Japan's state-backed chip venture Rapidus began test production of next-generation chips on Tuesday, an early but key step in the country's efforts to make its own artificial intelligence components. The 2-year-old company is gearing up to mass produce semiconductors using 2-nanometer processes in 2027, which on paper would match Taiwan Semiconductor Manufacturing Co. in terms of chipmaking prowess. Japan has to date earmarked 1.72 trillion ( 11.5 billion) to support the startup, part of a yearslong push to regain some of the tech leadership it's ceded to the U.S., Taiwan and South Korea. "It was extraordinarily difficult to develop 2 nm technology and the knowhow for mass production," and more experimentation lies ahead, Chief Executive Officer Atsuyoshi Koike, who is 72, said at a news conference. "We will take things step by step to lower error rates and secure customer trust."

The Tokyo Metropolitan Government will begin using the artificial intelligence chatbot ChatGPT for writing texts and carrying out other clerical work in all of its offices from August, Gov. Yuriko Koike said Tuesday. ChatGPT "has the potential to greatly transform the way public administration is conducted," Koike said during a metropolitan assembly session. She added that "better city governance" can be achieved by assessing the positive and negative aspects of the AI service. Koike also said the metropolitan government will use ChatGPT for tasks including preparing documents in question-and-answer format, and seek input from its employees about other practical uses for the generative AI tool. This could be due to a conflict with your ad-blocking or security software.

Researchers at Kyoto University and Nagoya University in Japan have recently devised a new, automatic approach for designing robots that could simultaneously improve their shape, structure, movements, and controller components. This approach, presented in a paper published in Artificial Life and Robotics, draws inspiration from the evolution of vertebrates, the broad category of animals that possess a backbone or spinal column, which includes mammals, reptiles, birds, amphibians, and fishes. "The automatic robot design is a completely novel research project for the Matsuno Lab, the laboratory led by Fumitoshi Matsuno, and this is the first paper published for this project," Ryosuke Koike, one of the researchers who carried out the study, told TechXplore. "Its primary objective was to design a good-performing robot for a given task. Since there are innumerable possible combinations of robot morphologies and controllers, it is impossible to reach the best robot by manual human exploration. Therefore, we realized that it is necessary to establish a method for automatically designing robots using computers."

Most of modern medicine has physical tests or objective techniques to define much of what ails us. Yet, there is currently no blood or genetic test, or impartial procedure that can definitively diagnose a mental illness, and certainly none to distinguish between different psychiatric disorders with similar symptoms. Experts at the University of Tokyo are combining machine learning with brain imaging tools to redefine the standard for diagnosing mental illnesses. We only meet patients in the hospital or clinic, not out in their daily lives. We have to make medical conclusions using subjective, secondhand information," explained Dr. Shinsuke Koike, M.D., Ph.D., an associate professor at the University of Tokyo and a senior author of the study recently published in Translational Psychiatry. "Frankly, we need objective measures," said Koike.

The Tokyo Metropolitan Government on Friday unveiled robots that will be used in two hotels housing those infected with the novel coronavirus. The metropolitan government aims to efficiently clean the hotels, which are to house asymptomatic patients or those with light symptoms, and lower the burden on staff members. The robots were unveiled at the Apa Hotel & Resort in the capital's Sumida Ward, and Tokyo Gov. Yuriko Koike came to inspect them. One cylindrical robot is programed to hand lunch boxes to patients and clean the hotel lobby. Another robot, a humanoid, is designed to interact with patients.

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.

Recently I read an interesting article on Google's Cloud Platform blog about a Japanese cucumber farmer who built a home brew automated system for sorting cucumbers using an Arduino, a Raspberry Pi, and Google's machine learning technology. There's a short video that shows the system in action. The cucumbers are photographed in three different ways using cameras controlled by the Raspberry Pi. The images are sent to the Google Cloud, where they are analyzed for characteristics such as shape, size, and thickness. Based upon the results of the analytics, the cucumber can be classified into one of nine different categories.

AI/ML is not just for the FANG companies (Facebook, Amazon, Netscape, and Google) but is beginning to be a substantial part of new products in unexpected categories, and is helping established business innovate. But even today, it is impacting how we manage teams and projects, enabling teams to be more efficient and creative. A great example (here today) is using Natural Speech Processing to create meeting minutes automatically the second a meeting is over. Soon we will see "agents" that excerpt action items, and "bots" that follow up (here soon). Unfortunately, this new wave of technology is surrounded by a great deal of hype.

Not much about Makoto Koike's adult life suggests that he would be a farmer. Trained as an engineer, he spent most of his career in a busy urban section of Aichi Prefecture, Japan, near the headquarters of the Toyota Motor Corporation, writing software to control cars. Koike's longtime hobby is tinkering with electronic kits and machines; he is not naturally an outdoorsy type. Yet, in 2014, at the age of thirty-three, he left his job and city life to move to his parents' cucumber farm, in the greener prefecture of Shizuoka. "I thought I was getting old," Koike told me.

Two cucumber farmers in Japan have received an unusual boost to their business after their son adapted Google's powerful artificial intelligence software to carry out the arduous task of sorting vegetables. Makoto Koike returned to his parent's cucumber farm in 2015 after working as a computer systems designer in the automobile industry. While helping out on the farm, Koike realized that one of the most time-consuming processes could be overcome through automation. Taking inspiration from Google's powerful artificial intelligence computer program AlphaGo, Koike set about designing a sorting system using a $35 Raspberry Pi 3 computer and Google's open source deep-learning platform TensorFlow. "Each cucumber has different color, shape, quality and freshness," Koike said.