'Every user has to make a choice of actually wanting to download Firefox and use it.' 'Every user has to make a choice of actually wanting to download Firefox and use it.' Do you need an assistant for your online activities? Multiple major players in artificial intelligence are moving on from chatbots like ChatGPT and are now focusing their efforts on new browsers with deep AI integrations. Those could take the form of an agent that shops for you or an omnipresent chatbot that follows you around and summarizes what you're seeing, looks up related stuff, or answers related questions.

Men with suspected prostate cancer will be able to get a diagnosis from the NHS within a day, under a new trial hailed as a potential game changer for identifying and treating the disease. The 15 hospitals taking part will use AI technology to interpret MRI scans and spot areas of abnormal tissue within minutes, according to NHS England. Scans showing a high-cancer risk will be triaged as priority review for a radiologist and patients will be booked for a same-day biopsy. Around one in eight men will develop prostate cancer in their lives, according to Prostate Cancer UK, with research showing it has overtaken breast cancer as the most commonly diagnosed form of the disease in the UK. But unlike breast cancer, there is currently no national screening programme for prostate cancer.

Amazon is planning major job cuts among its corporate workers as soon as this week, multiple media outlets have reported. The online retail giant plans to lay off as many as 30,000 employees as part of cost-cutting measures led by chief executive Andy Jassy, according to the Wall Street Journal and Reuters. Each cited sources stating the same number of layoffs. Amazon declined to comment when contacted by the BBC. If confirmed, the layoffs could be one of the largest seen in recent months.

Doctors are more like machines': my mother's worrying reliance on AI for health advice Tired of a two-day commute to see her overworked doctor, my mother turned to tech for help with her kidney disease. E very few months, my mother, a 57-year-old kidney transplant patient who lives in a small city in eastern China, embarks on a two-day journey to see her doctor. She fills her backpack with a change of clothes, a stack of medical reports and a few boiled eggs to snack on. Then, she takes a 90-minute ride on a high-speed train and checks into a hotel in the eastern metropolis of Hangzhou. At 7am the next day, she lines up with hundreds of others to get her blood taken in a long hospital hall that buzzes like a crowded marketplace. In the afternoon, when the lab results arrive, she makes her way to a specialist's clinic. She gets about three minutes with the doctor. Then, my mother packs up and starts the long commute home. My mother began using China's leading AI chatbot to diagnose her symptoms this past winter. She would lie down on her couch and open the app on her iPhone. "Hi," she said in her first message to the chatbot, on 2 February. How can I assist you today?" the system responded instantly, adding a smiley emoji.

Is London ready for driverless taxis? Autonomous cabs are a staple in some US cities - but how will they cope with London's streets? Will ghost taxis put a whole workforce out of a job? Will British passengers behave themselves without a human driver in the front seat - and can the technology really be trusted to keep people safe?

Ever since her death in 1986, it was taken as common knowledge that Elsa Lanchester - who became a horror movie icon by playing the title character in the Bride of Frankenstein - had been cremated and her ashes sprinkled in the ocean. But then Scott Michaels, the founder of Dearly Departed Tours, discovered that her cremated remains were interred in a rose garden under her married name, Elsa Lanchester Laughton. For almost 40 years no one had made the connection - until now, he says. Mr Michaels, 63, is a historian who specialises in the dark side of Hollywood. A go-to for programmes about dead Hollywood celebrities and murder, he has consulted for Quentin Tarantino's Manson murder film Once Upon a Time in Hollywood.

Turing AI Institute boss denies accusations of'toxic internal culture' The Alan Turing Institute Chair has told the BBC there is no substance to a number of serious accusations which rocked the organisation in the summer. In August, whistleblowers accused the charity's leadership of misusing public funds, overseeing a toxic internal culture, and failing to deliver on its mission. They said the Turing Institute, the UK's national body for artificial intelligence (AI), was on the brink of collapse after Peter Kyle, the then technology secretary, threatened to withdraw its £100m funding. But speaking exclusively to the BBC, Chair Dr Doug Gurr said the whistleblower claims were independently investigated by a third party which found them to have no substance. I fully sympathise that going through any transition is always challenging, he said.

These robots can clean, exercise - and care for your elderly parents. Would you trust them to? Hidden away in a lab in north-west London three black metal robotic hands move eerily on an engineering work bench. We're not trying to build Terminator, jokes Rich Walker, director of Shadow Robot, the firm that made them. Bespectacled, with long hair and a beard and moustache, he seems more like a latter-day hippy than a tech whizz, and he is clearly proud as he shows me around his firm.

Semi-supervised learning (SSL) aims to train a machine learning model using both labelled and unlabelled data. While the unlabelled data have been used in various ways to improve the prediction accuracy, the reason why unlabelled data could help is not fully understood. One interesting and promising direction is to understand SSL from a causal perspective. In light of the independent causal mechanisms principle, the unlabelled data can be helpful when the label causes the features but not vice versa. However, the causal relations between the features and labels can be complex in real world applications. In this paper, we propose a SSL framework that works with general causal models in which the variables have flexible causal relations. More specifically, we explore the causal graph structures and design corresponding causal generative models which can be learned with the help of unlabelled data. The learned causal generative model can generate synthetic labelled data for training a more accurate predictive model. We verify the effectiveness of our proposed method by empirical studies on both simulated and real data.

This work is a commentary of the article \href{https://doi.org/10.18716/ojs/phai/2025.2801}{AI Survival Stories: a Taxonomic Analysis of AI Existential Risk} by Cappelen, Goldstein, and Hawthorne. It is not just a commentary though, but a useful reminder of the philosophical limitations of \say{linear} models of risk. The article will focus on the model employed by the authors: first, I discuss some differences between standard Swiss Cheese models and this one. I then argue that in a situation of epistemic indifference the probability of P(D) is higher than what one might first suggest, given the structural relationships between layers. I then distinguish between risk and uncertainty, and argue that any estimation of P(D) is structurally affected by two kinds of uncertainty: option uncertainty and state-space uncertainty. Incorporating these dimensions of uncertainty into our qualitative discussion on AI existential risk can provide a better understanding of the likeliness of P(D).