A three-day conference on AI at 70: What Must Remain Human? began on Oct. 29, drawing industry leaders, tech experts, policymakers, critics, and researchers to Dartmouth, and bringing a sharp focus on human judgment to the equation. Marking 70 years since Dartmouth hosted the summer workshop that launched artificial intelligence as a field of research, day one
Today, Amazon SageMaker AI announces support for Seekable OCI (SOCI)-indexed container images for training and processing jobs, so your jobs start running your code sooner. SOCI-indexed images start Amazon SageMaker AI training containers in seconds, cutting GPU idle time during image pulls by up to 90%, with no impact on training performance. Before a training
By Adam Zewe | MIT News Generative artificial intelligence models are rooted in ideas of mid-20th century engineers who thought some amount of irrationality was essential for a machine that could think like a human, contends Benjamin Lindquist, an assistant professor in the MIT History Section, who holds an MIT Schwarzman College of Computing shared
Skip to main content We’d just watched the keynote at Nebius House and headed over to GTC Berlin. Once we made it inside along with a crowd of eager attendees, it was packed and buzzing. The first thing I noticed was robots. A lot of robots. And a clean, shiny booth, which would soon bear a new Nebius tagline, courtesy of Jensen Huang. (Scroll down for that one.)
Key Takeaways: Universities are integrating AI into engineering education while reinforcing physics, math, and other fundamentals that students need to evaluate AI-generated work. Critical thinking and engineering judgment are more important than ever because AI can produce plausible but incorrect answers, leaving students responsible for verifying results and assumptions. Schools are redesigning assessments around oral
A new low-cost, scalable AI deep learning model to detect lung infections using CT scans. By Research Matters Staff Writer(s) · October 29, 2026 · Bhubaneswar · 2 min read EN Understanding lung infections such as pneumonia and tuberculosis requires expert analysis of chest CT scans. Catching these infections early is crucial to ensure proper
Accurate forecasting of renewable energy has become increasingly important for planning, managing and operating modern power systems as wind, solar and other renewable sources take up a growing share of electrical grids. A new systematic review published in Neural Computing and Applications examines how deep learning, one of the most prominent approaches in this field
Industrial environments generate vast amounts of sensor data, but most of it remains underutilized. Deployed on AWS, Archetype AI’s Newton physical world model brings Physical AI to manufacturing, turning raw signals into real-time operational intelligence. Introduction The next wave of AI is moving beyond the digital realm and into the physical world. Foundation models have
Physicists have trained two artificial intelligence models to identify the topological charge of Laguerre-Gaussian laser beams from nothing more than a small fragment of the random speckle pattern the beams produce after scattering from a rough surface. The work, published in Applied Physics B, pushes the reliable detection of these swirling optical modes up to
At MSToronto 2026, investigators applied machine learning to health records, retinal scans, and blood samples to flag multiple sclerosis and neuromyelitis optica spectrum disorder years before diagnosis or disability worsening, and identified the symptoms and conditions that tend to come first. Machine learning models applied to electronic health records (EHRs), retinal imaging, and blood samples