Keio University President Kohei Ito (left) and OpenAI Chief Strategy Officer Jason Kwon sign a memorandum of understanding on Tuesday in Tokyo. Keio University is working with OpenAI to integrate artificial intelligence into its education system. Keio University President Kohei Ito and OpenAI Chief Strategy Officer Jason Kwon signed a memorandum of understanding Tuesday, making Keio the first Japanese university to form a strategic partnership with the producer of ChatGPT. "We will develop an environment where students and researchers can proactively learn and utilize AI," Ito said. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

A member of the Ukrainian State Emergency Service attends a transfer ceremony of special vehicles from Japan to Ukraine in Kyiv in November 2023. With Russia making incremental territorial gains in Ukraine, Kyiv is urging Tokyo to boost its support in areas such as cybersecurity, demining and counterdrone systems, transforming what started as ad hoc, nonlethal assistance into a long-term security partnership. "Ukraine has identified several priority areas," Ukrainian Deputy Defense Minister Serhiy Boev told The Japan Times in an exclusive interview. These include counterdrone systems that can be integrated with the country's air-defense network, logistics and maintenance support for nonlethal equipment, as well as surveillance and reconnaissance capabilities to enhance maritime domain awareness, particularly in the Black Sea. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Unlike conventional keyword-based search tools, the AI service for searching through disclosure materials allows for prompts such as companies whose dividend predictions rose at least 20%. Japan Exchange Group, the operator of the Tokyo Stock Exchange (TSE), on Tuesday launched a service enabling users to search corporate disclosure materials using artificial intelligence. The J-Lens service, whose prototype version was released by JPX Market Innovation & Research, a unit of Japan Exchange, or JPX, is aimed at improving investor convenience by enhancing search functions for the massive volume of disclosure documents. Around 150,000 such documents are filed each year. Unlike conventional keyword-based search tools, J-Lens allows for prompts such as companies whose dividend predictions rose at least 20%.

A damaged concrete pillar supporting the Hachinohe Line in the city of Hachinohe, Aomori Prefecture, on Wednesday. False claims that a powerful earthquake in northern Japan was "human-caused," along with artificial intelligence-generated videos, are spreading rapidly across social media after the quake struck Aomori Prefecture on Monday evening. The earthquake registered an upper 6 on Japan's seismic intensity scale, prompting warnings from the Japan Meteorological Agency (JMA) and the Cabinet Secretariat against the spread of unverified information that could hamper emergency response efforts. Misinformation circulated widely on platforms including X, echoing a pattern seen during previous disasters such as the Noto Peninsula earthquake in January 2024, when false rescue pleas and conspiracy theories also gained traction online. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Until now, Tokyo police had identified suspicious posts on social media platforms by manually searching for them using keywords. Tokyo's Metropolitan Police Department has introduced an artificial intelligence tool that automatically gathers and analyzes social media posts that appear to offer dark part-time jobs, it announced Tuesday. For example, if a post on X is deemed to be an offer for shady jobs, police post a reply warning users the message in question may contain inappropriate content soliciting people who are prepared to do illicit part-time jobs. The number of such warning posts made between August and November this year came to around 18,500, more than double the roughly 8,800 replies made in the entire year of 2024. Until now, Tokyo police had identified suspicious posts by manually searching for such messages using keywords.

Sam Altman's appearance on is part of a larger charm offensive currently being waged by the tech establishment. OpenAI CEO Sam Altman was at the center of Silicon Valley's most visible publicity push in recent memory Monday night when he appeared on . In a predictably softball interview with host Jimmy Fallon, Altman explained how ChatGPT has helped him alleviate the anxiety that comes with being a new parent. It was a distinctly clever, if somewhat surprising, choice from Altman who has mostly kept his personal life out of the media spotlight. But Altman is a salesman, and a good salesman understands the optics of good television.

Nvidia CEO Jensen Huang speaks alongside U.S. President Donald Trump at the White House in Washington on April 30. U.S. President Donald Trump decided to let Nvidia sell its H200 artificial intelligence chips to China after concluding the move carried a lower security risk because the company's Chinese archrival, Huawei Technologies, already offers AI systems with comparable performance, according to a person familiar with the deliberations. Administration officials who weighed whether to clear Nvidia's H200 had considered multiple possible scenarios, factoring in the views of national security hawks in Washington, said the person. Options ranged from exporting zero AI chips to China to allowing exports of everything to flood the Chinese market and overwhelm Huawei. Ultimately the policy backed by Trump called for clearing H200s to China while holding back the latest Nvidia chips for American customers, the person said.

The Best Razor I've Ever Used Is on Sale Henson Razors are engineered to give a spectacular shave with dirt-cheap generic blades. Razors are one of the most heavily and competitively marketed products in American capitalism. Made with steel and plastic that costs a few pennies, but sold for a thousand percent profit, the razor market is the subject of vigorous academic study and debate. The founder of Gillette famously came up with a model of basically giving away the razor handle so he could sell the blades. Canadian startup Henson has the opposite model, charging $79 for a razor that can give you an excellent shave with dirt-cheap disposable blades that cost about 15 cents each .

A large amount of work has been done in Multi-Agent Systems (MAS) for modeling and solving problems with multiple interacting agents. However, most LLMs are pretrained independently and not specifically optimized for coordination. For example, existing LLM fine-tuning frameworks rely on individual rewards, which require complex reward designs for each agent to encourage collaboration. To address this challenge, we model LLM collaboration as a cooperative Multi-Agent Reinforcement Learning (MARL) problem. We develop a multi-agent, multi-turn algorithm, Multi-Agent Group Relative Policy Optimization (MAGRPO), to solve it, building on current RL approaches for LLMs as well as MARL techniques. Our experiments on LLM writing and coding collaboration demonstrate that fine-tuning multiple LLMs with MAGRPO enables agents to generate high-quality responses efficiently through effective cooperation. Our approach opens the door to using MARL methods for LLM collaboration and highlights the associated challenges.

Implicit Neural Representations (INRs) leverage neural networks to map coordinates to corresponding signals, enabling continuous and compact representations. This paradigm has driven significant advances in various vision tasks. However, existing INRs lack frequency selectivity and spatial localization, leading to an over-reliance on redundant signal components. Consequently, they exhibit spectral bias, tending to learn low-frequency components early while struggling to capture fine high-frequency details. To address these issues, we propose FLAIR (Frequency- and Locality-Aware Implicit Neural Representations), which incorporates two key innovations. The first is Band-Localized Activation (BLA), a novel activation designed for joint frequency selection and spatial localization under the constraints of the time-frequency uncertainty principle (TFUP). Through structured frequency control and spatially localized responses, BLA effectively mitigates spectral bias and enhances training stability. The second is Wavelet-Energy-Guided Encoding (WEGE), which leverages the discrete wavelet transform to compute energy scores and explicitly guide frequency information to the network, enabling precise frequency selection and adaptive band control. Our method consistently outperforms existing INRs in 2D image representation, as well as 3D shape reconstruction and novel view synthesis.