health-care providers are all seeing the benefit of the gadgets, in a shift expected to persist long after the outbreak subsides.
Researchers from Tokyo Metropolitan University have used machine learning to analyze spin models, which are used in physics to study phase transitions. Previous work showed that an image/handwriting classification model could be applied to distinguish states in the simplest models. The team showed the approach is applicable to more complex models and found that an AI trained on one model and applied to another could reveal key similarities between distinct phases in different systems. Machine learning and artificial intelligence (AI) are revolutionizing how we live, work, play, and drive. Self-driving cars, the algorithm that beat a Go grandmaster and advances in finance are just the tip of the iceberg of a wide range of applications now having a significant impact on society.
Human-assisted artificial intelligence platform Engineer.ai The startup with global presence including offices in Los Angeles, London, Delhi NCR, Mumbai, and Tokyo will use the capital to go deeper in engineering operations and drive customer acquisition. Besides, the Sachin Dev Duggal led company is also planning to expand its operations in the Asia Pacific region, especially India, South East Asia including China. Touted as the low code no code AI platform, Engineer.ai'Builder'
Engineer.ai, which uses Artificial Intelligence to help small and mid-sized organisations build their own bespoke software (custom or tailor-made software), has raised a Series A investment of $29.5 Mn, led by Lakestar and Jungle Ventures. The funding round also saw participation from DeepCore -- Softbank's AI-focussed investment fund. Founded by Sachin Dev Duggal and Saurabh Dhoot in 2012, Engineer.ai is a global company with split headquarters in Los Angeles and London, supported by offices in Delhi and Tokyo. The startup was formerly known as SD Squared and was rebranded to Engineer.ai. in June 2018. With over $24M in gross revenue and customers that include BBC, Virgin Group and the San Francisco Giants, Engineer.ai
A Tokyo-based risk management firm is cautioning against a potential surge in coronavirus-related disinformation on April Fools' Day, alarmed by the recent spread of what it perceives to be baseless rumors on social media that the government is secretly preparing for the start of a Tokyo lockdown that day. Unsubstantiated rumors pertaining to COVID-19 have been swirling online for months, but gossip with a more urgent tone and more fear-mongering in nature has emerged in recent days, making digital literacy against false rumors more important than ever, according to Tokyo-based Spectee Inc. The firm says it uses cutting-edge artificial intelligence to monitor, collect and analyze the deluge of online information. "Previously, the most common types of coronavirus-related misinformation and disinformation we would see were primarily medical and health-related, as in, 'granite has the power to kill the virus,' or'drinking lukewarm water is effective against the virus,'" said Kenjiro Murakami, head of Spectee. But as the number of COVID-19 cases has risen and the prospect of a citywide lockdown -- floated by Tokyo Gov. Yuriko Koike as a possibility -- loomed large over Japan last week, Murakami said the firm detected a rise in rumors over the weekend that go far beyond misguided health tips.
Episode 80: The featured guests are Machine Learning Tokyo (MLT) members Suzana Ilić (co-founder), Dimitris Katsios, and Asir Saeed. MLT is a Tokyo-based nonprofit organization dedicated to democratizing Machine Learning (ML). They are a team of engineers and researchers--now with a community of 5,000 people--and the winner of the Rakuten Technology & Innovation Silver Award 2019.
Good gamers can tune out distractions and unimportant on-screen information and focus their attention on avoiding obstacles and overtaking others in virtual racing games like Mario Kart. However, can machines behave similarly in such vision-based tasks? A possible solution is designing agents that encode and process abstract concepts, and research in this area has focused on learning all abstract information from visual inputs. This however is compute intensive and can even degrade model performance. Now, researchers from Google Brain Tokyo and Google Japan have proposed a novel approach that helps guide reinforcement learning (RL) agents to what's important in vision-based tasks.
IMAGE: Simulated low temperature (left) and high temperature (right) phase of a 2D Ising model, where blue points are spins pointing up, and the red points are spins pointing down. Tokyo, Japan - Researchers from Tokyo Metropolitan University have used machine learning to study spin models, used in physics to study phase transitions. Previous work showed that image/handwriting classifying AI could be applied to distinguish states in the simplest models. The team showed the approach is applicable to more complex models and found that an AI trained on one model and applied to another could reveal key similarities between distinct phases in different systems. Machine learning and artificial intelligence (AI) are revolutionizing how we live, work, play, and drive.
Toyota Motor Corp. and Nippon Telegraph and Telephone Corp., Japan's auto and telecommunications giants, formed a capital tie-up Tuesday to build energy-efficient "smart cities" where autonomous vehicles transport residents. The two firms, which have been developing "connected cars" equipped with advanced telecommunication systems since 2017, deepened their partnership into mutual shareholdings, with each investing around 200 billion yen ($1.8 billion) by purchasing each other's treasury stocks. Toyota said it will start the smart city project at a 175-acre site at the foot of Mt. Toyota has said only fully autonomous, zero-emission vehicles are allowed to travel on main streets in the envisioned smart city where around 2,000 residents have in-home robotics to assist their daily lives. NTT also said it will launch an internet-led smart city project at an NTT-related block in Shinagawa area in Tokyo's Minato Ward.