Shortly after the launch of ChatGPT, the Atlantic drew up a list of the greatest threats to the 166-year-old publication from generative artificial intelligence. At the top: Google's embrace of the technology. About 40% of the magazine's web traffic comes from Google searches, which turn up links that users click on. A task force at the Atlantic modeled what could happen if Google integrated AI into search. It found that 75% of the time, the AI-powered search would likely provide a full answer to a user's query and the Atlantic's site would miss out on traffic it otherwise would have gotten.

Jack Krawczyk discusses how Google Bard helps users connect and communicate -- and what the future holds for the platform. ChatGPT has been found to have shared inaccurate information regarding drug usage, according to new research. In a study led by Long Island University (LIU) in Brooklyn, New York, nearly 75% of drug-related, pharmacist-reviewed responses from the generative AI chatbot were found to be incomplete or wrong. In some cases, ChatGPT, which was developed by OpenAI in San Francisco and released in late 2022, provided "inaccurate responses that could endanger patients," the American Society of Health System Pharmacists (ASHP), headquartered in Bethesda, Maryland, stated in a press release. ChatGPT also generated "fake citations" when asked to cite references to support some responses, the same study also found.

There was the Bollywood star in skin-tight lycra, the Bangladeshi politician filmed in a bikini and the young Pakistani woman snapped with a man. None were real, but all three images were credible enough to unleash lust, vitriol, and even allegedly a murder, underlining the sophistication of generative artificial intelligence and the threats it poses to women across Asia. The two videos and the photo were deepfakes, and went viral in a vibrant social mediascape struggling to come to grips with technology that has the power to create convincing copies and can upend real lives.

Can generative AI help us speed up the authoring of tools to help self-represented litigants? In this paper, we describe 3 approaches to automating the completion of court forms: a generative AI approach that uses GPT-3 to iteratively prompt the user to answer questions, a constrained template-driven approach that uses GPT-4-turbo to generate a draft of questions that are subject to human review, and a hybrid method. We use the open source Docassemble platform in all 3 experiments, together with a tool created at Suffolk University Law School called the Assembly Line Weaver. We conclude that the hybrid model of constrained automated drafting with human review is best suited to the task of authoring guided interviews.

High-resolution image generation with Generative Artificial Intelligence (GenAI) has immense potential but, due to the enormous capital investment required for training, it is increasingly centralised to a few large corporations, and hidden behind paywalls. This paper aims to democratise high-resolution GenAI by advancing the frontier of high-resolution generation while remaining accessible to a broad audience. We demonstrate that existing Latent Diffusion Models (LDMs) possess untapped potential for higher-resolution image generation. Our novel DemoFusion framework seamlessly extends open-source GenAI models, employing Progressive Upscaling, Skip Residual, and Dilated Sampling mechanisms to achieve higher-resolution image generation. The progressive nature of DemoFusion requires more passes, but the intermediate results can serve as "previews", facilitating rapid prompt iteration.

Computer simulations offer a robust toolset for exploring complex systems across various disciplines. A particularly impactful approach within this realm is Agent-Based Modeling (ABM), which harnesses the interactions of individual agents to emulate intricate system dynamics. ABM's strength lies in its bottom-up methodology, illuminating emergent phenomena by modeling the behaviors of individual components of a system. Yet, ABM has its own set of challenges, notably its struggle with modeling natural language instructions and common sense in mathematical equations or rules. This paper seeks to transcend these boundaries by integrating Large Language Models (LLMs) like GPT into ABM. This amalgamation gives birth to a novel framework, Smart Agent-Based Modeling (SABM). Building upon the concept of smart agents -- entities characterized by their intelligence, adaptability, and computation ability -- we explore in the direction of utilizing LLM-powered agents to simulate real-world scenarios with increased nuance and realism. In this comprehensive exploration, we elucidate the state of the art of ABM, introduce SABM's potential and methodology, and present three case studies (source codes available at https://github.com/Roihn/SABM), demonstrating the SABM methodology and validating its effectiveness in modeling real-world systems. Furthermore, we cast a vision towards several aspects of the future of SABM, anticipating a broader horizon for its applications. Through this endeavor, we aspire to redefine the boundaries of computer simulations, enabling a more profound understanding of complex systems.

The use of generative AI in education is a controversial topic. Current technology offers the potential to create educational content from text, speech, to images based on simple input prompts. This can enhance productivity by summarizing knowledge and improving communication, quickly adjusting to different types of learners. Moreover, generative AI holds the promise of making the learning itself more fun, by responding to user inputs and dynamically generating high-quality creative material. In this paper we present the multisensory educational game ArchiGuesser that combines various AI technologies from large language models, image generation, to computer vision to serve a single purpose: Teaching students in a playful way the diversity of our architectural history and how generative AI works.

There is a tension at the heart of ChatGPT that may soon snap. Does the technology expand our world or constrain it? Which is to say, do AI-powered chatbots open new doors to learning and discovery, or do they instead risk siloing off information and leaving us stuck with unreliable access to truth? Earlier today, OpenAI, the maker of ChatGPT, announced a partnership with the media conglomerate Axel Springer that seems to get us closer to an answer. Under the arrangement, ChatGPT will gain the capacity to present its users with "summaries of selected global news content" published by the news organizations in Axel Springer's portfolio, which includes Politico and Business Insider.

Axel Springer, the publisher of Business Insider and Politico, said on Wednesday it was partnering with OpenAI, which will pay the German media group to allow ChatGPT to summarize current articles in responses generated by the chatbot. "ChatGPT users around the world will receive summaries of selected global news content from Axel Springer's media brands," which also includes the German tabloid Bild, the two companies said in a statement. The chatbot's answers will include material otherwise kept behind a paywall and offer "links to the full articles for transparency and further information", they said. Axel Springer will be paid for making its content available to the US artificial intelligence firm, a spokesman for the media group told AFP. The deal is valid for several years and does not commit either side to exclusivity, leaving them free to sign new agreements, the spokesman said without giving more detail.

OpenAI will pay German publisher Axel Springer to use its news articles to train its AI models and show real-time information from Axel Springer's brands, which include Business Insider and Politico in the US and Bild and Welt in Europe, in ChatGPT's responses. None of the companies disclosed how much the deal was worth, but Bloomberg reported that OpenAI will pay the publisher tens of millions of euros over the next three years. "This partnership with Axel Springer will help provide people with new ways to access quality, real-time news content through our AI tools," said OpenAI's chief operating officer Brad Lightcap in a statement. "We are deeply committed to working with publishers and creators around the world and ensuring they benefit from advanced AI technology and new revenue models." OpenAI's partnership with Axel Springer comes on the heels of concerns from creators, authors, and publishers who have criticized and sued generative AI companies for training their models on their content without consent or compensation.