The science of soulmates: Is there someone out there exactly right for you? On Valentine's Day, there's the temptation to believe that somewhere out there is The One: a soulmate, a perfect match, the person you were meant to be with. Across history, humans have always been drawn to the idea that love isn't random. In ancient Greece, Plato imagined that we were once whole beings with four arms, four legs and two faces, so radiant that Zeus split us in two; ever since, each half has roamed the earth searching for its missing other, a myth that gives the modern soulmate its poetic pedigree and the promise that somewhere, someone will finally make us feel complete. In the Middle Ages, troubadours and Arthurian tales recast that longing as courtly love, a fierce, often forbidden devotion like Lancelot's for Guinevere, in which a knight proved his worth through self-sacrifice for a beloved he might never openly declare.

This study explored how large language models (LLMs) perform in two areas related to art: writing critiques of artworks and reasoning about mental states (Theory of Mind, or ToM) in art-related situations. For the critique generation part, we built a system that combines Noel Carroll's evaluative framework with a broad selection of art criticism theories. The model was prompted to first write a full-length critique and then shorter, more coherent versions using a step-by-step prompting process. These AI-generated critiques were then compared with those written by human experts in a Turing test-style evaluation. In many cases, human subjects had difficulty telling which was which, and the results suggest that LLMs can produce critiques that are not only plausible in style but also rich in interpretation, as long as they are carefully guided. In the second part, we introduced new simple ToM tasks based on situations involving interpretation, emotion, and moral tension, which can appear in the context of art. These go beyond standard false-belief tests and allow for more complex, socially embedded forms of reasoning. We tested 41 recent LLMs and found that their performance varied across tasks and models. In particular, tasks that involved affective or ambiguous situations tended to reveal clearer differences. Taken together, these results help clarify how LLMs respond to complex interpretative challenges, revealing both their cognitive limitations and potential. While our findings do not directly contradict the so-called Generative AI Paradox--the idea that LLMs can produce expert-like output without genuine understanding--they suggest that, depending on how LLMs are instructed, such as through carefully designed prompts, these models may begin to show behaviors that resemble understanding more closely than we might assume.

How many atoms are there in the observable universe? Current estimates point to a number we would write as 1 followed by 80 zeroes, or 1080. If you peered inside each of these atoms and counted their subatomic particles, you could count a bit higher. But what happens beyond that? Take 1090 – even if you counted every atom and subatomic particle in the known universe, you wouldn't reach this number. In some sense, 1090 has no relation to physical reality.

'The Big Weekend Show' co-hosts discuss Tinder user traffic peaking during'Dating Sunday.' A judge has dismissed kidnapping and conspiracy charges filed against five Massachusetts college students accused of luring a man to their campus in a "Catch a Predator"-style scheme using a dating app. A Worcester District Court judge dismissed the charges against Kelsey Brainard, Isabella Trudeau, Joaquin Smith, Kevin Carroll and Easton Randall on Tuesday. The decision came after lawyers for the teenage Assumption University students claimed prosecutors lacked probable cause and filed motions to dismiss last month. Information regarding the status of a sixth student, charged as a juvenile, was not immediately available.

The North Slope of Alaska is dominated by small waterbodies that provide critical ecosystem services for local population and wildlife. Detailed information on the depth of the waterbodies is scarce due to the challenges with collecting such information. In this work we have trained a machine learning (Random Forest Regressor) model to predict depth from multispectral Landsat data in waterbodies across the North Slope of Alaska. The greatest challenge is the scarcity of in situ data, which is expensive and difficult to obtain, to train the model. We overcame this challenge by using modeled depth predictions from a prior study as synthetic training data to provide a more diverse training data pool for the Random Forest. The final Random Forest model was more robust than models trained directly on the in situ data and when applied to 208 Landsat 8 scenes from 2016 to 2018 yielded a map with an overall $r^{2}$ value of 0.76 on validation. The final map has been made available through the Oak Ridge National Laboratory Distribute Active Archive Center (ORNL-DAAC). This map represents a first of its kind regional assessment of waterbody depth with per pixel estimates of depth for the entire North Slope of Alaska.

Anti-vaccine activist Robert F. Kennedy Jr.'s presidential campaign hosted an online panel Wednesday on the future of AI moderated, for some reason, by Ian Carroll, a self-styled journalist with a history of antisemitic statements. In the course of the conversation, Kennedy admitted that he "gets manipulated by AI all the time." "Somebody will send me something and I'll go'Holy cow, did you see this?'," he said, describing how he credulously forwards fake content to his children, only for them to have to correct him. RFK Jr. said he regularly "gets manipulated by AI." While Carroll has no particular public profile on AI, his persona tracks with the campaign's focus on tech figures and influencers as it courts a young, male, and extremely online audience.

Remote sighted assistance (RSA) technology--which connects visually impaired individuals with human agents through a live video call on their smartphones--helps people with low or no vision navigate tasks that require sight. But what happens when existing computer vision technology doesn't fully support an agent in fulfilling certain requests, such as reading instructions on a medicine bottle or recognizing flight information on an airport's digital screen? According to researchers at the Penn State College of Information Sciences and Technology, there are some challenges that cannot be solved with existing computer vision techniques. Instead, the researchers posit that they would be better addressed by humans and AI working together to improve the technology and enhance the experience for both visually impaired users and the agents who support them. In a recent study presented at the 27th International Conference on Intelligent User Interfaces (IUI) in March, the researchers highlighted five emerging problems with RSA that they say warrant new development in human-AI collaboration.

When voice actor Heath Miller sits down in his boatshed-turned-home studio in Maine to record a new audiobook narration, he has already read the text through carefully at least once. To deliver his best performance, he takes notes on each character and any hints of how they should sound. Over the past two years, audiobook roles, like narrating popular fantasy series He Who Fights With Monsters, have become Miller's main source of work. But in December he briefly turned online detective after he saw a tweet from UK sci-fi author Jon Richter disclosing that his latest audiobook had no need for the kind of artistry Miller offers: It was narrated by a synthetic voice. Richter's book listing on Amazon's Audible credited that voice as "Nicholas Smith" without disclosing that it wasn't human. To Miller's surprise, he found that "Smith" voiced a total of around half a dozen on the site from multiple publishers--breaching Audible rules that say audiobooks "must be narrated by a human."

"We just know it's the right thing to do for our customers and--I say this from years of doing risk management-- it's good, basic risk management," says Shannon Carroll, director of global environmental sustainability at AT&T. "If all indications are that something is going to happen in the future, it's our responsibility to be prepared for that." Globally, leaders from government, business, and academia see the urgency. When citing risks with the highest impact, those surveyed listed climate action failure and other environmental risks second only to infectious diseases. AT&T is taking action with its Climate Resilience Project, using spatial data analysis and location information to tackle the complex problem of how increasingly powerful storms could affect infrastructure such as cell towers and the telecom's ability to deliver service to its customers. "Spatial analysis is this way of going beyond what we visually see," explains Lauren Bennett, head of spatial analysis and data science at Esri, a geographic information systems (GIS) company.

In the summer of 2009, the Israeli neuroscientist Henry Markram strode onto the TED stage in Oxford, England, and made an immodest proposal: Within a decade, he said, he and his colleagues would build a complete simulation of the human brain inside a supercomputer. They'd already spent years mapping the cells in the neocortex, the supposed seat of thought and perception. "It's a bit like going and cataloging a piece of the rain forest," Markram explained. "How many trees does it have? What shapes are the trees?"