Race on to establish globally recognised'AI-free' logo Organisations worldwide are racing to develop a universally recognised label for human-made products and services as part of the growing backlash against AI use. Declarations like Proudly Human, Human-made, 'No A.I and AI-free are appearing across films, marketing, books and websites. It is in response to fears that jobs or entire professions are being swept away in a wave of AI-powered automation. BBC News has counted at least eight different initiatives trying to come up with a label that could get the kind of global recognition that the Fair Trade logo has for ethically made products. But with so many competing labels - as well as confusion over the definition of AI-free - experts say consumers are in danger of being left confused unless a single standard can be agreed on.

Human commonsense understanding of the physical and social world is organized around intuitive theories. These theories support making causal and moral judgments. When something bad happens, we naturally ask: who did what, and why? A rich literature in cognitive science has studied people's causal and moral intuitions. This work has revealed a number of factors that systematically influence people's judgments, such as the violation of norms and whether the harm is avoidable or inevitable.

A core problem in cognitive science and machine learning is to understand how humans derive semantic representations from perceptual objects, such as color from an apple, pleasantness from a musical chord, or seriousness from a face. Markov Chain Monte Carlo with People (MCMCP) is a prominent method for studying such representations, in which participants are presented with binary choice trials constructed such that the decisions follow a Markov Chain Monte Carlo acceptance rule. However, while MCMCP has strong asymptotic properties, its binary choice paradigm generates relatively little information per trial, and its local proposal function makes it slow to explore the parameter space and find the modes of the distribution. Here we therefore generalize MCMCP to a continuous-sampling paradigm, where in each iteration the participant uses a slider to continuously manipulate a single stimulus dimension to optimize a given criterion such as'pleasantness'. We formulate both methods from a utility-theory perspective, and show that the new method can be interpreted as'Gibbs Sampling with People' (GSP). Further, we introduce an aggregation parameter to the transition step, and show that this parameter can be manipulated to flexibly shift between Gibbs sampling and deterministic optimization. In an initial study, we show GSP clearly outperforming MCMCP; we then show that GSP provides novel and interpretable results in three other domains, namely musical chords, vocal emotions, and faces.

Dell's excellent 4K monitor is a perfect second screen for working from home. All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links. If you're tired of staring a tiny laptop screen while working from home, consider scooping up our favorite desktop monitor for almost 25 percent off its normal price. The Dell 27 Plus 4K (8/10, WIRED Reivew) is currently marked down to just $228 on Amazon, the lowest we've seen yet for this smart and practical 4K screen.

The Text With Jesus chatbot app displayed on an iPhone on Oct. 2. | AFP-JIJI New York - Artificial intelligence, the technology upending nearly every corner of society, is creeping into religion, serving up virtual Jesus and automated sermons -- a change drawing mixed reviews from the faithful. Religious chatbots and other faith-based digital tools are growing in number, offering counsel, comfort and spiritual guidance during an age of rapidly transforming socialization and engagement. One app, which is called Text with Jesus, has thousands of paying subscribers. It lets people ostensibly ask questions of Mary, Joseph, Jesus and nearly all 12 apostles. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Ominous warning for humanity as birds suddenly adopt'unsettling' behavior Meghan is accused of'giggling as model stumbles on the catwalk': More Paris Fashion Week disasters emerge, including awkward moment with Kristin Scott Thomas More girls are starting their periods younger than ever before - scientists think they've finally found what's causing it The TRUTH to the doting mother who slaughtered her children and husband told by those she'd been quietly tormenting for years Insiders confirm what everyone suspects about Taylor Swift and Blake Lively... the private apology... and how any future friendship hangs on one humiliating condition Outrage as Baltimore's Dem mayor spends $164k of taxpayer cash on ultra-luxurious new SUV I have no sympathy for them - but this disturbing new trend isn't the answer: JANA HOCKING Taylor Swift reveals truth behind raunchy song about Travis Kelce's manhood Trump stuns CNN reporter as he muses about Ghislaine Maxwell pardon: 'I haven't heard that name in so long' Revealed: Which slimming jab REALLY works best. The doctors' ultimate expert guide on which to pick, how to save money, beat every side effect... and what you need to know about the'golden dose' Functioning alcoholics hide in plain sight... so are YOU one? Trump brands NFL's Bad Bunny Super Bowl halftime show selection'absolutely ridiculous' The troubled background of delivery man stabbed by Mark Sanchez... as he launches million-dollar lawsuit and sparks civil war at Fox People who don't like animals are more likely to have dark personality traits, study finds On-screen psychopaths such as Patrick Bateman in'American Psycho' and Villanelle in ' Killing Eve ' are often depicted hurting animals. Now, a study suggests this character flaw is not just the stuff of fiction. Scientists in Serbia have found a link between psychopathy and the belief that animals aren't as worthy as humans.

The new owners could erase that legacy. The legend goes like this: In 1999, a programmer named Patrick Barrett joined the video game studio Maxis to help develop the video game that would become . Working from an out-of-date design handbook, he coded the game to allow for same-sex relationships--even though the studio initially decided to include queer relationships for fear of backlash. The game was demoed to press with a wedding scene at E3 1999, and during the demo two female Sims kissed. Suddenly the game was the talk of the event, and any attempt to walk queer content back would be impossible to do quietly.

Large Language Models (LLMs) are increasingly tasked with analyzing legal texts and citing relevant statutes, yet their reliability is often compromised by general pre-training that ingests legal texts without specialized focus, obscuring the true depth of their legal knowledge. This paper introduces CLaw, a novel benchmark specifically engineered to meticulously evaluate LLMs on Chinese legal knowledge and its application in reasoning. CLaw comprises two key components: (1) a comprehensive, fine-grained corpus of all 306 Chinese national statutes, segmented to the subparagraph level and incorporating precise historical revision timesteps for rigorous recall evaluation (64,849 entries), and (2) a challenging set of 254 case-based reasoning instances derived from China Supreme Court curated materials to assess the practical application of legal knowledge. Our empirical evaluation reveals that most contemporary LLMs significantly struggle to faithfully reproduce legal provisions. As accurate retrieval and citation of legal provisions form the basis of legal reasoning, this deficiency critically undermines the reliability of their responses. We contend that achieving trustworthy legal reasoning in LLMs requires a robust synergy of accurate knowledge retrieval--potentially enhanced through supervised fine-tuning (SFT) or retrieval-augmented generation (RAG)--and strong general reasoning capabilities. This work provides an essential benchmark and critical insights for advancing domain-specific LLM reasoning, particularly within the complex legal sphere.

The Ryder Cup returns, and it's on a golf course like no other: Bethpage Black, also known as the People's Course. It's one of the toughest tests in golf, built by working-class New Yorkers. Samantha Johnson takes a look at the history of Bethpage Black, a course that sees history, class and identity colliding on the fairways.