'I wish I could push ChatGPT off a cliff': professors scramble to save critical thinking in an age of AI Lea Pao, a professor of literature at Stanford University, has been experimenting with ways to get her students to learn offline. She has them memorize poems, perform at recitation events, look at art in the real world. It's an effort to reconnect them to the bodily experience of learning, she said, and to keep them from turning to artificial intelligence to do the work for them. "There's no AI-proof anything," Pao said. "Rather than policing it, I hope that their overall experiences in this class will show them that there's a way out."

The speed at which artificial intelligence is gaining in mathematical ability has taken many by surprise. Are the days of handwritten mathematics coming to an end? In March 2025, mathematician Daniel Litt made a bet. Despite the march of progress of artificial intelligence in many fields, he believed his subject was safe, wagering with a colleague that there was only a 25 per cent chance an AI could write a mathematical paper at the level of the best human mathematicians by 2030. Only a year later, he thinks he was wrong.

Horrifying next twist in the Alexander brothers case: MAUREEN CALLAHAN exposes an unthinkable perversion that's been hiding in plain sight Hollywood icon who starred in Psycho after Hitchcock dubbed her'my new Grace Kelly' looks incredible at 95 Alexander brothers' alleged HIGH SCHOOL rape video: Classmates speak out on sickening footage... as creepy unseen photos are exposed Model Cindy Crawford, 60, mocked for her'out of touch' morning routine: 'Nothing about this is normal' Kentucky mother and daughter turn down $26.5MILLION to sell their farms to secretive tech giant that wants to build data center there Tucker Carlson erupts at Trump adviser as she hurls'SLANDER' claim linking him to synagogue shooting NFL superstar Xavier Worthy spills all on Travis Kelce, the Chiefs' struggles... and having Taylor Swift as his No 1 fan Heartbreaking video shows very elderly DoorDash driver shuffle down customer's driveway with coffee order because he is too poor to retire Amber Valletta, 52, was a '90s Vogue model who made movies with Sandra Bullock and Kate Hudson, see her now Nancy Mace throws herself into Iran warzone as she goes rogue on Middle East rescue mission: 'I AM that person' The hidden generation of'Starseed' children with telepathy and healing powers and the signs your child could be among them The future of humanity may be in the hands of a special group of children born with exceptional powers, a psychic medium has claimed. Jill M Jackson told the Daily Mail that these so-called'starseeds' are souls with origins beyond Earth, reincarnated in human bodies after living elsewhere in the universe. She said these gifted children, with telepathic and healing abilities, have appeared in waves over generations, with the last decade bringing two particularly notable waves. 'The guardians of these children talk about really needing to be aware of their thoughts, because their children can telepathically hear what they are saying, even being in the other room,' Jackson explained. 'One parent gave me an example.

'You can't replace human connection, human judgment,' warns Sarah Caliboso-Soto, a licensed clinical social worker. 'You can't replace human connection, human judgment,' warns Sarah Caliboso-Soto, a licensed clinical social worker. Schools are using AI counselors to track students' mental health. As hundreds of schools implement an automated monitoring tool, educators say that students can find talking to a chatbot'more natural' than confiding in a human The alert came around 7pm. Brittani Phillips checked her phone. A middle school counselor in Putnam county, Florida, Phillips receives messages from an artificial intelligence-enabled therapy platform that students use during nonschool hours.

Algorithmic decisions about individuals require predictions that are not only accurate but also fair with respect to sensitive attributes such as gender and race. Causal notions of fairness align with legal requirements, yet many methods assume access to detailed knowledge of the underlying causal graph, which is a demanding assumption in practice. We propose a learning framework that achieves interventional fairness by leveraging a causal graph over \textit{clusters of variables}, which is substantially easier to estimate than a variable-level graph. With possible \textit{adjustment cluster sets} identified from such a cluster causal graph, our framework trains a prediction model by reducing the worst-case discrepancy between interventional distributions across these sets. To this end, we develop a computationally efficient barycenter kernel maximum mean discrepancy (MMD) that scales favorably with the number of sensitive attribute values. Extensive experiments show that our framework strikes a better balance between fairness and accuracy than existing approaches, highlighting its effectiveness under limited causal graph knowledge.

