Robots are trained for specific tasks, such as cutting, using simulation. However, collecting real-world data is expensive, slow, and sometimes unsafe, particularly for tasks involving physical interaction. A new AI-based method co-developed by Aston University’s Dr. Alireza Rastegarpanah could revolutionize the way advanced robotic systems are trained for real-life tasks, making them more practical and reliable.Robots are trained for specific tasks, such as cutting, using simulation. However, collecting real-world data is expensive, slow, and sometimes unsafe, particularly for tasks involving physical interaction. A new AI-based method co-developed by Aston University’s Dr. Alireza Rastegarpanah could revolutionize the way advanced robotic systems are trained for real-life tasks, making them more practical and reliable.Machine learning & AI[#item_full_content]

Researchers from MIT and elsewhere have developed a more user-friendly and efficient method to help networking engineers identify potential system failures before they cause major problems, like a cloud service outage that leaves millions of users unable to access applications.Researchers from MIT and elsewhere have developed a more user-friendly and efficient method to help networking engineers identify potential system failures before they cause major problems, like a cloud service outage that leaves millions of users unable to access applications.Computer Sciences[#item_full_content]

On a recent weekday, around 50 people gathered outside the headquarters of a Chinese mobile internet company, waiting to get help with installing an artificial intelligence assistant.On a recent weekday, around 50 people gathered outside the headquarters of a Chinese mobile internet company, waiting to get help with installing an artificial intelligence assistant.Machine learning & AI[#item_full_content]

The US government on Tuesday announced in a policy shift that it will have access to tech giants’ new AI models to evaluate them before they are released.The US government on Tuesday announced in a policy shift that it will have access to tech giants’ new AI models to evaluate them before they are released.Machine learning & AI[#item_full_content]

Hydrology experts at the U.S. Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) used artificial intelligence and a physics-based understanding of streamflow to create a model that provides highly accurate predictions of river temperatures, even in waterways that lack sensors. The findings are published in the Journal of Hydrology.Hydrology experts at the U.S. Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) used artificial intelligence and a physics-based understanding of streamflow to create a model that provides highly accurate predictions of river temperatures, even in waterways that lack sensors. The findings are published in the Journal of Hydrology.Energy & Green Tech[#item_full_content]

NASA announced that it will launch the Nancy Grace Roman space telescope into orbit in September 2026, eight months ahead of schedule. The new space telescope is expected to deliver 20,000 terabytes of data to astronomers over the course of its life.NASA announced that it will launch the Nancy Grace Roman space telescope into orbit in September 2026, eight months ahead of schedule. The new space telescope is expected to deliver 20,000 terabytes of data to astronomers over the course of its life.Machine learning & AI[#item_full_content]

Artificial intelligence systems based on neural networks—such as ChatGPT, Claude, DeepSeek or Gemini—are extraordinarily powerful, yet their internal workings remain largely a “black box.” To better understand how these systems produce their responses, a group of physicists at Harvard University has developed a simplified mathematical model of learning in neural networks that can be analyzed mathematically using the tools of statistical physics.Artificial intelligence systems based on neural networks—such as ChatGPT, Claude, DeepSeek or Gemini—are extraordinarily powerful, yet their internal workings remain largely a “black box.” To better understand how these systems produce their responses, a group of physicists at Harvard University has developed a simplified mathematical model of learning in neural networks that can be analyzed mathematically using the tools of statistical physics.Computer Sciences[#item_full_content]

In a novel attempt to improve how large language models learn and make them more capable and energy-efficient, Stevens Institute of Technology researchers have devised an algorithm that improves AI data sharing, boosts performance and reduces power consumption.In a novel attempt to improve how large language models learn and make them more capable and energy-efficient, Stevens Institute of Technology researchers have devised an algorithm that improves AI data sharing, boosts performance and reduces power consumption.Machine learning & AI[#item_full_content]