Plus: Google's new image generator has extremely loose guardrails We're learning more about what vitamin D does to our bodies At a checkup a few years ago, a doctor told me I was deficient in vitamin D. But he wouldn't write me a prescription for supplements, simply because, as he put it, everyone in the UK is deficient. Putting the entire population on vitamin D supplements would be too expensive for the country's national health service, he told me. But supplementation--whether covered by a health-care provider or not--can be important. As those of us living in the Northern Hemisphere spend fewer of our waking hours in sunlight, let's consider the importance of vitamin D. Read the full story . This article first appeared in The Checkup, MIT Technology Review's weekly biotech newsletter. Here's why we don't have a cold vaccine.

Nyalleng Moorosi is part of a movement aimed at involving more African voices in AI policymaking. The room is draped in white curtains, and a giant screen blinks with videos created with generative AI. A classic East African folk song by the Tanzanian singer Saida Karoli plays loudly on the speakers. Friends greet each other as waiters serve arrowroot crisps and sugary mocktails. A man and a woman wearing leopard skins atop their clothes sip beer and chat; many women are in handwoven Ethiopian garb with red, yellow, and green embroidery. "The best thing about the Indaba is always the parties," computer scientist Nyalleng Moorosi tells me.

We consider the fundamental benchmarking problem of gathering in an $(N,f)$-fault system consisting of $N$ robots, of which at most $f$ might fail at any execution, under asynchrony. Two seminal results established impossibility of a solution in the oblivious robot (OBLOT) model in a $(2,0)$-fault system under semi-synchrony and in a $(3,1)$-Byzantine fault system under asynchrony. Recently, a breakthrough result circumvented the first impossibility result by giving a deterministic algorithm in a $(2,0)$-fault system under asynchrony in the luminous robot (LUMI) model using 2-colored lights. However, a breakthrough result established impossibility of gathering in a $(2,1)$-crash system in the LUMI model under semi-synchrony. In this paper, we consider a {\em mobility fault} model in which a robot crash only impacts it mobility but not the operation of the light. We establish four results under asynchrony in LUMI with the mobility fault model. We show that it is impossible to solve gathering in a $(2,1)$-mobility fault system using 2-colored lights, and then give a solution using 3-colored lights, which is optimal w.r.t. the number of colors. We then consider an $(N,f)$-mobility fault system, $f

Collectible card games (CCGs) are a difficult genre for AI due to their partial observability, long-term decision-making, and evolving card sets. Due to this, current AI models perform vastly worse than human players at CCG tasks such as deckbuilding and gameplay. In this work, we introduce UrzaGPT, a domain-adapted large language model that recommends real-time drafting decisions in Magic: The Gathering. Starting from an open-weight LLM, we use Low-Rank Adaptation fine-tuning on a dataset of annotated draft logs. With this, we leverage the language modeling capabilities of LLM, and can quickly adapt to different expansions of the game. We benchmark UrzaGPT in comparison to zero-shot LLMs and the state-of-the-art domain-specific model. Untuned, small LLMs like Llama-3-8B are completely unable to draft, but the larger GPT-4o achieves a zero-shot performance of 43%. Using UrzaGPT to fine-tune smaller models, we achieve an accuracy of 66.2% using only 10,000 steps. Despite this not reaching the capability of domain-specific models, we show that solely using LLMs to draft is possible and conclude that using LLMs can enable performant, general, and update-friendly drafting AIs in the future.

In 2002, artificial intelligence was still in winter. Despite decades of effort, dreams of bestowing computers with human-like cognition and real-world understanding had not materialized. To look for a way forward, a small group of scientists gathered for "The St. Thomas Common Sense Symposium." AI pioneer Marvin Minsky was the central presence, along with his protégé Pushpinder Singh. After the symposium, Minsky, Singh, and renowned philosopher Aaron Sloman published a paper on the group's ideas for how to reach human-like AI.

Donald Trump joined big oil and technology bosses on Tuesday at a major artificial intelligence and energy summit in Pittsburgh, outraging environmentalists and community organizations. The event came weeks after the passage of a mega-bill that experts say could stymy AI growth with its attacks on renewable energy. "We're here today because we believe that America's destiny is to dominate every industry and be the first in every technology, and that includes being the world's number one superpower in artificial intelligence," said Trump. The inaugural Pennsylvania energy and innovation summit, held at Carnegie Mellon University, is an attempt to position the state as an AI leader, showcasing the technological innovation being developed in the city and the widespread availability of fossil fuel reserves to power them. At the gathering, Trump announced 70bn in AI and energy investments for the state, Axios first reported, in a move the event's host, the Republican Pennsylvania senator, Dave McCormick, says will be a boon to local economies.

