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.

Many high-dimensional statistical inference problems are believed to possess inherent computational hardness. Various frameworks have been proposed to give rigorous evidence for such hardness, including lower bounds against restricted models of computation (such as low-degree functions), as well as methods rooted in statistical physics that are based on free energy landscapes. This paper aims to make a rigorousconnectionbetween the seeminglydifferent low-degreeand free-energybased approaches. We define a free-energybasedcriterionfor hardnessand formallyconnectit to the well-establishednotionof low-degree hardness for a broad class of statistical problems, namely all Gaussian additive models and certain models with a sparse planted signal.

A.I. is coming for knowledge work, and yet college seems to be getting easier. Does something need to change? Around twenty years ago, when I was a graduate student in English, I taught a class in a special observation room at my university's teaching center. My students and I sat around a long oval table while cameras recorded us. I can't remember which novel we discussed, but I do know what I learned when I watched the tape afterward, with a teaching coach. She pointed out that, when I was calling on students, I often looked to my right, missing the raised hands on my left. I didn't let silences go on long enough, instead speaking just when a student had worked up the courage to talk. On the plus side, she noticed I'd been using a technique she liked, which I'd borrowed from a professor of mine: it was like cold-calling, except that, after you'd surprised a student with a challenging question, you told them that you'd circle back in a few minutes, to give them time to consider what they'd say.

This article was featured in One Story to Read Today, a newsletter in which our editors recommend a single must-read from The Atlantic, Monday through Friday. Diana Henriques was first stricken in late 1996. A business reporter for The New York Times, she was in the midst of a punishing effort to bring a reporting project to fruition. Then one morning she awoke to find herself incapable of pinching her contact lens between her thumb and forefinger. Henriques's hands were soon cursed with numbness, frailty, and a gnawing ache she found similar to menstrual cramps.

Banks seem to hate when their customers go on holiday. Somewhere in the world, Joe Bloggs has gambled that he won't need to bring cash with him to sunny Sweden, since the Swedes seem to accept card payments more or less everywhere. As soon as he taps his plastic to the reader, however, there's still a small chance that his bank decides to block the transaction. After all, say the algorithms, what evidence is there in the corporate records that Mr Bloggs is ever likely to pay for his kladkakka in Stockholm? Billions of these types of decisions are made every day by machine learning (ML) algorithms in banks.

The researchers took a small sample of tissue from Paul (his real name is not known because his identity was obscured in the trial). They divided the sample, which included both normal cells and cancer cells, into more than a hundred pieces and exposed them to various cocktails of drugs. Then, using robotic automation and computer vision (machine-learning models trained to identify small changes in cells), they watched to see what would happen. In effect, the researchers were doing what the doctors had done: trying different drugs to see what worked. But instead of putting a patient through multiple months-long courses of chemotherapy, they were testing dozens of treatments all at the same time.

TuringBots are AI-powered software that automatically supplements developers' work designing and building software code. It functions as an intelligent agent using advanced forms of machine learning to help auto-generate code, Hopkins said. Extended reality (XR) includes a combination of visual elements provided by tools like augmented, mixed and virtual reality. Though use cases are hard to pin down for enterprise businesses, Hopkins said in five years, use cases like training and onboarding for frontline workers could be viable opportunities. Web3 is a concept Hopkins said promises a decentralized internet by using technologies such as blockchain and cryptocurrency that's not dominated by big tech companies, financial institutions and other entities. But it's unclear how the technology will develop and benefit enterprises.

It was early one morning in 1996 when Andrew Hopkins, then a PhD biophysics student at Oxford University, had a brainwave as he walked home from a late-night lab meeting. He was trying to find molecules to fight HIV and to better understand drug resistance. "I remember this idea struck me that there must be a better way to do drug discovery other than the complex and expensive way everyone was following," he says. "Why couldn't we design an automated approach to drug design that would use all the information in parallel so that even a humble PhD student could create a medicine? That idea really stuck with me. I remember almost the exact moment to this day. And that was the genesis of the idea that eventually became Exscientia."

A man has told his story of going from living on a council estate to founding one of Britain's largest biotech companies which floated on New York's Nasdaq stock exchange for $2.9bn. The Welsh scientist's company - which uses artificial intelligence to cut the time and money being spent on discovering new drugs - has earned him a whopping €470 million, but he says he is nowhere near finished. Andrew Hopkins grew up on a council estate in the UK but described how he has since swapped that life for one in the prestigious city of Oxford after setting up his company, Exscientia. The 50-year-old founder retains 18.6 million shares, giving him a 15.8% stake of the company. On paper, he's worth around €470m since the flotation in October 2021, but in real life, Andrew, or Professor Hopkins as he's known in the field, is only just beginning.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. J.J. Watt has apparently found his team new: the Arizona Cardinals. Watt tweeted a picture of himself working out in a Cardinals shirt, signaling that he will join the team for the 2021 season. Watt agreed to a two-year deal worth $31 million, ESPN reported.