Anthropic, the company behind the generative AI tool Claude, claimed in March 2026 that it used an AI interviewer to conduct “the largest and most multilingual qualitative study” ever done. The AI tool collected responses from nearly 81,000 people about their visions for AI, spanning 70 languages and 159 countries. Anthropic contends that tools like this can enable researchers to conduct “rich, open-ended interviews at a very large scale.”Anthropic, the company behind the generative AI tool Claude, claimed in March 2026 that it used an AI interviewer to conduct “the largest and most multilingual qualitative study” ever done. The AI tool collected responses from nearly 81,000 people about their visions for AI, spanning 70 languages and 159 countries. Anthropic contends that tools like this can enable researchers to conduct “rich, open-ended interviews at a very large scale.”Machine learning & AI[#item_full_content]
South Korean researchers have successfully developed a core technology that can fundamentally resolve “memory shortages,” a chronic bottleneck in large-scale artificial intelligence (AI) training. This technology is a next-generation memory expansion technology based on Ethernet, which is expected to drive infrastructural innovation across the entire AI and big data industries in the future.South Korean researchers have successfully developed a core technology that can fundamentally resolve “memory shortages,” a chronic bottleneck in large-scale artificial intelligence (AI) training. This technology is a next-generation memory expansion technology based on Ethernet, which is expected to drive infrastructural innovation across the entire AI and big data industries in the future.Computer Sciences[#item_full_content]
South Korean researchers have successfully developed a core technology that can fundamentally resolve “memory shortages,” a chronic bottleneck in large-scale artificial intelligence (AI) training. This technology is a next-generation memory expansion technology based on Ethernet, which is expected to drive infrastructural innovation across the entire AI and big data industries in the future.South Korean researchers have successfully developed a core technology that can fundamentally resolve “memory shortages,” a chronic bottleneck in large-scale artificial intelligence (AI) training. This technology is a next-generation memory expansion technology based on Ethernet, which is expected to drive infrastructural innovation across the entire AI and big data industries in the future.[#item_full_content]
Drones are becoming increasingly common in densely populated urban centers, supporting applications ranging from parcel delivery to surveillance. However, their growing presence has introduced significant challenges related to safety, congestion, and coordination in low-altitude airspace.Drones are becoming increasingly common in densely populated urban centers, supporting applications ranging from parcel delivery to surveillance. However, their growing presence has introduced significant challenges related to safety, congestion, and coordination in low-altitude airspace.Automotive[#item_full_content]
Researchers at Carnegie Mellon University are investigating how humans respond to artificial intelligence agents that sound physically present in the same room, work that could shape the future of audio-only AI systems used in smart glasses, accessibility tools and other screen-free technologies.Researchers at Carnegie Mellon University are investigating how humans respond to artificial intelligence agents that sound physically present in the same room, work that could shape the future of audio-only AI systems used in smart glasses, accessibility tools and other screen-free technologies.Consumer & Gadgets[#item_full_content]
When you ask a large language model a question, the reply may include falsehoods, and if you challenge those statements with facts, the AI may still uphold the reply as true. That’s what my research group found when we asked five leading models to describe scenes in movies or novels that don’t actually exist.When you ask a large language model a question, the reply may include falsehoods, and if you challenge those statements with facts, the AI may still uphold the reply as true. That’s what my research group found when we asked five leading models to describe scenes in movies or novels that don’t actually exist.Machine learning & AI[#item_full_content]
Near misses like the one at New York’s John F. Kennedy International Airport inspired a group from the AirLab in Carnegie Mellon University’s Robotics Institute (RI) to create World2Rules, an AI system that learns interpretable safety rules from data to analyze, verify, and explain potential collision scenarios.Near misses like the one at New York’s John F. Kennedy International Airport inspired a group from the AirLab in Carnegie Mellon University’s Robotics Institute (RI) to create World2Rules, an AI system that learns interpretable safety rules from data to analyze, verify, and explain potential collision scenarios.Automotive[#item_full_content]
Deliberations begin Monday in the blockbuster trial pitting Elon Musk against AI giant OpenAI and its CEO Sam Altman, whom Musk accuses of abandoning the company’s founding mission.Deliberations begin Monday in the blockbuster trial pitting Elon Musk against AI giant OpenAI and its CEO Sam Altman, whom Musk accuses of abandoning the company’s founding mission.Business[#item_full_content]
Wall Street is licking its chops over an unprecedented slate of massive IPOs set to arrive in the coming months, beginning with Elon Musk’s SpaceX in June.Wall Street is licking its chops over an unprecedented slate of massive IPOs set to arrive in the coming months, beginning with Elon Musk’s SpaceX in June.Business[#item_full_content]
Recent years have witnessed the unprecedented development of Industry 4.0 and the Industrial Internet of Things. These two technologies have significantly facilitated data collection from different sources for numerous tasks, such as reconstruction, classification, and prediction, for next-generation applications. However, the effective fusion and interpretation of these multi-source datasets remain challenging, making it a thriving area of research.Recent years have witnessed the unprecedented development of Industry 4.0 and the Industrial Internet of Things. These two technologies have significantly facilitated data collection from different sources for numerous tasks, such as reconstruction, classification, and prediction, for next-generation applications. However, the effective fusion and interpretation of these multi-source datasets remain challenging, making it a thriving area of research.Computer Sciences[#item_full_content]