Scientists and engineers at Lawrence Livermore National Laboratory (LLNL) have developed a camera-based inspection system that can monitor complex 3D-printed structures layer by layer, using AI and machine learning (ML) to measure tiny variations and potentially identify problems before a part ever leaves the printer.Scientists and engineers at Lawrence Livermore National Laboratory (LLNL) have developed a camera-based inspection system that can monitor complex 3D-printed structures layer by layer, using AI and machine learning (ML) to measure tiny variations and potentially identify problems before a part ever leaves the printer.Engineering[#item_full_content]
Calls to rein in the development of ever more powerful AI models are fueling fears over the massive capital outlays in the sector—and the prospect that profits from the promised revolution might not be enough to cover them.Calls to rein in the development of ever more powerful AI models are fueling fears over the massive capital outlays in the sector—and the prospect that profits from the promised revolution might not be enough to cover them.Machine learning & AI[#item_full_content]
The United Nations rights chief called Monday for countries and “frontier” artificial intelligence companies to act urgently to rein in a technology he warned posed “unprecedented risks.”The United Nations rights chief called Monday for countries and “frontier” artificial intelligence companies to act urgently to rein in a technology he warned posed “unprecedented risks.”Machine learning & AI[#item_full_content]
A new deep-learning architecture could deflect cyberattacks by combining several methods for analyzing network traffic, according to research published in the International Journal of Business Intelligence and Data Mining. The approach addresses a weakness in standard intrusion-detection systems, which struggle with the volume and complexity of modern network traffic.A new deep-learning architecture could deflect cyberattacks by combining several methods for analyzing network traffic, according to research published in the International Journal of Business Intelligence and Data Mining. The approach addresses a weakness in standard intrusion-detection systems, which struggle with the volume and complexity of modern network traffic.Security[#item_full_content]
MIT researchers have developed a new technique that helps generative artificial intelligence models find solutions to high-stakes problems. In these settings, a plausible answer is not enough: The output often must also satisfy nonnegotiable safety, physical or task-specific requirements, known as hard constraints.MIT researchers have developed a new technique that helps generative artificial intelligence models find solutions to high-stakes problems. In these settings, a plausible answer is not enough: The output often must also satisfy nonnegotiable safety, physical or task-specific requirements, known as hard constraints.Computer Sciences[#item_full_content]
MIT researchers have developed a new technique that helps generative artificial intelligence models find solutions to high-stakes problems. In these settings, a plausible answer is not enough: The output often must also satisfy nonnegotiable safety, physical or task-specific requirements, known as hard constraints.MIT researchers have developed a new technique that helps generative artificial intelligence models find solutions to high-stakes problems. In these settings, a plausible answer is not enough: The output often must also satisfy nonnegotiable safety, physical or task-specific requirements, known as hard constraints.[#item_full_content]
As a child, you likely saw a few Disney movies depicting inanimate objects, such as clocks, cups and toys, as interactive companions to humans—an act of pure magic, seemingly. But scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are now doing something similar: transforming stationary items into self-aware tools that perceive and respond to human motion to complete a task.As a child, you likely saw a few Disney movies depicting inanimate objects, such as clocks, cups and toys, as interactive companions to humans—an act of pure magic, seemingly. But scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are now doing something similar: transforming stationary items into self-aware tools that perceive and respond to human motion to complete a task.[#item_full_content]
William Overman began his Ph.D. program at Stanford Graduate School of Business at an auspicious moment: just two months before ChatGPT launched publicly in November 2022, exploding the widely held understanding of what machines are capable of.William Overman began his Ph.D. program at Stanford Graduate School of Business at an auspicious moment: just two months before ChatGPT launched publicly in November 2022, exploding the widely held understanding of what machines are capable of.Computer Sciences[#item_full_content]
William Overman began his Ph.D. program at Stanford Graduate School of Business at an auspicious moment: just two months before ChatGPT launched publicly in November 2022, exploding the widely held understanding of what machines are capable of.William Overman began his Ph.D. program at Stanford Graduate School of Business at an auspicious moment: just two months before ChatGPT launched publicly in November 2022, exploding the widely held understanding of what machines are capable of.[#item_full_content]
Recently, Anthropic chief executive Dario Amodei called for artificial intelligence (AI) companies, including his own, to slow down their work. Sam Altman and Elon Musk, heads of rivals OpenAI and xAI respectively, agreed.Recently, Anthropic chief executive Dario Amodei called for artificial intelligence (AI) companies, including his own, to slow down their work. Sam Altman and Elon Musk, heads of rivals OpenAI and xAI respectively, agreed.Business[#item_full_content]
