They work 24/7 at high speeds and get searingly hot - but data centre computer chips get plenty of pampering. Some of them basically live at the spa. We'll have fluid that comes up and [then] shower down, or trickle down, onto a component, says Jonathan Ballon, chief executive at liquid cooling firm Iceotope. Some things will get sprayed. In other cases, the industrious gizmos recline in circulating baths of fluid, which ferries away the heat they generate, enabling them to function at very high speeds, known as overclocking.

This paper considers the problem of testing for latent structure in large symmetric data matrices. The goal here is to develop statistically principled methodology that is flexible in its applicability, computationally efficient, and insensitive to extreme data variation, thereby overcoming limitations facing existing approaches. To do so, we introduce and systematically study certain symmetric matrices, called Wilcoxon--Wigner random matrices, whose entries are normalized rank statistics derived from an underlying independent and identically distributed sample of absolutely continuous random variables. These matrices naturally arise as the matricization of one-sample problems in statistics and conceptually lie at the interface of nonparametrics, multivariate analysis, and data reduction. Among our results, we establish that the leading eigenvalue and corresponding eigenvector of Wilcoxon--Wigner random matrices admit asymptotically Gaussian fluctuations with explicit centering and scaling terms. These asymptotic results enable rigorous parameter-free and distribution-free spectral methodology for addressing two hypothesis testing problems, namely community detection and principal submatrix detection. Numerical examples illustrate the performance of the proposed approach. Throughout, our findings are juxtaposed with existing results based on the spectral properties of independent entry symmetric random matrices in signal-plus-noise data settings.

Effective feature selection is essential for high-dimensional data analysis and machine learning. Unsupervised feature selection (UFS) aims to simultaneously cluster data and identify the most discriminative features. Most existing UFS methods linearly project features into a pseudo-label space for clustering, but they suffer from two critical limitations: (1) an oversimplified linear mapping that fails to capture complex feature relationships, and (2) an assumption of uniform cluster distributions, ignoring outliers prevalent in real-world data. To address these issues, we propose the Robust Autoencoder-based Unsupervised Feature Selection (RAEUFS) model, which leverages a deep autoencoder to learn nonlinear feature representations while inherently improving robustness to outliers. We further develop an efficient optimization algorithm for RAEUFS. Extensive experiments demonstrate that our method outperforms state-of-the-art UFS approaches in both clean and outlier-contaminated data settings.

We consider statistical tasks in high dimensions whose loss depends on the data only through its projection into a fixed-dimensional subspace spanned by the parameter vectors and certain ground truth vectors. This includes classifying mixture distributions with cross-entropy loss with one and two-layer networks, and learning single and multi-index models with one and two-layer networks. When the data is drawn from an isotropic Gaussian mixture distribution, it is known that the evolution of a finite family of summary statistics under stochastic gradient descent converges to an autonomous ordinary differential equation (ODE), as the dimension and sample size go to $\infty$ and the step size goes to $0$ commensurately. Our main result is that these ODE limits are universal in that this limit is the same whenever the data is drawn from mixtures of arbitrary product distributions whose first two moments match the corresponding Gaussian distribution, provided the initialization and ground truth vectors are coordinate-delocalized. We complement this by proving two corresponding non-universality results. We provide a simple example where the ODE limits are non-universal if the initialization is coordinate aligned. We also show that the stochastic differential equation limits arising as fluctuations of the summary statistics around their ODE's fixed points are not universal.

Vince Zampella, who co-created the widely-popular video game Call of Duty, has died in a single-vehicle Ferrari crash in California, aged 55. Zampella's death was confirmed by Electronic Arts, which owns Respawn Entertainment, a game studio he co-founded. This is an unimaginable loss, and our hearts are with Vince's family, his loved ones, and all those touched by his work, a spokesperson for Electronic Arts told the BBC. Officials said the person on the vehicle's passenger seat was ejected while the driver remained trapped. It is unclear if Zampella was driving the car.

The critically endangered chicks, Oscar and Duffy, were born at a New Jersey aquarium. Breakthroughs, discoveries, and DIY tips sent every weekday. An aquarium in New Jersey welcomed two new residents, just in time for the holidays. On December 20, staff at Adventure Aquarium in Camden revealed the recent births of Duffy and Oscar, a pair of African penguins () and some much needed good news in light of ongoing conservation concerns . "These milestones are incredibly important for the critically endangered African penguin population, and we couldn't be more proud to play a role in their future," the aquarium just outside of Philadelphia, Pennsylvania wrote in a social media post .

Russia has intensified its strikes on the southern Ukrainian region of Odesa, causing widespread power cuts and threatening the region's maritime infrastructure. Ukrainian Deputy Prime Minister Oleksiy Kuleba said Moscow was carrying out systematic attacks on the region. Last week, he warned that the focus of the war may have shifted towards Odesa. President Volodymyr Zelensky said the repeated attacks were an attempt by Moscow to block Ukraine's access to maritime logistics. Earlier in December, Russian President Vladimir Putin threatened to sever Ukraine's access to the sea as retaliation for drone attacks on tankers of Russia's shadow fleet in the Black Sea.

Chinese robotaxis could be set to hit UK roads in 2026 as ride-sharing apps Uber and Lyft announce partnerships with Baidu to trial the tech. The two companies are hoping to obtain approval from regulators to test the autonomous vehicles in London. Baidu's Apollo Go driverless taxi service already operates in dozens of cities, mostly in China, and has accrued millions of rides without a human behind the wheel. Transport secretary Heidi Alexander said the news was another vote of confidence in our plans for self-driving vehicles - but many remain sceptical about their safety. We're planning for self-driving cars to carry passengers for the first time from spring, under our pilot scheme - harnessing this technology safely and responsibly to transform travel, Ms Alexander said in a post on X .

President Donald Trump speaks in the Roosevelt Room flanked by Masayoshi Son, Larry Ellison, and Sam Altman at the White House on January 21, 2025. President Donald Trump speaks in the Roosevelt Room flanked by Masayoshi Son, Larry Ellison, and Sam Altman at the White House on January 21, 2025. In case you missed it, 2025 was a big year for AI. It became an economic force, propping up the stock market, and a geopolitical pawn, redrawing the frontlines of Great Power competition. It had both global and deeply personal effects, changing the ways that we think, write, and relate.

Long the province of the ultra-wealthy, prenuptial agreements are being embraced by young people--including many who don't have all that much to divvy up. More than forty per cent of millennials and Gen Z-ers claim to have signed a prenup. Andrea Zevallos declared 2016 her "year of dating." She was twenty-seven, working at Universal Studios Hollywood, the theme park, and determined to find love. She calculated it would take three dates a week. By December, she was losing hope. "It was exhausting," she said. Then, while scrolling OkCupid, she noticed a "cute guy" with a "Hamilton" reference in his handle. His name was Alex Switzky, and like her he was a musical-theatre enthusiast and aspiring screenwriter. He was different from the other men she'd met. On their second date, he started planning a third. Zevallos "was used to L.A. guys cagey about any sort of calendar." One day, Switzky called her. Accustomed to texts, she assumed that he was about to break up with her. "The most millennial response," she recalled, laughing.