Since generative AI exploded into global consciousness in 2023, an unprecedented demand for computing power has emerged alongside the demand for apps utilising the technology. Tool's like OpenAI's ChatGPT require thousands of Nvidia GPUs (graphics processing units) to smoothly process all the information being fed in and output. Nvidia last week compared GPUs to rare earth metals for AI, saying they're "foundational" for the operation of generative AI today. The energy required to power all this hardware is the equivalent of a small country, according to a report released by French energy company Schneider Electric last year. On Wednesday OpenAI's CEO, Sam Altman, told an audience at Davos that an energy breakthrough was needed to power AI advances.

U.S. antitrust enforcers are opening an investigation into the relationships between leading artificial intelligence startups such as ChatGPT-maker OpenAI and Anthropic and the tech giants that have invested billions of dollars into them. "We're scrutinizing whether these ties enable dominant firms to exert undue influence or gain privileged access in ways that could undermine fair competition," said Lina Khan, chair of the U.S. Federal Trade Commission, in opening remarks at a Thursday AI forum. Khan said the market inquiry would review "the investments and partnerships being formed between AI developers and major cloud service providers." The FTC said on Thursday that it has issued "compulsory orders" to five companies -- cloud providers Amazon, Google and Microsoft, and AI startups Anthropic and OpenAI -- requiring them to provide information regarding investments and partnerships. Microsoft's close and years-long relationship with OpenAI is the best known of the partnerships.

Regulatory compliance in the pharmaceutical industry entails navigating through complex and voluminous guidelines, often requiring significant human resources. To address these challenges, our study introduces a chatbot model that utilizes generative AI and the Retrieval Augmented Generation (RAG) method. This chatbot is designed to search for guideline documents relevant to the user inquiries and provide answers based on the retrieved guidelines. Recognizing the inherent need for high reliability in this domain, we propose the Question and Answer Retrieval Augmented Generation (QA-RAG) model. In comparative experiments, the QA-RAG model demonstrated a significant improvement in accuracy, outperforming all other baselines including conventional RAG methods. This paper details QA-RAG's structure and performance evaluation, emphasizing its potential for the regulatory compliance domain in the pharmaceutical industry and beyond. We have made our work publicly available for further research and development.

The traditional role of the network layer is the transfer of packet replicas from source to destination through intermediate network nodes. We present a generative network layer that uses Generative AI (GenAI) at intermediate or edge network nodes and analyze its impact on the required data rates in the network. We conduct a case study where the GenAI-aided nodes generate images from prompts that consist of substantially compressed latent representations. The results from network flow analyses under image quality constraints show that the generative network layer can achieve an improvement of more than 100% in terms of the required data rate.

Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence. The rapid growth of medical evidence, which can be obtained from various sources, poses a challenge in collecting, appraising, and synthesizing the evidential information. Recent advancements in generative AI, exemplified by large language models, hold promise in facilitating the arduous task. However, developing accountable, fair, and inclusive models remains a complicated undertaking. In this perspective, we discuss the trustworthiness of generative AI in the context of automated summarization of medical evidence.

The Federal Trade Commission is launching an inquiry into massive investments made by Microsoft, Amazon and Alphabet into generative AI startups OpenAI and Anthropic, the agency announced on Thursday. The FTC said that it had issued "compulsory orders" to the companies and would scrutinize their relationships with AI startups to understand their impact on competition. "History shows that new technologies can create new markets and healthy competition," FTC Chair Lina Khan said in a statement. "As companies race to develop and monetize AI, we must guard against tactics that foreclose this opportunity. Our study will shed light on whether investments and partnerships pursued by dominant companies risk distorting innovation and undermining fair competition."

Under the Biden administration, federal regulators have stepped up their scrutiny of Big Tech companies' acquisitions of smaller rivals, bringing lengthy and costly legal challenges against Meta's acquisition of the virtual reality company Within and Microsoft's purchase of the game maker Activision. In the age of generative AI, Silicon Valley giants have to date sidestepped such legal obstacles by instead funneling investments into younger AI companies and striking deals to ensure those start-ups are giving preference to their computing services.

The United States trade regulator launched an inquiry on Thursday into generative artificial intelligence investments and partnerships. The Federal Trade Commission (FTC) said in a statement that it issued orders to five companies requiring them to provide information on the matter. The companies were Google's parent company Alphabet, Amazon, Anthropic, Microsoft, and ChatGPT maker OpenAI, the agency's statement said. The inquiry will focus on what authority and rights the tech giants' investments in the fledgling AI companies have conferred and whether those deals harm competition. "Our study will shed light on whether investments and partnerships pursued by dominant companies risk distorting innovation and undermining fair competition," FTC chair Lina Khan said in a statement.

Cutting-edge artificial intelligence models such as OpenAI's GPT-4V and Google's Gemini struggle to solve clever wordplay puzzles involving both images and text. Rebus puzzles typically require a puzzler to identify a word represented by an image, to add or subtract letters from that word and to combine the result with words identified from other images to arrive at a solution. How this moment for AI will change society forever (and how it won't)

The project could build new factories or partner with existing chip-making companies, like Taiwan Semiconductor Manufacturing Co., the world's biggest made-to-order chip company that currently manufactures around 90 percent of the world's advanced chips, one of the people said. The venture could operate similarly to how Apple allocates huge amounts of money to TSMC in order to guarantee a stable supply of chips, the person said.