Mayor Zohran Mamdani framed New York City's sanctuary status in religious terms at interfaith breakfast, invoking Bible, Quran, and Bhagavad Gita before 400 faith leaders.

Breakthroughs, discoveries, and DIY tips sent every weekday. Making new friends (especially as an adult) can be challenging. When new birds are introduced to a group, monk parakeets will "test the waters" to avoid getting injured by defensive strangers. The parakeets will gradually approach the new bird, taking some time to get familiar before ramping up to more risky or vulnerable interactions that are needed to form the bonds necessary for survival. "There can be a lot of benefits to being social, but these friendships have to start somewhere," said Claire O'Connell, a study co-author and a doctoral student in the University of Cincinnati, said in a statement .

This is a story about a classroom. The kids in the classroom are all waiting in line to get a snack from their teacher. What are the kids having for snack?

Tinglesbar incorporates ASMR into elementary school and doctor's visits simulations, offering a social haven for introverts. "It's time for your lice check," a woman who goes by "Ms. K" whispers directly into my ear as she starts running her fingers into my scalp and through each strand of hair. I'm in a dark room, Eastern flute music playing in the background as I sit across from my partner who's also having his hair caressed by a stranger. We close our eyes so we don't burst out laughing.

Community detection is one of the fundamental problems in data science which consists of partitioning nodes into disjoint communities. We present a game-theoretic perspective on the Constant Potts Model (CPM) for partitioning networks into disjoint communities, emphasizing its efficiency, robustness, and accuracy. Efficiency: We reinterpret CPM as a potential hedonic game by decomposing its global Hamiltonian into local utility functions, where the local utility gain of each agent matches the corresponding increase in global utility. Leveraging this equivalence, we prove that local optimization of the CPM objective via better-response dynamics converges in pseudo-polynomial time to an equilibrium partition. Robustness: We introduce and relate two stability criteria: a strict criterion based on a novel notion of robustness, requiring nodes to simultaneously maximize neighbors and minimize non-neighbors within communities, and a relaxed utility function based on a weighted sum of these objectives, controlled by a resolution parameter. Accuracy: In community tracking scenarios, where initial partitions are used to bootstrap the Leiden algorithm with partial ground-truth information, our experiments reveal that robust partitions yield higher accuracy in recovering ground-truth communities.

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.

Breakthroughs, discoveries, and DIY tips sent every weekday. When the brain releases oxytocin during sex, childbirth, breastfeeding, and social interactions, the hormone supports strong feelings such as attachment, trust, and closeness. That's why oxytocin is frequently nicknamed the love, cuddle, or happy hormone--even though it's also linked with aggression. To continue investigating the biological role of oxytocin, a team of researchers studied it with scientist's poster species for love and friendship, the prairie vole (Microtus ochrogaster). The small rodents found throughout central North America have bonds that are "similar to human friendships in the sense that they are selective and long-lasting. Voles form strong, stable bonds with specific peers," Markita Landry, a chemist from the University of California (UC), Berkeley, tells Popular Science.

Traditional AI safety evaluations on isolated LLMs are insufficient as multi-agent AI ensembles become prevalent, introducing novel emergent risks. This paper introduces the Multi-Agent Emergent Behavior Evaluation (MAEBE) framework to systematically assess such risks. Using MAEBE with the Greatest Good Benchmark (and a novel double-inversion question technique), we demonstrate that: (1) LLM moral preferences, particularly for Instrumental Harm, are surprisingly brittle and shift significantly with question framing, both in single agents and ensembles. (2) The moral reasoning of LLM ensembles is not directly predictable from isolated agent behavior due to emergent group dynamics. (3) Specifically, ensembles exhibit phenomena like peer pressure influencing convergence, even when guided by a supervisor, highlighting distinct safety and alignment challenges. Our findings underscore the necessity of evaluating AI systems in their interactive, multi-agent contexts.

Self-disclosure, the sharing of one's thoughts and feelings, is affected by the perceived relationship between individuals. While chatbots are increasingly used for self-disclosure, the impact of a chatbot's framing on users' self-disclosure remains under-explored. We investigated how a chatbot's description of its relationship with users, particularly in terms of ephemerality, affects self-disclosure. Specifically, we compared a Familiar chatbot, presenting itself as a companion remembering past interactions, with a Stranger chatbot, presenting itself as a new, unacquainted entity in each conversation. In a mixed factorial design, participants engaged with either the Familiar or Stranger chatbot in two sessions across two days, with one conversation focusing on Emotional- and another Factual-disclosure. When Emotional-disclosure was sought in the first chatting session, Stranger-condition participants felt more comfortable self-disclosing. However, when Factual-disclosure was sought first, these differences were replaced by more enjoyment among Familiar-condition participants. Qualitative findings showed Stranger afforded anonymity and reduced judgement, whereas Familiar sometimes felt intrusive unless rapport was built via low-risk Factual-disclosure.