ROTC students at Old Dominion subdued and killed ISIS-linked gunman who left one dead, two wounded after shouting'Allahu Akbar' and opened fire Horrifying next twist in the Alexander brothers case: MAUREEN CALLAHAN exposes an unthinkable perversion that's been hiding in plain sight Kentucky mother and daughter turn down $26.5MILLION to sell their farms to secretive tech giant that wants to build data center there Hollywood icon who starred in Psycho after Hitchcock dubbed her'my new Grace Kelly' looks incredible at 95 Kylie Jenner's total humiliation in Hollywood: Derogatory rumor leaves her boyfriend's peers'laughing at her' behind her back Tucker Carlson erupts at Trump adviser as she hurls'SLANDER' claim linking him to synagogue shooting Ben Affleck'scores $600m deal' with Netflix to sell his AI film start-up Long hair over 45 is ageing and try-hard. I've finally cut mine off. Alexander brothers' alleged HIGH SCHOOL rape video: Classmates speak out on sickening footage... as creepy unseen photos are exposed Heartbreaking video shows very elderly DoorDash driver shuffle down customer's driveway with coffee order because he is too poor to retire Amber Valletta, 52, was a '90s Vogue model who made movies with Sandra Bullock and Kate Hudson, see her now Model Cindy Crawford, 60, mocked for her'out of touch' morning routine: 'Nothing about this is normal' Ey up AI! Scientists are teaching artificial intelligence how to understand UK accents and dialects - so, how many of these regional terms do YOU know? Scientists are teaching AI how to understand slang words such as'chuck' and'nowt' so that automated phone lines can understand local callers. Councils across the UK are turning to artificial intelligence to man their phones, helping people with enquiries such as when to put their bins out or how to pay their council tax.

Understanding minimal assumptions that enable learning and generalization is perhaps the central question of learning theory. Several celebrated results in statistical learning theory, such as the VC theorem and Littlestone's characterization of online learnability, establish conditions on the hypothesis class that allow for learning under independent data and adversarial data, respectively. Building upon recent work bridging these extremes, we study sequential decision making under distributional adversaries that can adaptively choose data-generating distributions from a fixed family $U$ and ask when such problems are learnable with sample complexity that behaves like the favorable independent case. We provide a near complete characterization of families $U$ that admit learnability in terms of a notion known as generalized smoothness i.e. a distribution family admits VC-dimension-dependent regret bounds for every finite-VC hypothesis class if and only if it is generalized smooth. Further, we give universal algorithms that achieve low regret under any generalized smooth adversary without explicit knowledge of $U$. Finally, when $U$ is known, we provide refined bounds in terms of a combinatorial parameter, the fragmentation number, that captures how many disjoint regions can carry nontrivial mass under $U$. These results provide a nearly complete understanding of learnability under distributional adversaries. In addition, building upon the surprising connection between online learning and differential privacy, we show that the generalized smoothness also characterizes private learnability under distributional constraints.

'People are being more discerning about spending money,' he says. 'People are being more discerning about spending money,' he says. T hey are already packing our groceries and delivering shopping. Now robots are coming to the kebab shop, alongside self-service screens and loyalty apps, as takeaways look for ways to tackle rising costs. German Doner Kebab (GDK), a perhaps surprisingly British-owned chain that has been springing up across the country, has turned to technology to keep its fast food business buzzing in the face of rising costs and tough times on the high street.

Don't make us security guards, says teacher stabbed by pupil A teacher who thought she was going to die when she was stabbed by a 13-year-old pupil in the schoolyard has said giving staff handheld scanners will not stop violence in schools. Liz Hopkin, who was attacked at Ysgol Dyffryn Aman in 2024, said she felt really worried after the Welsh government announced it would offer school staff more guidance on what to do if they suspected a pupil had brought a weapon into school. It comes as a 15-year-old boy was charged with attempted murder after a teacher was stabbed at a school in the neighbouring county. Hopkin said teachers aren't security, while the Welsh government said the resources were about prevention, building on existing guidance. Hopkin, her colleague Fiona Elias and a pupil were attacked at the school where she worked in Ammanford, Carmarthenshire, by a girl who had previously been found with a knife.