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Chatbot connections: New study reveals the truth about AI boyfriends

Advances in AI technology have ushered in a new era of digital romance, where people are forming intimate emotional connections with chatbots. For many, these AI companions are a crucial lifeline, helping to combat feelings of loneliness. Yet, despite a rapidly evolving social trend that has attracted widespread interest, it has been largely understudied by researchers.

A new analysis of the popular Reddit community, r/MyBoyfriendIsAI, is addressing the gap by providing the first in-depth insights into how intimate human–AI relationships begin, evolve and affect users.

Researchers from the Massachusetts Institute of Technology (MIT) studied 1,506 of the most popular posts from this Reddit community, which has more than 27,000 members. First, they used AI tools to read all the conversations and sorted them into six main themes, such as coping with loss. Then they used custom-built AI classifiers to review the posts again and measure specific details within them.

Proven quantum advantage: Researchers cut the time for a learning task from 20 million years to 15 minutes

Amid high expectations for quantum technology, a new paper in Science reports a proven quantum advantage. In an experiment, entangled light has allowed researchers to learn a system’s noise with very few measurements.

Researchers at the Technical University of Denmark (DTU) and international partners have demonstrated that entangled light can cut the number of measurements needed to learn the behavior of a complex, noisy quantum system by an enormous factor.

“This is the first proven quantum advantage for a photonic system,” says corresponding author Ulrik Lund Andersen, a professor at DTU Physics. “Knowing that such an advantage is possible with a straightforward optical setup should help others look for areas where this approach would pay off, such as sensing and machine learning.”

Unofficial Postmark MCP npm silently stole users’ emails

A npm package copying the official ‘postmark-mcp’ project on GitHub turned bad with the latest update that added a single line of code to exfiltrate all its users’ email communication.

Published by a legitimate-looking developer, the malicious package was a perfect replica of the authentic one in terms of code and description, appearing as an official port on npm for 15 iterations.

Model Context Protocol (MCP) is an open standard that allows AI assistants to interface with external tools, APIs, and databases in a structured, predefined, and secure manner.

AI system learns from many types of scientific information and runs experiments to discover new materials

Materials science experiments can also face reproducibility challenges. To address the problem, CRESt monitors its experiments with cameras, looking for potential problems and suggesting solutions via text and voice to human researchers.

The researchers used CRESt to develop an electrode material for an advanced type of high-density fuel cell known as a direct formate fuel cell. After exploring more than 900 chemistries over three months, CRESt discovered a catalyst material made from eight elements that achieved a 9.3-fold improvement in power density per dollar over pure palladium, an expensive precious metal. In further tests, CRESTs material was used to deliver a record power density to a working direct formate fuel cell even though the cell contained just one-fourth of the precious metals of previous devices.

The results show the potential for CRESt to find solutions to real-world energy problems that have plagued the materials science and engineering community for decades.

AI can now pass the hardest level of the CFA exam in a matter of minutes

Several artificial intelligence models are now advanced enough to pass the three-part chartered financial analyst exam, even the most difficult Level III test.

Previous research, particularly from two years ago, had found AI could clear Levels I and II of the exam, but it struggled with Level III, due to the essay questions.

The new study was developed by researchers from New York University Stern School of Business and Goodfin, an AI-powered wealth-management platform.


For humans to pass the prestigious, three-part chartered financial analyst exam, it typically takes around 1,000 hours of studying over the course of several years. New research found that the technology underpinning a slew of artificial intelligence models is now advanced enough to pass even the most difficult – Level III – mock exams in a matter of minutes.

The new study – developed by researchers from New York University Stern School of Business and GoodFin, an AI-powered wealth management platform – evaluated 23 large language models on their ability to answer multiple choice and essay questions on mock CFA Level III exams. They found frontier reasoning models, including o4-mini, Gemini 2.5 Pro and Claude Opus, were able to use “chain-of-thought prompting” to successfully pass.

Previous research, particularly from two years ago, had found artificial intelligence could clear Levels I and II of the exam, but it struggled with Level III, due to the essay questions. However, the technology has evolved so rapidly that the researchers wanted to know whether the models could handle, “specialized, high-stakes analytical reasoning required for professional financial decision-making.” The third CFA exam is primarily focused on portfolio management and wealth planning.

AI system for rapid annotation of medical images could accelerate clinical research

Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical researchers take when running a new study involving biomedical images.

For instance, to determine how the size of the brain’s hippocampus changes as patients age, the scientist first outlines each hippocampus in a series of brain scans. For many structures and image types, this is often a manual process that can be extremely time-consuming, especially if the regions being studied are challenging to delineate.

To streamline the process, MIT researchers developed an artificial intelligence-based system that enables a researcher to rapidly segment new biomedical imaging datasets by clicking, scribbling, and drawing boxes on the images. This new AI model uses these interactions to predict the segmentation.

AI Cracks the Code for the Next Generation of Solar Power

Rising global energy demands are pushing the limits of solar technology. Scientists in Sweden have now taken a major step toward unlocking the potential of halide perovskites. Global demand for electricity is climbing at a fast pace, making it essential to find sustainable ways to meet future nee

Psychiatric Facilities Are Being Bombarded by AI Users

While many working people are reasonably worried about AI taking their jobs and leaving them on the street, another consequence of the AI revolution is filling seats in mental health facilities.

The mass adoption of large language model (LLM) chatbots is resulting in large numbers of mental health crises centered around AI use, in which people share delusional or paranoid thoughts with a product like ChatGPT — and the bot, instead of recommending that the user get help, affirms the unbalanced thoughts, often spiraling into marathon chat sessions that can end in tragedy or even death.

New reporting by Wired, drawing on more than a dozen psychiatrists and researchers, calls it a “new trend” growing in our AI-powered world. Keith Sakata, a psychiatrist at UCSF, told the publication he’s counted a dozen cases of hospitalization in which AI “played a significant role” in “psychotic episodes” this year alone.

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