A new feature on X revealed that many influential MAGA accounts are not actually based in the US. President Donald Trump has continued sharing their posts anyway. A new feature on X has revealed that a number of major MAGA accounts on the platform are operated by people based overseas. And in the days since these accounts were exposed, President Donald Trump has continued boosting several of them. Many of the accounts, which have large followings and claim to be conservative people based in Texas or "America First" accounts "promoting good resisting evil," are actually operated everywhere from Chile and Nigeria to Russia and across eastern Europe .

Persian names present unique challenges for natural language processing applications, particularly in gender detection and digital identity creation, due to transliteration inconsistencies and cultural-specific naming patterns. Existing tools exhibit significant performance degradation on Persian names, while the scarcity of comprehensive datasets further compounds these limitations. To address these challenges, the present research introduces PNGT-26K, a comprehensive dataset of Persian names, their commonly associated gender, and their English transliteration, consisting of approximately 26,000 tuples. As a demonstration of how this resource can be utilized, we also introduce two frameworks, namely Open Gender Detection and Nominalist. Open Gender Detection is a production-grade, ready-to-use framework for using existing data from a user, such as profile photo and name, to give a probabilistic guess about the person's gender. Nominalist, the second framework introduced by this paper, utilizes agentic AI to help users choose a username for their social media accounts on any platform. It can be easily integrated into any website to provide a better user experience. The PNGT-26K dataset, Nominalist and Open Gender Detection frameworks are publicly available on Github.

The upgrades being pushed out for AI chatbots aren't slowing down, and one of the latest improvements added to Google Gemini is an ability for the AI to remember previous conversations. This allows you to refer back to something you've said the previous day, the previous week, or whenever it was. But do you want that? "Gemini can now recall your past chats to provide more helpful responses," explains Google. "Whether you're asking a question about something you've already discussed, or asking Gemini to summarize a previous conversation, Gemini now uses information from relevant chats to craft a response." For now, this is exclusive to Gemini Advanced subscribers and those using Gemini in English, though it may roll out to other users in the future.

We've seen numerous new features added to ChatGPT in recent months, including updated models, web search capabilities, and the ability to remember what you say to it--and the latest software upgrade added to the AI bot by OpenAI makes it more useful as a general-purpose digital assistant. Beginning in beta form, and available initially to paying subscribers--the feature will reach everyone eventually, OpenAI says--ChatGPT Tasks lets you request the AI chatbot perform actions regularly on an automated schedule, or remind you about something in the future. Here's everything you need to know about it. "In this early beta, you can create scheduled tasks that enable ChatGPT to run automated prompts and proactively reach out to you on a scheduled basis," explains OpenAI. Tasks are available on the web, in the mobile apps, and in the macOS desktop app; OpenAI says the feature will make it to the Windows desktop app soon.

Welcome to Opt Out, a semi-regular column in which we help you navigate your online privacy and show you how to say no to surveillance. If you'd like to skip to a section about a particular site or social network, click the "Jump to" menu at the top of this article. The competition to make the latest, greatest, most advanced artificial intelligence thing has turned an already data-hungry tech industry ravenous. Companies looking to build out their AI-powered search engines, smart email composers or chatbots are scraping your posts and personal data and using them to train those systems, which need ever-increasing amounts of text and images. Even if you haven't opted in to letting them use your data to train their AI, some companies have opted you in by default.

A growing number of studies have linked facial width-to-height ratio (fWHR) with various antisocial or violent behavioral tendencies. However, those studies have predominantly been laboratory based and low powered. Behavioral tendencies were measured using 55 well-established psychometric scales, including self-report scales measuring intelligence, domains and facets of the five-factor model of personality, impulsiveness, sense of fairness, sensational interests, self-monitoring, impression management, and satisfaction with life. The findings revealed that fWHR is not substantially linked with any of these self-reported measures of behavioral tendencies, calling into question whether the links between fWHR and behavior generalize beyond the small samples and specific experimental settings that have been used in past fWHR research. A growing number of studies have linked facial widthto-height Broader-faced men, but not women, have also been ratio (fWHR; Weston, Friday, & Liò, 2007) with shown to be more likely to cheat when reporting dice various antisocial or violent behavioral tendencies in rolls, n = 146, t(144) = 1.97, p =.05 (Geniole, Keyes, men, but not in women.

Welcome to Opt Out, a semi-regular column in which we help you navigate your online privacy and show you how to say no to surveillance. If you'd like to skip to a section about a particular site or social network, click the "Jump to" menu at the top of this article. The competition to make the latest, greatest, most advanced artificial intelligence thing has turned an already data-hungry tech industry ravenous. Companies looking to build out their AI-powered search engines, smart email composers or chatbots are scraping your posts and personal data and using them to train those systems, which need ever-increasing amounts of text and images. Even if you haven't opted in to letting them use your data to train their AI, some companies have opted you in by default.

Social media is heading toward personalization more and more, where individuals reveal their beliefs, interests, habits, and activities, simply offering glimpses into their personality traits. This study, explores the correlation between the use of Arabic language on twitter, personality traits and its impact on sentiment analysis. We indicated the personality traits of users based on the information extracted from their profile activities, and the content of their tweets. Our analysis incorporated linguistic features, profile statistics (including gender, age, bio, etc.), as well as additional features like emoticons. To obtain personality data, we crawled the timelines and profiles of users who took the 16personalities test in Arabic on 16personalities.com. Our dataset comprised 3,250 users who shared their personality results on twitter. We implemented various machine learning techniques, to reveal personality traits and developed a dedicated model for this purpose, achieving a 74.86% accuracy rate with BERT, analysis of this dataset proved that linguistic features, profile features and derived model can be used to differentiate between different personality traits. Furthermore, our findings demonstrated that personality affect sentiment in social media. This research contributes to the ongoing efforts in developing robust understanding of the relation between human behaviour on social media and personality features for real-world applications, such as political discourse analysis, and public opinion tracking.

While scientists haven't invented a time machine just yet, there is now a way for you to get some much-needed advice from your older self. Experts at Massachusetts Institute of Technology (MIT) have created Future You – an AI-powered chatbot that simulates a version of the user at 60 years old. The researchers say that a quick chat with your future self is just what people need to start thinking more about their decisions in the present. With an aged-up profile picture and a full life's worth of synthetic memories, the chatbot delivers plausible stories about the user's life alongside sage wisdom from the future. And, in a trial of 334 volunteers, just a short conversation with the chatbot left users feeling less anxious and more connected to their future selves.

Recent advancements in generative artificial intelligence (AI) have raised concerns about their potential to create convincing fake social media accounts, but empirical evidence is lacking. In this paper, we present a systematic analysis of Twitter(X) accounts using human faces generated by Generative Adversarial Networks (GANs) for their profile pictures. We present a dataset of 1,353 such accounts and show that they are used to spread scams, spam, and amplify coordinated messages, among other inauthentic activities. Leveraging a feature of GAN-generated faces -- consistent eye placement -- and supplementing it with human annotation, we devise an effective method for identifying GAN-generated profiles in the wild. Applying this method to a random sample of active Twitter users, we estimate a lower bound for the prevalence of profiles using GAN-generated faces between 0.021% and 0.044% -- around 10K daily active accounts. These findings underscore the emerging threats posed by multimodal generative AI. We release the source code of our detection method and the data we collect to facilitate further investigation. Additionally, we provide practical heuristics to assist social media users in recognizing such accounts.