The widespread adoption of large language models (LLMs) marks a transformative era in technology, especially within the educational sector. This paper explores the integration of LLMs within learning management systems (LMSs) to develop an adaptive learning management system (ALMS) personalized for individual learners across various educational stages. Traditional LMSs, while facilitating the distribution of educational materials, fall short in addressing the nuanced needs of diverse student populations, particularly in settings with limited instructor availability. Our proposed system leverages the flexibility of AI to provide a customizable learning environment that adjusts to each user's evolving needs. By integrating a suite of general-purpose and domain-specific LLMs, this system aims to minimize common issues such as factual inaccuracies and outdated information, characteristic of general LLMs like OpenAI's ChatGPT. This paper details the development of an ALMS that not only addresses privacy concerns and the limitations of existing educational tools but also enhances the learning experience by maintaining engagement through personalized educational content.

While large generative artificial intelligence (GenAI) models have achieved significant success, they also raise growing concerns about online information security due to their potential misuse for generating deceptive content. Out-of-context (OOC) multimodal misinformation detection, which often retrieves Web evidence to identify the repurposing of images in false contexts, faces the issue of reasoning over GenAI-polluted evidence to derive accurate predictions. Existing works simulate GenAI-powered pollution at the claim level with stylistic rewriting to conceal linguistic cues, and ignore evidence-level pollution for such information-seeking applications. In this work, we investigate how polluted evidence affects the performance of existing OOC detectors, revealing a performance degradation of more than 9 percentage points. We propose two strategies, cross-modal evidence reranking and cross-modal claim-evidence reasoning, to address the challenges posed by polluted evidence. Extensive experiments on two benchmark datasets show that these strategies can effectively enhance the robustness of existing out-of-context detectors amidst polluted evidence.

The potential for negative impacts of AI has rapidly become more pervasive around the world, and this has intensified a need for responsible AI governance. While many regulatory bodies endorse risk-based approaches and a multitude of risk mitigation practices are proposed by companies and academic scholars, these approaches are commonly expert-centered and thus lack the inclusion of a significant group of stakeholders. Ensuring that AI policies align with democratic expectations requires methods that prioritize the voices and needs of those impacted. In this work we develop a participative and forward-looking approach to inform policy-makers and academics that grounds the needs of lay stakeholders at the forefront and enriches the development of risk mitigation strategies. Our approach (1) maps potential mitigation and prevention strategies of negative AI impacts that assign responsibility to various stakeholders, (2) explores the importance and prioritization thereof in the eyes of laypeople, and (3) presents these insights in policy fact sheets, i.e., a digestible format for informing policy processes. We emphasize that this approach is not targeted towards replacing policy-makers; rather our aim is to present an informative method that enriches mitigation strategies and enables a more participatory approach to policy development.

OpenAI has begun previewing a new tool called Operator that can navigate within a web browser. According to a blog post published Thursday, the software is powered by what the company calls a Computer-Using Agent. "CUA is trained to interact with graphical user interfaces (GUIs) -- the buttons, menus, and text fields people see on a screen -- just as humans do," says OpenAI of the model. "This gives it the flexibility to perform digital tasks without using OS- or web-specific APIs." The current release of Operator builds on OpenAI's GPT-4o model.

This week, OpenAI and other tech companies joined US president Donald Trump at the White House to pledge a private investment of half a trillion dollars in US data centres over the next four years. The "Stargate Project" could power an ambitious expansion of AI technology – with repercussions for the US electricity grid and the country's energy future. The Stargate announcement comes as North America has been experiencing surging electricity demand in recent years.

Things were not looking great for OpenAI at the end of last year. The company had been struggling with major delays on its long-awaited GPT-5 and hemorrhaging key talent--notably, Chief Scientist Ilya Sutskever, Chief Technology Officer Mira Murati, and Alec Radford, the researcher who'd set the company on the path of developing GPTs in the first place. Several people who left either joined OpenAI competitors or launched new ones. The start-up's relationship with Microsoft, its biggest backer and a crucial provider of the computing infrastructure needed to train and deploy its AI models, was being investigated by the Federal Trade Commission. And then there was Elon Musk.

OpenAI is letting some users try a new ChatGPT feature that uses its artificial intelligence to operate a web browser to book trips, buy groceries, hunt for bargains, and do many other online chores. The new tool, called Operator, is an AI agent: It relies on an AI model trained on both text and images to interpret commands and figure out how to use a web browser to execute them. OpenAI claims it has the potential to automate many day-to-day tasks and workday errands. OpenAI's Operator follows rival releases by both Google and Anthropic, which have demonstrated ones capable of using the web. AI agents are widely seen as the next evolutionary stage for AI following chatbots, and many companies have hopped on the hype train by touting them.

OpenAI claims that Operator outperforms similar rival tools, including Anthropic's Computer Use (a version of Claude 3.5 Sonnet that can carry out simple tasks on a computer) and Google DeepMind's Mariner (a web-browsing agent built on top of Gemini 2.0). The fact that three of the world's top AI firms have converged on the same vision of what agent-based models could be makes one thing clear. The battle for AI supremacy has a new frontier--and it's our computer screens. "Moving from generating text and images to doing things is the right direction," says Ali Farhadi, CEO of the Allen Institute for AI (AI2). "It unlocks business, solves new problems."

Thousands of people have reported they are unable to use the world's best-known artificial intelligence (AI) tool, ChatGPT Downdetector, which tracks website outages, showed more than 10,000 people reported the AI chatbot, which is made by OpenAI, was not working in the UK on Thursday. Users attempting to use it were met with a message reading "the web server reported a bad gateway error". OpenAI has not yet publicly commented on the outage. The BBC has contacted the firm for comment. However, many people have taken to social media to highlight the problem and the disruption it is causing them.

ChatGPT is down across the US as users report seeing a'bad gateway' error message when using the AI tool. Downdetector, a site that monitors online outages, shows issues hit the OpenAI-owned platform around 7am ET. The error message indicates that one server received an invalid response from another, creating a communication breakdown. Many users have shared their frustrations on X, saying they'feel lost without it.' 'Seriously, how am I supposed to brainstorm, write, and research without my AI assistant,' an X user posted.