Large language models (LLMs), the artificial intelligence (AI) systems supporting the functioning of ChatGPT, Gemini and similar conversational platforms, are often expected to answer queries, generate texts for specific purposes and make decisions without the supervision of human experts. Yet past studies suggest that these models can sometimes mislead users, producing unreliable answers that express high confidence in false or inaccurate statements.Large language models (LLMs), the artificial intelligence (AI) systems supporting the functioning of ChatGPT, Gemini and similar conversational platforms, are often expected to answer queries, generate texts for specific purposes and make decisions without the supervision of human experts. Yet past studies suggest that these models can sometimes mislead users, producing unreliable answers that express high confidence in false or inaccurate statements.[#item_full_content]

Artificial intelligence (AI) systems, particularly the large language models (LLMs) that underpin ChatGPT and similar platforms, are remarkably skilled at answering queries about a wide range of topics. However, the extent to which they can interpret social situations and predict how humans might respond in specific scenarios remains poorly understood.Artificial intelligence (AI) systems, particularly the large language models (LLMs) that underpin ChatGPT and similar platforms, are remarkably skilled at answering queries about a wide range of topics. However, the extent to which they can interpret social situations and predict how humans might respond in specific scenarios remains poorly understood.[#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]

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]

Networks are everywhere. They connect computers across the internet, carry electricity through power grids and represent transport routes for moving people and goods. Yet many problems that appear to have nothing to do with networks can also be represented and solved as networks. Examples include matching passengers with drivers in a ride-hailing app or distributing computing tasks across servers.Networks are everywhere. They connect computers across the internet, carry electricity through power grids and represent transport routes for moving people and goods. Yet many problems that appear to have nothing to do with networks can also be represented and solved as networks. Examples include matching passengers with drivers in a ride-hailing app or distributing computing tasks across servers.[#item_full_content]

WordPress is one of the most widely used content management systems for websites. Plugins are very popular among developers and users because they allow websites to be customized with functionality tailored to individual needs.WordPress is one of the most widely used content management systems for websites. Plugins are very popular among developers and users because they allow websites to be customized with functionality tailored to individual needs.[#item_full_content]

New research suggests that generative artificial intelligence (AI) could weaken not only employment opportunities for junior software developers but also the pathway through which they develop into senior professionals.New research suggests that generative artificial intelligence (AI) could weaken not only employment opportunities for junior software developers but also the pathway through which they develop into senior professionals.[#item_full_content]

AI systems that generate video frame by frame could follow a user’s camera commands far more accurately, thanks to a new training method developed by researchers from the University of Surrey and NVIDIA. This improvement matters most when someone steers a generated scene rather than simply watching it. That includes video games built on AI-generated worlds, virtual production sets where a director can move a camera around, and simulated environments used to train robots. The findings are posted on the arXiv preprint server.AI systems that generate video frame by frame could follow a user’s camera commands far more accurately, thanks to a new training method developed by researchers from the University of Surrey and NVIDIA. This improvement matters most when someone steers a generated scene rather than simply watching it. That includes video games built on AI-generated worlds, virtual production sets where a director can move a camera around, and simulated environments used to train robots. The findings are posted on the arXiv preprint server.[#item_full_content]

A guiding principle for many software engineers—”What you see is what you get” —means creating programs where the content you’re editing looks the same as the final product. But when you’re using generative AI (genAI) systems to 3D-print, say, a mug, you’ll likely get a cup that can’t hold your coffee. Why is that?A guiding principle for many software engineers—”What you see is what you get” —means creating programs where the content you’re editing looks the same as the final product. But when you’re using generative AI (genAI) systems to 3D-print, say, a mug, you’ll likely get a cup that can’t hold your coffee. Why is that?[#item_full_content]

When a website loads quickly or an operating system runs smoothly, you can thank caching—a widely used computing process for fast data access that works by storing frequently used pieces of data in a computer’s memory.When a website loads quickly or an operating system runs smoothly, you can thank caching—a widely used computing process for fast data access that works by storing frequently used pieces of data in a computer’s memory.[#item_full_content]