How nervous are investors about the stock market? Every week it seems US financial markets are hit by another bout of fear. The latest worries spread this week from the banking sector in the US, after two regional lenders warned they would be hit by losses from alleged fraud. But before that, markets swooned over signs of rekindled US-China tensions, as the two superpowers face off over tariffs, advanced technology and access to rare earths. The bankruptcies of car parts supplier First Brands and subprime car lender Tricolor acted as a trigger for nervous chatter in September.

U.S. military seized survivors after a drone strike on alleged drug smuggling boat in the Caribbean, marking first known survivors in President Donald Trump's anti-cartel campaign.

OpenAI has temporarily stopped its artificial intelligence (AI) app Sora creating deepfake videos portraying Dr Martin Luther King Jr, following a request from his estate. It said disrespectful content had been generated about the civil rights campaigner. Sora has become popular in the US for making hyper-realistic AI-generated videos, which has led to people sharing clips of deceased celebrities and historical figures in outlandish and often offensive scenarios. OpenAI said it would pause images of Dr King as it strengthens guardrails for historical figures - but it continues to allow people to make clips of others. The firm has faced controversy over this stance, as videos featuring notable figures such as President John F. Kennedy, Queen Elizabeth II and Professor Stephen Hawking have been shared widely online.

As the Group of 20 leaders gather in Cape Town, clean air features on the agenda as a standalone priority for the first time in the forum's history. The reality, however, is stark. Outdoor air pollution claims 5.7 million lives each year, and a report released last week highlights the lack of international development finance for clean air. Only $3.7bn was spent globally in 2023, representing barely 1 percent of aid, with only a fraction reaching Africa. As the minister chairing the G20's environment workstream this year, I am proud to have worked with member countries and international organisations to place air pollution firmly on the agenda.

Metropolis The Housing Market Is Already Terrible. A.I. Is Making It Even Worse. While digital staging is nothing new to real estate, bot-made listings are forcing homebuyers and professionals to ask themselves if this is a straight-up deceptive practice. DeAnn Wiley was on the hunt for a new rental in Detroit earlier this month when she had the displeasure of arriving at a property that looked nothing like what was advertised online. "The photos made the home look brand new, only to get there and see the usual wear and tear and the old'landlord special,' " she told Slate.

Can Ukraine restore its pre-war borders? Why are Tomahawk missiles for Ukraine a'red line' for Russia? Is Russia testing NATO with aerial incursions in Europe? Russian war correspondent Ivan Zuyev has been killed by a Ukrainian drone strike while on assignment on the front line of the war in southern Ukraine's Zaporizhia region, his publication, state news agency RIA said. Zuyev's colleague, Yuri Voitkevich, was seriously wounded in the attack.

Taylor Swift fans are driving a surge in popularity of a German museum exhibiting a portrait of the Shakespeare character Ophelia, recently reimagined in a song and music video from Swift's new album The Life of a Showgirl. The Hessische Landesmuseum in the central German city of Wiesbaden saw hundreds more visitors than usual over the weekend, as fans hoped to see the real version of the painting that opens the music video for The Fate of Ophelia. In the video, viewed more than 65 million times on Youtube, the painting comes alive, with Swift at its centre. We're really enjoying this attention - it's a lot of fun, museum spokesperson Susanne Hirschmann told the Associated Press. Hirschmann said that one family had travelled from the northern city of Hamburg, a five-hour drive away, while some of the visitors were Americans from an army base nearby.

China's biggest shopping event starts five weeks early to revive spending It's known to be China's biggest online shopping event - taking place on 11 November each year. But this year, Single's Day sales have already begun in mid-October, as part of efforts by Chinese retailers to boost spending in a sluggish market. China has been plagued with issues like growing youth unemployment, a prolonged property crisis, steep government debt and an ongoing trade war with the US - all of which is making the country's consumers cut back on spending. The Chinese government has been spending billions - through family subsidies, more wages and discounts for consumer goods in a bid to counter this, but retail sales growth is still failing to meet expectations. Originally created by Alibaba as a Chinese shopping festival, Singles' Day is akin to Amazon's Prime Day or Black Friday promotions elsewhere in the world.

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Simulation-based inference (SBI) is emerging as a new statistical paradigm for addressing complex scientific inference problems. By leveraging the representational power of deep neural networks, SBI can extract the most informative simulation features for the parameters of interest. Sequential SBI methods extend this approach by iteratively steering the simulation process towards the most relevant regions of parameter space. This is typically implemented through an algorithmic structure, in which simulation and network training alternate over multiple rounds. This strategy is particularly well suited for high-precision inference in high-dimensional settings, which are commonplace in physics applications with growing data volumes and increasing model fidelity. Here, we introduce dynamic SBI, which implements the core ideas of sequential methods in a round-free, asynchronous, and highly parallelisable manner. At its core is an adaptive dataset that is iteratively transformed during inference to resemble the target observation. Simulation and training proceed in parallel: trained networks are used both to filter out simulations incompatible with the data and to propose new, more promising ones. Compared to round-based sequential methods, this asynchronous structure can significantly reduce simulation costs and training overhead. We demonstrate that dynamic SBI achieves significant improvements in simulation and training efficiency while maintaining inference performance. We further validate our framework on two challenging astrophysical inference tasks: characterising the stochastic gravitational wave background and analysing strong gravitational lensing systems. Overall, this work presents a flexible and efficient new paradigm for sequential SBI.