Breakthroughs, discoveries, and DIY tips sent every weekday. Archaeopteryx represents a pivotal point in the grand evolutionary journey linking dinosaurs to their avian descendants. But paleontologists still have questions about the Jurassic era animal's anatomy and behavior roughly 165 years after its discovery. One of the most pressing lingering mysteries is how Archaeopteryx managed to fly above its fellow feathered dinosaur relatives. After more than two decades spent in a private collection, one of the most detailed and complete fossil sets arrived at the Chicago's Field Museum in 2022.

Microsoft quietly announced earlier this week that it plans to shut down a longstanding tool supplying search engine startups and other software developers with a raw feed of Bing search results. The Bing Search APIs, or application programming interfaces, were once vital to many niche Google alternatives, but fell out of favor more recently as Microsoft hiked fees for the service and restricted its use. The shutoff, which is scheduled to begin on August 11, still came as a surprise to several developers who spoke with WIRED. Customers learned of it on Monday via an email from Microsoft and a post on its website. They were directed to consider using "Grounding with Bing Search as part of Azure AI Agents," a Microsoft service that allows chatbots like ChatGPT to augment AI-generated responses with "real-time public web data."

Since the release and viral success of ChatGPT in late 2022, generative AI has been integrated into an ever-expanding number of tech platforms and gadgets. As is often the case with powerful new technologies, generative AI's growth has outpaced our ability to build frameworks for safe and responsible use. Teachers, for example, must now contend with the fact that many (if not all) of their students are using generative AI tools like ChatGPT and Gemini to complete assignments. The long-term implications of this sudden surge for the education system remain to be seen. Similarly, business leaders now face the challenge of managing a generative AI-powered workforce and ensuring that the technology facilitates, rather than hinders, employee performance.

We consider learning Nash equilibria in two-player zero-sum Markov Games with nonlinear function approximation, where the action-value function is approximated by a function in a Reproducing Kernel Hilbert Space (RKHS). The key challenge is how to do exploration in the high-dimensional function space. We propose a novel online learning algorithm to find a Nash equilibrium by minimizing the duality gap. At the core of our algorithms are upper and lower confidence bounds that are derived based on the principle of optimism in the face of uncertainty. We prove that our algorithm is able to attain an O(\sqrt{T}) regret with polynomial computational complexity, under very mild assumptions on the reward function and the underlying dynamic of the Markov Games.

Active learning methods have shown great promise in reducing the number of samples necessary for learning. As automated learning systems are adopted into real-time, real-world decision-making pipelines, it is increasingly important that such algorithms are designed with safety in mind. In this work we investigate the complexity of learning the best safe decision in interactive environments. We reduce this problem to a safe linear bandits problem, where our goal is to find the best arm satisfying certain (unknown) safety constraints. We propose an adaptive experimental design-based algorithm, which we show efficiently trades off between the difficulty of showing an arm is unsafe vs suboptimal.

Barbie is one of the most successful children's toys in history, spawning a multimedia franchise that includes merchandise, video games and a live-action film. Since US toy giant Mattel launched the original Barbie in 1959, more than 1 billion of the dolls have been sold worldwide. Certainly, Barbie's looks have been tweaked over the years to reflect changing beauty ideals and societal shifts. But according to a new study, one subtle change to Barbie has gone largely unnoticed – until now. Scientists in Australia have found that Barbies today have flatter feet than they did in past decades.

A confession: This dispatch will not be coming to you from one of the long-devout Martha Wells faithful. I'm a convert, a curious reader who turned to Wells' The Murderbot Diaries series after reading my colleague Meghan Herbst's fantastic 2024 profile of the author, which left me questioning who would be challenged with taking on the series' title character in Apple TV's adaptation and why it was Alexander Skarsgård. Put differently, I wanted to know if the actor known for playing blood-sucker Eric Northman in True Blood and a berserker prince in The Northman would be the right fit to play a security robot, or SecUnit, struggling with social awkwardness after hacking his own "governor module" to give himself the freedom to not obey human orders. If the weird affection he forms for the scientists he's charged with protecting, and the stunted way he goes about showing it, would translate to Murderbot. After watching the first episodes of the show, which debuts Friday on Apple TV, I got my answers--and found myself asking a lot more questions.

Artificial intelligence can spontaneously develop human-like social conventions, a study has found. The research, undertaken in collaboration between City St George's, University of London and the IT University of Copenhagen, suggests that when large language model (LLM) AI agents such as ChatGPT communicate in groups without outside involvement they can begin to adopt linguistic forms and social norms the same way that humans do when they socialise. The study's lead author, Ariel Flint Ashery, a doctoral researcher at City St George's, said the group's work went against the majority of research done into AI, as it treated AI as a social rather than solitary entity. "Most research so far has treated LLMs in isolation but real-world AI systems will increasingly involve many interacting agents," said Ashery. "We wanted to know: can these models coordinate their behaviour by forming conventions, the building blocks of a society? The answer is yes, and what they do together can't be reduced to what they do alone."

The UK government's proposed AI-powered crime prediction tool, designed to flag individuals deemed "high risk" for future violence based on personal data like mental health history and addiction, marks a provocative new frontier. Elsewhere, Argentina's new Artifical Intelligence Unit for Security intends to use machine learning for crime prediction and real-time surveillance. And in some US cities, AI facial recognition is paired with street surveillance to track suspects. The promise of anticipating violence Minority Report-style is compelling.

Feedback is New Scientist's popular sideways look at the latest science and technology news. You can submit items you believe may amuse readers to Feedback by emailing feedback@newscientist.com Saturday 17 May will see the final of this year's Eurovision Song Contest, which will be the most over-the-top evening of television since, well, the previous Eurovision. Feedback is deeply relieved that Feedback Jr appears not to be interested this year, so we might escape having to sit up and watch the entire thing. While we are deeply supportive of the contest's kind and welcoming vibe, most of the songs make our ears bleed.