Our study makes several key contributions to understanding LLM - generated disinformation: By validat ion on broader datasets, our detection methods establish a robust analytical framework for examining real - world disinformation content, confirming both the increasing presence and prevalence of machine - generated texts in disinformation datasets over time. The distribution of LLM - generated content varies significantly across languages and platforms, revealing targeted patterns of misuse rather than uniform effects. This provides empirical validation for previously speculated concerns and unsupported fears ab out increased LLM deployment in disinformation campaigns. Most importantly, our findings underscore the urgent need for continued investigation and improved countermeasures, including enhanced detection methods and credibility assessment systems to preserve information integrity in our evolving digital landscape.

Mental health experts, regulators, and many internet users themselves have called out the damage that social media can do to mental health. Must it addict, inflame, and depress us? A new social network called Maven aims to offer a healthier alternative, inspired by one scientist's work in artificial intelligence. The platform eschews likes and follows in favor of letting pure chance play more of a role in what appears in users' feeds. Maven's lead investor is Twitter cofounder and former CEO Ev Williams, who also founded Medium.

Chinese robotics company Ewaybot took to the CES trade show in Las Vegas with MoRo, a robotic assistant that is designed to simplify your life. Capable of moving around indoors and outdoors, handling objects and listening to voice commands, the MoRo is nearly 4-feet tall, weighs close to 80 pounds and has up to eight hours of battery life. It also costs a hefty $30,000, so the dream of a robot butler isn't quite there yet.

In-home assistants like Amazon Echo and Google Home are handy, but their functions are limited: They can tell you where to find a can of soda, but they can't actually bring one to you. Robotics company Ewaybot created Moro as a rolling, humanoid assistant for research labs and universities, and it's currently in a handful of schools across China. Moro is about four feet tall, weighs roughly 77 pounds, and its arms have six points of articulation; they each end in a three-pronged version of a hand that can grip everything from pens to heavy vials. The robot responds to voice communication as well (watch out, Alexa). Moro uses Intel's RealSense camera to avoid obstacles, plus ultrasound and infrared sensors.

Teaching artificial intelligence is effective if the experience is a visual and interactive one, with educational materials that utilize combinations of various content types such as text, math, and code into an integrated experience. Unfortunately, easy-to-use tools for creating such pedagogical resources are not available to the educators, resulting in most courses being taught using a disconnected set of static materials, which is not only ineffective for learning AI, but further, requires repeated and redundant effort for the instructor. In this paper, we introduce Moro, a software tool for easily creating and presenting AI-friendly teaching materials. Moro notebooks integrate content of different types (text, math, code, images), allow real-time interactions via modifiable and executable code blocks, and are viewable in browsers both as long-form pages and as presentations. Creating notebooks is easy and intuitive; the creation tool is also in-browser, is WYSIWYG for quick iterations of editing, and supports a variety of shortcuts and customizations for efficiency. We present three deployed case studies of Moro that widely differ from each other, demonstrating its utility in a variety of scenarios such as in-class teaching and conference tutorials.