In his 1927 paper, 'A law of comparative judgment,' the American psychologist L. L. Thurstone proposed that when people select one option among multiple alternatives, they are picking the one that has the highest value to them, even though they cannot assign a particular number to that choice. Thurstone was a pioneer of 'psychometrics' ' a field built upon the premise that mental processes, which we cannot see, can nevertheless be measured and quantified. His 1927 paper laid the groundwork for what are now called random utility models, which provide a mathematical framework for describing human preferences ' information that can be relied upon, in turn, to make predictions about various hypothetical situations. Random utility models (RUMs) are so named because they assess the 'utility,' or benefit, that can be obtained from a given choice ' such as deciding which book to read first among the stack of novels you brought back from the library. 'These models are inherently random,' explains Gabriele Farina, an assistant professor in MIT's Department of Electrical Engineering and Computer Science (EECS) and principal investigator at the Laboratory for Information and Decision Systems (LIDS), 'because people are different. Everyone has their own preferences, and even those preferences can vary from time to time.' For example, someone who normally picks coffee over tea in the morning, and prefers tea after dinner, may, upon occasion, mix up that order entirely....

At the 2026 World Cup, the refs on the field and the officials on the sidelines will be able to use an abundance of tech to help call penalties, spot offside violations, and make other consequential decisions. The video assistant referee system, known as VAR, and the semi-automated offside technology (SAOT) have been used in soccer for years. But the setup at this summer's World Cup represents some of the most advanced uses of adjudication tech to date'not just in soccer, but across all high-level sports. During each match, the pitch will be awash in sensors, cameras, and new computer vision software. One especially notable advancement this year is the use of digital twins. Every player in the World Cup has had their body scanned by a computer. The digital twin of any athlete'which precisely matches their height, limb length, and shoe size'can be dropped into a virtual simulation of the game to determine their exact position relative to the ball, boundary lines, and other players. Officials can use all of this data to help spot infractions, determine penalties, and smooth out the edges of the beautiful game....

The rise of artificial intelligence is riding on the back of an enormous data center expansion. Data centers are projected to account for anywhere from 9 to 17 percent of total electricity usage in the U.S. by the end of the decade. Today, around a third of data center electricity is devoted to cooling the chips that run AI models. That's the process Ferveret is working to make more efficient. The startup, founded by Reza Azizian, a former MIT postdoc in nuclear engineering, and Matteo Bucci, MIT's Esther and Harold E. Edgerton Associate Professor in the Department of Nuclear Science and Engineering, is adapting an approach from nuclear reactors to cool chips using no water and significantly less electricity. The company's cooling system submerges computer servers in a specialized liquid that absorbs heat much more efficiently than air from a fan. What makes the solution different from other liquid cooling systems are the bubbles: Ferveret's Adaptive Phase Cooling (APC) solution produces much smaller bubbles at the surface of the server, which detach more frequently, accelerating the heat transfer process....

A new kernel, or core program within an operating system, gives researchers a cleaner view of what's happening inside a processor. Called Fractal and developed at MIT, the kernel has already surfaced previously unknown behavior in Apple's M1. When security researchers want to understand what a modern processor is really doing with the kind of detail that determines whether attacks like Spectre and Meltdown are possible, they usually run their experiments on top of an operating system that was never built for the job. They open up macOS or Linux, patch the kernel by hand, and hope the modifications hold. The approach is unstable, hard to reproduce, and on Apple's platforms, slated for deprecation. A team at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) decided to build something different. Fractal, an operating system kernel written from the ground up, treats the hardware itself as the object of study. Its first major use, a deep look at branch predictors ' a CPU's way of guessing what code to run next, before it knows for certain, so it doesn't have to waste time waiting to find out ' inside Apple's M1 processor, has already turned up findings that prior work missed, including the first evidence that a class of speculative attack known as 'Phantom' affects Apple Silicon....