The AI giant is worried about what all-powerful bots could mean for our constitutional rights. Late last month, OpenAI launched a rather grand mission: nothing less than defending individual political freedom in an age of all-powerful machines. The company's "Strategic Futures" team has styled itself, in a sense, as inheriting the task of America's Founding Fathers: "We labor in service of the ideals of free expression and individual liberty that are enshrined in the humble parchment of the U.S. Constitution," Dean Ball, the team's leader, wrote in a new OpenAI blog post. Ball worries that advanced AI could radically concentrate power in the hands of those who control it, displacing labor in ways that disempower humans. In an extreme scenario, governments will have no need to listen to their citizens if there are robots to wage wars and omniscient software to run the bureaucracy.

Golden State Valkyries and New York Liberty headline two WNBA picks for tonight's slate Governor Landry backs Lane Kiffin, LSU in fight with SEC: 'Don't hate the player, hate the game' Giants QB's girlfriend takes NFL preseason fashion to next level, 9U football kid unloads & Horvat kids' clubs Vinod Khosla knows little about owning an NFL team but it's fine because he just bought the Super Bowl champs MLB stadium looks virtually empty as fans send clear message about the team: 'Embarrassing' Defense didn't give the jury a'path to not guilty': Donna Rotunno Jonathan Turley argues Lindsay Clancy's defense'lost ground' during closing arguments Historic cross fight could'unravel' LA community traditions, lawyer warns House Dems appoint pro-Israel lawmakers in blow to party's far-left wing Ritter: Clancy prosecution was'surprisingly' effective in closing arguments'Survivor' star Christian Hubicki talks China's wild Robot Olympics: 'They're willing to break the robots': Brit struggles to define'woman' in spectacular exchange OutKick Sports LA Sparks star directs explicit rant at Enes Kanter Freedom over trans debate: 'Stupid piece of s---' Former NBA players Enes Kanter Freedom and Royce White will reportedly be denied from entering the upcoming 2027 WNBA draft league. 'Outnumbered' reacts and debates Charles Barkley's viral comments defending women's sports. Los Angeles Sparks forward Cameron Brink sharply criticized Enes Kanter Freedom, using explicit language and calling the former NBA center a stupid piece of s-- for challenging the WNBA's draft eligibility rules. The 2024 No. 2 overall pick dismissed the national debate over transgender athletes in women's sports as a manufactured non-issue before directing her comments personally at Freedom. Speaking with Mirror U.S. Sports, Brink framed the debate as an attack on the transgender community rather than a dispute over competitive fairness.

Harrison Butker's 69-yard field goal demonstrates the NFL's latest big scoring controversy Nationals outfielder does his best Spider-Man impression for one of baseball's best catches of the year Oregon coach Dan Lanning lays out multiple reasons why NFL players returning to college football is'unfair' Ryan Lochte's fiancée wants his former Playboy model ex-wife to take those'homewrecker' claims somewhere else Chiefs' Harrison Butker nails incredible 69-yard field goal vs Bucs, shares disappointment with performance Supporting data centers is'perilous' politically: Brian Kilmeade'Misinformation' about AI data centers is widespread, former Texas Gov Rick Perry says Socialists don't believe in liberty of any kind: Daniel Di Martino North, South Korea have a'complicated' relationship: Rep Brian Mast There is no justice in the history of the Supreme Court more willing to'go further' than Justice Clarence Thomas: Sen. Ted Cruz Clarence Thomas won't'pick a fight' or'seek trouble': Sen Ted Cruz Iran threatens'seismic retaliation' as Trump administration prepares new sanctions Freedom says the Chicago Sky guard told him'she's not gonna sleep with you' after he cheered for Sophie Cunningham Former NBA player Enes Kanter Freedom said Chicago Sky guard Natasha Cloud made a vulgar remark toward him and repeatedly cursed before security removed him from Sunday night's game against the Indiana Fever. Freedom, who was sitting near the baseline at Wintrust Arena, said the confrontation began after he celebrated a 3-pointer by Fever guard Sophie Cunningham. Sophie Cunningham shot a three, and I put my hands up to celebrate, Freedom said. Literally, a couple possessions later, Natasha came back and started screaming and yelling and said, 'She's not gonna sleep with you.' Chicago Sky guard Natasha Cloud argues with former NBA center Enes Kanter Freedom during the second half of a WNBA basketball game against the Indiana Fever on Sunday, Aug. 23, 2026, in Chicago. And I was like, 'I am not trying to sleep with her. I'm just here to protect women and support her.' And then, obviously, after that she started yapping, and she started to walk towards me, and literally I just got up, and then I was like, 'I'm just here to protect women, and that's all.' Video of the incident showed Cloud walking toward Freedom, yelling and pointing at him late in the third quarter. Freedom stood, extended his arms and took a step onto the court as security and Sky players moved between them.

Japan's parliament has enacted a controversial law introducing criminal penalties for desecrating the national flag. The passage of the legislation on Friday is part of an ongoing drive by staunchly conservative Prime Minister Sanae Takaichi to promote traditional patriotism and correct what her supporters call a "wrong" legal double standard. Under the newly enacted law, violators who publicly damage, remove or defile the national flag in a manner that causes others "extreme discomfort or disgust" face up to two years in prison or a fine of up to 200,000 yen ($1,250). According to Japanese broadcaster Kyodo News, the law covers physical acts of vandalism such as stomping, burning, or throwing mud in public spaces, as well as livestreaming such acts. The law drafting committee, led by former Chief Cabinet Secretary Hirokazu Matsuno, carved out highly specific legal exemptions. The ruling party clarified that the new law completely exempts physical paintings, digital media including anime, manga, video games, and generative AI, and even the miniature paper flags famously used to decorate children's restaurant meals.

