The skills needed for wrapping up aren't always what you expect. My house contains a vaguely defined room--a parlor-like space that was created by a renovation decades ago. After my son was born, it served as a playroom, full of baby and toddler toys. Then it became a nook where, late at night, my wife and I could listen to music and read. That equilibrium held until the Legos and board games arrived; their incursion was the beginning of the end.

Placebo and "knowcebo" effects are a problem. But they can also help people feel better. This week I want to look at where we are with psychedelics, the mind-altering substances that have somehow made the leap from counterculture to major focus of clinical research. Compounds like psilocybin--which is found in magic mushrooms--are being explored for all sorts of health applications, including treatments for depression, PTSD, addiction, and even obesity. Over the last decade, we've seen scientific interest in these drugs explode. But most clinical trials of psychedelics have been small and plagued by challenges.

In many settings, machine learning models may be used to inform decisions that impact individuals or entities who interact with the model. Such entities, or may model decisions by manipulating their inputs to the model to obtain better outcomes and maximize some utility. We consider a multi-agent setting where the goal is to identify the "worst offenders:" agents that are gaming most aggressively. However, identifying such agents is difficult without knowledge of their utility function. Thus, we introduce a framework in which each agent's tendency to game is parameterized via a scalar. We show that this gaming parameter is only partially identifiable. By recasting the problem as a causal effect estimation problem where different agents represent different "treatments," we prove that a ranking of all agents by their gaming parameters is identifiable. We present empirical results in a synthetic data study validating the usage of causal effect estimation for gaming detection and show in a case study of diagnosis coding behavior in the U.S. that our approach highlights features associated with gaming.

Three people associated with artificial intelligence server maker Super Micro Computer, including its cofounder, have been charged with helping smuggle at least $2.5bn-worth of United States AI technology to China in violation of export laws, according to the US Department of Justice. US prosecutors did not name Super Micro in the complaint, referring only to a "US manufacturer", but San Jose, California-based Super Micro said it was informed by federal prosecutors of the indictment on Thursday. The Justice Department said it had charged Yih-Shyan Liaw, Ruei-Tsang Chang, and Ting-Wei Sun in an indictment unsealed in federal court in Manhattan on Thursday, on allegations of a complex scheme to send US-made servers through Taiwan to other countries in Southeast Asia, where they were swapped into unmarked boxes and sent on to China. The US has had export restrictions on China for advanced AI chips since 2022. In a release, FBI Assistant Director in Charge James Barnacle said the defendants used fabricated documents, staged bogus equipment to pass audit inventories, and used a pass-through company to conceal their misconduct and true clientele list.

Obtaining the human-like perception ability of abstracting visual concepts from concrete pixels has always been a fundamental and important target in machine learning research fields such as disentangled representation learning and scene decomposition. Towards this goal, we propose an unsupervised transformer-based Visual Concepts Tokenization framework, dubbed VCT, to perceive an image into a set of disentangled visual concept tokens, with each concept token responding to one type of independent visual concept. Particularly, to obtain these concept tokens, we only use cross-attention to extract visual information from the image tokens layer by layer without self-attention between concept tokens, preventing information leakage across concept tokens. We further propose a Concept Disentangling Loss to facilitate that different concept tokens represent independent visual concepts. The cross-attention and disentangling loss play the role of induction and mutual exclusion for the concept tokens, respectively. Extensive experiments on several popular datasets verify the effectiveness of VCT on the tasks of disentangled representation learning and scene decomposition. VCT achieves the state of the art results by a large margin.

The data leak triggered a major internal security alert inside Meta. The data leak triggered a major internal security alert inside Meta. Fri 20 Mar 2026 02.00 EDTLast modified on Fri 20 Mar 2026 03.03 EDT An AI agent instructed an engineer to take actions that exposed a large amount of Meta's sensitive data to some of its employees, in the latest example of AI causing upheaval in a large tech company. The leak, which Meta confirmed, happened when an employee asked for guidance on an engineering problem on an internal forum. An AI agent responded with a solution, which the employee implemented - causing a large amount of sensitive user and company data to be exposed to its engineers for two hours.

Two robots box while German Chancellor Friedrich Merz visits Unitree Robotics in Zhejiang Province, China. In the exhibition hall at Unitree Robotics in Hangzhou, Friedrich Merz smiled and applauded the martial arts display by a platoon of humanoid warriors. But when a robot boxer advanced toward him, punching the air with its red-gloved fists, the German chancellor flinched, a look of alarm crossing his face as he appeared to realize the danger posed by an autonomous fighting machine. It was also a moment that crystallized for Merz the power of China's technology, according to a person familiar with his thinking. He saw it, too, as a sign of how far behind Germany has fallen and how European Union regulation holds back their efforts to catch up, the person said, asking not to be named discussing the chancellor's private views. The trip, last month, has triggered a broader reckoning that is starting to settle in across Europe: Maybe de-risking from China is just too big a task.

Federal prosecutors charged three men linked to Supermicro with allegedly smuggling $2.5 billion in U.S. AI technology to China using fake documents, dummy servers, and shell companies.

A trio linked with a US technology supplier have been charged over a ploy to smuggle American artificial intelligence (AI) chips to China, the Department of Justice said on Thursday. The individuals allegedly conspired to sell billions of dollars' worth of technology to buyers in China by faking documents and using dummy equipment to slip past audits, according to the DOJ. The goods in question included Nvidia-made semiconductors, highly coveted AI chips which are subject to export controls. In August 2025, two Chinese nationals were also arrested and charged with illegally shipping millions of dollars' worth of Nvidia chips to China. The DOJ said in a statement on Thursday that it had arrested US-citizen Yih-Shyan Wally Liaw and Taiwanese citizen Ting-Wei Willy Sun, while Ruei-Tsang Steven Chang, a Taiwanese citizen, remains a fugitive.

The return of BTS is a big deal. In case you were in any doubt, just look at the frenzy surrounding the South Koreans' comeback. On Saturday, the band will kick off a sold-out, 82-date world tour with a free concert in Seoul, which is expected to be attended by more than 250,000 in-person fans and will be live-streamed on Netflix to more than 190 countries. When the tour wraps up in 2027, BTS are expected to have generated more than $1billion in revenue. Some more outlandish estimates suggest they will eclipse the $2billion haul of Taylor Swift's Eras tour.