An airline's boarding policy shake-up shows the limits of efficiency. Boarding a Southwest flight is no longer first come, first served. What is the best way to cram people into a tin can in the sky? For five decades, Dallas-based budget airline Southwest made its reputation on its unique open seating policy. Savvy passengers who checked in early got to board early, too, lining up at distinctive silver stanchions to claim first dibs on whichever seat they preferred.

Elon Musk has suggested he could buy Ryanair and called for its chief executive to be fired amid a deepening spat between the pair. The budget airline on Tuesday branded the Tesla chief executive an idiot, and used the extraordinary row to promote its January sale. Musk and Ryanair boss Michael O'Leary have been trading insults over the past week after O'Leary rejected the idea of using Musk's Starlink technology to provide wi-fi on flights. The two are among the world's most outspoken business chiefs, with Musk the world's richest man with an estimated net worth of $769bn (£573bn), and O'Leary running Europe's busiest airline. A statement on Ryanair's X account on Tuesday evening said: Perhaps Musk needs a break?? Ryanair is launching a Great Idiots seat sale especially for Elon and any other idiots on'X'.

How can one publish a dataset with sensitive attributes in a way that both preserves privacy and enables joins with other datasets on those same sensitive attributes? This problem arises in many contexts, e.g., a hospital and an airline may want to jointly determine whether people who take long-haul flights are more likely to catch respiratory infections. If they join their data by a common keyed user identifier such as email address, they can determine the answer, though it breaks privacy. This paper shows how the hospital can generate a private sketch and how the airline can privately join with the hospital's sketch by email address. The proposed solution satisfies pure differential privacy and gives approximate answers to linear queries and optimization problems over those joins. Whereas prior work such as secure function evaluation requires sender/receiver interaction, a distinguishing characteristic of the proposed approach is that it is non-interactive. Consequently, the sketch can be published to a repository for any organization to join with, facilitating data discovery. The accuracy of the method is demonstrated through both theoretical analysis and extensive empirical evidence.

Thousands of Airbus planes are being returned to normal service after being grounded for hours due to a warning that solar radiation could interfere with onboard flight control computers. The aerospace giant - based in France - said around 6,000 of its A320 planes had been affected with most requiring a quick software update. Some 900 older planes need a replacement computer. French Transport Minister Philippe Tabarot said the updates went very smoothly for more than 5,000 planes. Fewer than 100 aircraft still needed the update, Airbus had told him, according to local media.

The US government is aiming to ease the pressure on air traffic controllers suffering shutdown-related woes by curtailing flights. But airlines have experience with this kind of sudden disruption. Newark Liberty International Airport is one of the high-traffic airports that could see flight cuts starting Friday. The US Federal Aviation Administration plans to cut 10 percent of flights in 40 high-traffic airports on Friday morning if Congress fails to reopen the federal government by then, Transportation secretary Sean Duffy and FAA chief Bryan Bedford said Wednesday. The announcement came days after the US agency said it faced widespread shortages of air traffic controllers in half of the country's 30 busiest airports and hours-long security lines caused by absences of Transportation Security Administration agents.

Goal changes are a defining feature of real world multi-turn interactions, yet current agent benchmarks primarily evaluate static objectives or one-shot tool use. We introduce AgentChangeBench, a benchmark explicitly designed to measure how tool augmented language model agents adapt to mid dialogue goal shifts across three enterprise domains. Our framework formalizes evaluation through four complementary metrics: Task Success Rate (TSR) for effectiveness, Tool Use Efficiency (TUE) for reliability, Tool Call Redundancy Rate (TCRR) for wasted effort, and Goal-Shift Recovery Time (GSRT) for adaptation latency. AgentChangeBench comprises 2,835 task sequences and five user personas, each designed to trigger realistic shift points in ongoing workflows. Using this setup, we evaluate several frontier models and uncover sharp contrasts obscured by traditional $\text{pass}@k$ scores: for example, GPT-4o reaches $92.2\%$ recovery on airline booking shifts while Gemini collapses to $48.6\%$, and retail tasks show near perfect parameter validity yet redundancy rates above $80\%$, revealing major inefficiencies. These findings demonstrate that high raw accuracy does not imply robustness under dynamic goals, and that explicit measurement of recovery time and redundancy is essential. AgentChangeBench establishes a reproducible testbed for diagnosing and improving agent resilience in realistic enterprise settings.

Recent advancements in tool-augmented large language models have enabled them to interact with external tools, enhancing their ability to perform complex user tasks. However, existing approaches overlook the role of personalisation in guiding tool use. This work investigates how user preferences can be effectively integrated into goal-oriented dialogue agents. Through extensive analysis, we identify key weaknesses in the ability of LLMs to personalise tool use. To this end, we introduce TAPS, a novel solution that enhances personalised tool use by leveraging a structured tagging tool and an uncertainty-based tool detector. TAPS significantly improves the ability of LLMs to incorporate user preferences, achieving the new state-of-the-art for open source models on the NLSI task.

A yellow suitcase draws me in like a beacon. It is stacked on a dark shelf at the back of Greasby's auction house in Tooting, south London, and looks brand new, with a hard exterior and wheels that Richard Stacey, a Greasby's regular who is dressed in shorts, a plaid shirt and a cream bucket hat, tells me to test. So I test them – and they work. If I was just buying a bag, that is all I would need to know. But this isn't just a bag: the zip is locked and when I lift it, it is heavy.

United States Transportation Secretary Sean Duffy says there are concerns about the use of artificial intelligence to set personalised airline prices, echoing red flags brought up by three Democratic senators. Duffy on Tuesday promised to investigate any airline that uses the technology to set prices. "To try to individualise pricing on seats based on how much you make or don't make or who you are, I can guarantee you that we will investigate if anyone does that," Duffy said. "We would engage very strongly if any company tries to use AI to individually price their seating." Duffy noted Delta clarified that it would not use AI for pricing individual tickets, "and I'll take them at face value."