When Google founders Sergey Brin and Larry Page were still university researchers, they warned that advertising could undermine the trustworthiness of search engines.When Google founders Sergey Brin and Larry Page were still university researchers, they warned that advertising could undermine the trustworthiness of search engines.Machine learning & AI[#item_full_content]

Advertisers must disclose the use of AI-generated performers to consumers in California under a new law signed Wednesday by the state’s governor.Advertisers must disclose the use of AI-generated performers to consumers in California under a new law signed Wednesday by the state’s governor.Machine learning & AI[#item_full_content]

As concern rises over the risks of artificial intelligence, hopes for any kind of global approach depend on cooperation between the U.S. and China—superpowers that seem only to be more skeptical of each other’s AI strategy.As concern rises over the risks of artificial intelligence, hopes for any kind of global approach depend on cooperation between the U.S. and China—superpowers that seem only to be more skeptical of each other’s AI strategy.Machine learning & AI[#item_full_content]

Artificial Intelligence (AI) is rapidly advancing—and with it, the promise of solving some of academia’s toughest problems. But while many researchers focus on using AI to find answers, Associate Professor Hiroshi Kera of the Institute for Advanced Academic Research/Graduate School of Informatics is asking a different question: How can we design better problems for AI to solve?Artificial Intelligence (AI) is rapidly advancing—and with it, the promise of solving some of academia’s toughest problems. But while many researchers focus on using AI to find answers, Associate Professor Hiroshi Kera of the Institute for Advanced Academic Research/Graduate School of Informatics is asking a different question: How can we design better problems for AI to solve?Machine learning & AI[#item_full_content]

A research team led by Professor Daehee Park of the Department of Electrical Engineering and Computer Science at DGIST, in collaboration with a research team from KAIST, has developed a learning technique that enables a single compact AI model to simultaneously predict the movements of nearby people and plan safe navigation paths for robots while reducing performance degradation in both tasks. The research was presented at the 19th European Conference on Computer Vision (ECCV 2026) held in Malmö, Sweden, Sept. 8–12. The paper is available on the arXiv preprint server.A research team led by Professor Daehee Park of the Department of Electrical Engineering and Computer Science at DGIST, in collaboration with a research team from KAIST, has developed a learning technique that enables a single compact AI model to simultaneously predict the movements of nearby people and plan safe navigation paths for robots while reducing performance degradation in both tasks. The research was presented at the 19th European Conference on Computer Vision (ECCV 2026) held in Malmö, Sweden, Sept. 8–12. The paper is available on the arXiv preprint server.Robotics[#item_full_content]

A new approach could help make future AI chips smaller and more energy-efficient. A KAIST-led research team has used a single material to address one of the major obstacles facing atomically thin semiconductors: the difficulty of efficiently injecting charge. The technology could contribute to next-generation AI and low-power semiconductor devices in which multiple ultrathin layers are vertically integrated to increase device density and performance.A new approach could help make future AI chips smaller and more energy-efficient. A KAIST-led research team has used a single material to address one of the major obstacles facing atomically thin semiconductors: the difficulty of efficiently injecting charge. The technology could contribute to next-generation AI and low-power semiconductor devices in which multiple ultrathin layers are vertically integrated to increase device density and performance.Electronics & Semiconductors[#item_full_content]

A machine-learning system can identify fake, or spoofed, website addresses, according to research published in the International Journal of Electronic Security and Digital Forensics. The work offers a new tool to protect users against phishing attacks, in which attackers direct someone to a deceptive website to steal information such as bank logins or personal and private data.A machine-learning system can identify fake, or spoofed, website addresses, according to research published in the International Journal of Electronic Security and Digital Forensics. The work offers a new tool to protect users against phishing attacks, in which attackers direct someone to a deceptive website to steal information such as bank logins or personal and private data.Security[#item_full_content]

The Canadian computer scientist Yoshua Bengio, considered one of the founders of AI, told AFP that humanity is “losing control” of the technology and that the world needs guardrails similar to nuclear arms controls.The Canadian computer scientist Yoshua Bengio, considered one of the founders of AI, told AFP that humanity is “losing control” of the technology and that the world needs guardrails similar to nuclear arms controls.Machine learning & AI[#item_full_content]

Since 1665, scholarly journals have served as written records of scientific advancement—static words on a page, references written by people for other people to read. That’s about to change.Since 1665, scholarly journals have served as written records of scientific advancement—static words on a page, references written by people for other people to read. That’s about to change.Hi Tech & Innovation[#item_full_content]

Researchers at The University of Manchester, Shandong Jiaotong University and Harbin Engineering University have developed a machine learning framework that enables rapid predictions of how protected steel beams respond during a fire, offering engineers a faster way to assess fire safety performance in industrial structures.Researchers at The University of Manchester, Shandong Jiaotong University and Harbin Engineering University have developed a machine learning framework that enables rapid predictions of how protected steel beams respond during a fire, offering engineers a faster way to assess fire safety performance in industrial structures.Engineering[#item_full_content]