With the development of Large Language Models (LLMs) in consulting, their role in moral decision-making has become prominent. However, existing research predominantly consider AI as an independent "moral agent" adhering to the "Human-AI Alignment" paradigm. In this study, we propose that AI should serve as a "moral assistant", facilitating users' moral growth through the "Art of Midwifery" rather than substituting human judgment. We endow LLMs with distinct persona archetypes and conducted dialogues across six moral scenarios. Findings reveal that while the virtue exemplar excelled overall, optimal performance was context-dependent: the Guardian Angel excelled in bioethical crises for emotional support, whereas the Socratic persona better elicited reflection in existential dilemmas. We introduce "Constructive Divergence", arguing that AI should offer alternative perspectives at critical moment rather than blindly accommodate users, transcending traditional alignment paradigms.
Every day, 800 women and 6,700 newborns die from complications related to pregnancy or childbirth. A well-trained midwife can prevent most of these maternal and newborn deaths. Data science models together with logs generated by users of online learning applications for midwives can help to improve their learning competencies. The goal is to use these rich behavioral data to push digital learning towards personalized content and to provide an adaptive learning journey. In this work, we evaluate various forecasting methods to determine the interest of future users on the different kind of contents available in the app, broken down by profession and region.
Maternal and newborn mortality remain among the highest in sub-Saharan Africa, where midwifery care is often delivered by nurses who lack midwifery training to international standards, and consulting authoritative guidance at the point of care is hard: the guidelines are long and connectivity is intermittent. We present MAM-AI, a medical question-answering assistant for nurse-midwives in Zanzibar that runs entirely on a commodity Android device: a question is embedded (EmbeddingGemma, 300M) and matched against a curated corpus of 87 guideline documents (63,650 passages), then answered with citations by a 4B int4 generator (Gemma 4 E4B), fully offline, with no query leaving the device. We evaluate the exact deployed configuration with a layered methodology -- retriever, generator under oracle context, end-to-end, and latency -- scored by LLM judges validated against physician rubrics. The evaluation relocates the hard problem. On-device retrieval is essentially solved: the 300M embedder ranks third of seven retrievers and rivals cloud systems, so the passages the system needs are usually found. The small generator is what remains in doubt: adding retrieved context does not improve i
The automation of scientific discovery has reached an inflection point. While AI systems now operate instruments, optimize parameters and generate hypotheses, most remain procedural: they execute workflows fixed by human designers. True autonomous science demands epistemic autonomy--the capacity to construct, challenge and revise physical explanations in response to evidence. Here we introduce AHOIS, a multi-agent AI scientist that embeds Socratic midwifery into closed-loop experimentation. A physics-critic agent interrogates hypotheses through causal questioning, constraint checking, counterexample generation and falsification-criteria formulation. We evaluate AHOIS on a real multimode-fibre optical platform, a high-dimensional system with complex wave transformations, indirect detection, environmental drift and multi-modal acquisition. Without prior encoding schemes, classifiers or speckle models, the system autonomously proposed and validated a random-interference encoding hypothesis, discovered task-adaptive sparse-measurement strategies, diagnosed distinct failure modes (encoding instability, fluorescence contamination and detector noise) and translated a published imaging pro
The requirements for real-world manipulation tasks are diverse and often conflicting; some tasks require precise motion while others require force compliance; some tasks require avoidance of certain regions, while others require convergence to certain states. Satisfying these varied requirements with a fixed state-action representation and control strategy is challenging, impeding the development of a universal robotic foundation model. In this work, we propose Meta-Control, the first LLM-enabled automatic control synthesis approach that creates customized state representations and control strategies tailored to specific tasks. Our core insight is that a meta-control system can be built to automate the thought process that human experts use to design control systems. Specifically, human experts heavily use a model-based, hierarchical (from abstract to concrete) thought model, then compose various dynamic models and controllers together to form a control system. Meta-Control mimics the thought model and harnesses LLM's extensive control knowledge with Socrates' "art of midwifery" to automate the thought process. Meta-Control stands out for its fully model-based nature, allowing rigo
NASA’s Curiosity rover has entered a Martian valley covered by an astonishing “sea” of tiny polygon-shaped fractures。 The honeycomb patterns, each only a few inches wide, stretch across the landscape and even wrap around a nearby 20-foot-tall butte
Mathematicians have shown that no electoral system can perfectly balance local representation, proportional national results, and a fixed-size parliament once enough parties compete。 A newly proposed voting method could soften these unavoidable trade-offs and produce outcomes that are much closer to fair
Hundreds of Homeland Security drones retasked to survey wildlife and livestock
Metal-rich asteroids could one day become hardware stores for Mars, supplying the materials needed to build and repair a growing colony。 A new analysis shows that carefully selected asteroids may be reachable with current spacecraft technology。 Some could even provide the ingredients for making rocket fuel in space, dramatically reducing the burden
NASA engineers have found a clever way to squeeze more life out of Voyager 2, nearly half a century after it left Earth。 In an operation nicknamed the “Big Bang,” the team simultaneously shut down certain power-hungry hardware and switched to lower-power alternatives while keeping the spacecraft warm enough to survive
Scientists have discovered incredibly tiny plasma whirlpools swirling across the Sun’s surface, some just 20 kilometers wide。 These previously invisible vortices may twist magnetic fields and help build up the energy released in small solar eruptions called nanoflares。 They may also help magnetic fields spread through the Sun’s atmosphere far faste
AI firms quietly bulk buying rare books face resistance from booksellers
A black hole observed during a dramatic 2023 eruption did not simply devour gas from its nearby companion star。 It also expelled large amounts of material through powerful jets and winds, even after the outburst had nearly faded。 The results suggest black holes may continue reshaping their surroundings long after their brightest fireworks end
Scientists have created the first quantum material that can sort and transport different quantum states of light at room temperature, potentially removing the need for bulky, ultra-cold refrigeration systems。 Built from a gold film carved with hundreds of microscopic structures, the ultrathin “metacrystal” acts like a filter that directs different
Photons traveling through a cloud of atoms can emerge so early that they appear to have spent a negative amount of time inside。 Researchers tested whether this was merely a misleading feature of the light pulse by making extremely weak measurements of the atoms。 Surprisingly, the atoms confirmed the same negative dwell time
A ten-month Antarctic experiment found that astronauts may struggle not only with loneliness but also with spending too much time around the same people。 Frequent contact was linked to greater tension and mistrust, while the crew increasingly divided into cultural and language-based groups
A person’s sleeping brain may reveal warning signs of dementia long before memory problems begin。 Researchers used machine learning to analyze EEG recordings from about 7,000 adults and found that an older-than-expected “brain age” was tied to a sharply higher dementia risk。 Every additional 10 years of brain aging raised that risk by nearly 40%