The next time you're scrolling your phone, take a moment to appreciate the feat: The seemingly mundane act is possible thanks to the coordination of 34 muscles, 27 joints, and over 100 tendons and ligaments in your hand. Indeed, our hands are the most nimble parts of our bodies. Mimicking their many nuanced gestures has been a longstanding challenge in robotics and virtual reality. Now, MIT engineers have designed an ultrasound wristband that precisely tracks a wearer's hand movements in real-time. The wristband produces ultrasound images of the wrist's muscles, tendons, and ligaments as the hand moves, and is paired with an artificial intelligence algorithm that continuously translates the images into the corresponding positions of the five fingers and palm.

Linear attention has attracted interest as a computationally efficient approximation to softmax attention, especially for long sequences. Recent studies have explored distilling softmax attention in pre-trained Transformers into linear attention. However, a critical challenge remains: how to choose the feature dimension that governs the approximation quality. Existing methods fix this dimension uniformly across all attention layers, overlooking the diverse roles and complexities of them. In this paper, we propose a principled method to automatically determine the feature dimension in linear attention using the concept of statistical degrees of freedom, which represent the effective dimensionality of the inputs. We provide a theoretical bound on the approximation error and show that the dimension chosen by our method achieves smaller errors under a fixed computational budget. Furthermore, we introduce an efficient layerwise training strategy to learn nonlinear features tailored to each layer. Experiments on multiple pre-trained transformers demonstrate that our method improves the performance of distilled models compared to baselines without increasing the inference cost. Our findings also provide insight into how the complexity of the attention mechanism evolves across layers.

The analogy between deep neural network forward passes and renormalization group (RG) flows has been repeatedly noted in the literature, but existing treatments remain qualitative: depth is described as a coarse-graining scale, attention is likened to a partition function, and representations are said to flow toward fixed points. No existing work has defined a measurable RG order parameter, tested it under controlled variation of the input distribution, or made quantitative predictions that are empirically verified. We study the simplest architecture for which the analogy is tractable: a pure MLP residual stack trained on masked token prediction over synthetic Markov chain sequences with known spectral properties. We report three findings. (i) The effective rank of the residual stream decreases monotonically with depth after training, consistent with progressive integration of irrelevant degrees of freedom. (ii) This rank collapse is selective: it occurs for chains with short correlation length approximately 1 but is absent for chains with long correlation length approximately 7, measured at the position level to control for mean-pooling artifacts. The network preserves exactly the degrees of freedom relevant to the prediction task, the content of the RG relevance criterion. (iii) Inter-layer kernel drift is concentrated at one or two specific transitions, with the remainder of the network near a fixed point, consistent with a discrete fixed-point plateau. Together these findings constitute the first quantitative, position-level evidence that MLP residual networks implement a selective coarse-graining procedure governed by the spectral structure of the input distribution.

Identifying latent variables and the causal structure involving them is essential across various scientific fields. While many existing works fall under the category of constraint-based methods (with e.g. conditional independence or rank deficiency tests), they may face empirical challenges such as testing-order dependency, error propagation, and choosing an appropriate significance level. These issues can potentially be mitigated by properly designed score-based methods, such as Greedy Equivalence Search (GES) (Chickering, 2002) in the specific setting without latent variables. Yet, formulating score-based methods with latent variables is highly challenging. In this work, we develop score-based methods that are capable of identifying causal structures containing causally-related latent variables with identifiability guarantees. Specifically, we show that a properly formulated scoring function can achieve score equivalence and consistency for structure learning of latent variable causal models. We further provide a characterization of the degrees of freedom for the marginal over the observed variables under multiple structural assumptions considered in the literature, and accordingly develop both exact and continuous score-based methods. This offers a unified view of several existing constraint-based methods with different structural assumptions. Experimental results validate the effectiveness of the proposed methods.

Enes Kanter Freedom says Taiwan is the center of the global technology race and remains a key unresolved issue after the Trump-Xi summit produced no new discussions on chips or AI.

Government departments and other public bodies in the UK must consider requests to release information about AI-produced content, regulators have confirmed. The move follows a successful request by New Scientist for the release of a minister's ChatGPT logs The use of AI chatbots is subject to the UK's Freedom of Information laws Text, images and other content produced by UK government departments and other public bodies using artificial intelligence are subject to freedom of information (FOI) laws, regulators have confirmed - potentially opening the door for the public to gain access to ministers' ChatGPT or other chatbot records. The Information Commissioner's Office (ICO), the UK's data-protection agency, has released new guidance confirming that "If staff at a public authority use AI for work purposes, the information generated will be subject to FOIA [the Freedom of Information Act] along with the prompts used". Last year, successfully requested the then-UK tech secretary Peter Kyle's ChatGPT logs under FOI legislation, in what is believed to be a world first. That triggered subsequent requests from other news outlets to obtain other information, but many have either been rejected on cost grounds or labelled as "vexatious", an umbrella term that allows authorities to reject a request.