Interactive recommendation is a typical information-seeking task that allows users to interactively express their needs through natural language and obtain personalized recommendations. Large language model-powered (LLM-powered) agents have become a new paradigm in interactive recommendations, effectively capturing users' real-time needs and enhancing personalized experiences. However, due to limited planning and generalization capabilities, existing formulations of LLM-powered interactive recommender agents struggle to effectively address diverse and complex user intents, such as intuitive, unrefined, or occasionally ambiguous requests. To tackle this challenge, we propose a novel thought-augmented interactive recommender agent system (TAIRA) that addresses complex user intents through distilled thought patterns. Specifically, TAIRA is designed as an LLM-powered multi-agent system featuring a manager agent that orchestrates recommendation tasks by decomposing user needs and planning subtasks, with its planning capacity strengthened through Thought Pattern Distillation (TPD), a thought-augmentation method that extracts high-level thoughts from the agent's and human experts' experiences. Moreover, we designed a set of user simulation schemes to generate personalized queries of different difficulties and evaluate the recommendations based on specific datasets. Through comprehensive experiments conducted across multiple datasets, TAIRA exhibits significantly enhanced performance compared to existing methods. Notably, TAIRA shows a greater advantage on more challenging tasks while generalizing effectively on novel tasks, further validating its superiority in managing complex user intents within interactive recommendation systems. The code is publicly available at:https://github.com/Alcein/TAIRA.

Beneath this caution lingers a fundamental question about whether these annual gatherings are still worth it, given Mr Trump's clear disdain. He prefers bilateral dealmaking to multilateral consensus-building. This is the president's first such foray onto the world stage since his inauguration and his six partners will be looking anxiously to see whether he wants to pick a fight - or look statesmanlike - for voters back home. Max Bergmann, director of the Europe, Russia and Eurasia Program at the Center for Strategic and International Studies, said: "The question now is not so much'is this an awkward family gathering?' I think the question is: 'is this still a family?'"

"Greetings, Lovers, Legends, and Gods of Desire!" read the Partiful invite for the pre-Valentine's Day gathering. On this night, we will surrender to his playful whims." Then, sternly and in all caps: "YOU MUST BE PRE-APPROVED TO GET IN." A couple of days later, a text blast came in; the planners of this in-person dating meetup for singles were budgeting for 200 attendees, but more than 1,000 people applied, so there'd be a venue change. RSVPs closed at 3 pm sharp the day of the event. Then, at night, Barbarossa Lounge in San Francisco's Financial District welcomed the lucky guests who managed to get their names on the list. The event, Love in the Stars, was hosted by local event promoter Spice King and the online platform Paloma, which describes itself as a dating-oriented members club. Per the invitation's instructions, attendees dressed to signal their status; the singles wore a dash of red to make themselves identifiable as the ones looking for love. Their non-single supporters wore a splash of white or gold to signal they were already spoken for. Within an hour, there was no room to move. Small talk and awkward flirting filled every inch of the dark bar, with the question "So, do you like working in tech?" bouncing around at the same tempo as the clubby beats. Welcome to Silicon Valley's in-person dating scene. These regular events are only accessible to those already in the know. They feature pre-vetted guest lists; invite-only gatherings at villas in Hillsborough, one of the wealthiest towns in California; WhatsApp groups that gather monthly in apartments around town; and private parties with secret locations promising Stanford alumni and "creatives" in attendance. In an area that's notoriously tough on daters, at a time when dating app fatigue is at an all-time high, the appetite for ways to find love face-to-face is growing into a frenzy. "We have all collectively realized that dating apps are the worst," says Allie Hoffman, the founder of the two-year-old organization The Feels, a nationwide in-person dating event series with a strong presence in San Francisco. "There is no intention around how depleting, bot-y, ghosty, breadcrumb-y, gaslight-y and fishy they are.

For some years now, China's annual gathering of its national legislature had been an increasingly disciplined and choreographed affair -- its muted vibes practically an echo of deepening concern about domestic stagnation. The National People's Congress seven-day gathering, which concludes Tuesday in Beijing, came on the heels of a breakthrough in artificial intelligence by China's home-grown startup DeepSeek that's fired up investors, politicians and even regulators. It also followed Chinese President Xi Jinping's high-profile meeting with business chiefs including Jack Ma.