Artificial intelligence generated content (AIGC) has emerged as a promising technology to improve the efficiency, quality, diversity and flexibility of the content creation process by adopting a variety of generative AI models. Deploying AIGC services in wireless networks has been expected to enhance the user experience. However, the existing AIGC service provision suffers from several limitations, e.g., the centralized training in the pre-training, fine-tuning and inference processes, especially their implementations in wireless networks with privacy preservation. Federated learning (FL), as a collaborative learning framework where the model training is distributed to cooperative data owners without the need for data sharing, can be leveraged to simultaneously improve learning efficiency and achieve privacy protection for AIGC. To this end, we present FL-based techniques for empowering AIGC, and aim to enable users to generate diverse, personalized, and high-quality content. Furthermore, we conduct a case study of FL-aided AIGC fine-tuning by using the state-of-the-art AIGC model, i.e., stable diffusion model. Numerical results show that our scheme achieves advantages in effectively reducing the communication cost and training latency and privacy protection. Finally, we highlight several major research directions and open issues for the convergence of FL and AIGC.

Visual metaphors are powerful rhetorical devices used to persuade or communicate creative ideas through images. Similar to linguistic metaphors, they convey meaning implicitly through symbolism and juxtaposition of the symbols. We propose a new task of generating visual metaphors from linguistic metaphors. This is a challenging task for diffusion-based text-to-image models, such as DALL$\cdot$E 2, since it requires the ability to model implicit meaning and compositionality. We propose to solve the task through the collaboration between Large Language Models (LLMs) and Diffusion Models: Instruct GPT-3 (davinci-002) with Chain-of-Thought prompting generates text that represents a visual elaboration of the linguistic metaphor containing the implicit meaning and relevant objects, which is then used as input to the diffusion-based text-to-image models.Using a human-AI collaboration framework, where humans interact both with the LLM and the top-performing diffusion model, we create a high-quality dataset containing 6,476 visual metaphors for 1,540 linguistic metaphors and their associated visual elaborations. Evaluation by professional illustrators shows the promise of LLM-Diffusion Model collaboration for this task . To evaluate the utility of our Human-AI collaboration framework and the quality of our dataset, we perform both an intrinsic human-based evaluation and an extrinsic evaluation using visual entailment as a downstream task.

More than a quarter of UK adults have used generative artificial intelligence such as chatbots, according to survey showing that 4 million people have also used it for work. Generative AI, which refers to AI tools that produce convincing text or images in response to human prompts, has gripped the public imagination since the launch of ChatGPT in November. The rate of adoption of the latest generation of AI systems exceeds that of voice-assisted speakers such as Amazon's Alexa, according to accounting group Deloitte, which published the survey. Deloitte said 26% of 16- to 75-year-olds have used a generative AI tool, representing about 13 million people, with one in 10 of those respondents using it at least once a day. "It took five years for voice-assisted speakers to achieve the same adoption levels. It is incredibly rare for any emerging technology to achieve these levels of adoption and frequency of usage so rapidly," said Paul Lee, a Deloitte partner.

This spring, Congress hosted OpenAI's chief executive Sam Altman for a hearing, in which he admitted the technology could be a sousce of errors. He called for regulations to be crafted for the emerging industry and recommended that a new agency be formed to tackle it. He said he expected the technology to have a significant impact as its uses become clear, including on jobs.

The Associated Press (AP) and ChatGPT parent company OpenAI have reached a news-sharing agreement, but not for the reasons you may think. It doesn't involve AI chatbots quickly churning out content, but rather a way for OpenAI to train its algorithmic models, as reported by Axios. The two-year deal gives OpenAI access to select news content and technology from the AP archives, dating back to 1985. All of this sweet, sweet data will be used to improve the efficacy of future iterations of ChatGPT and related tools. This is one of the first high-profile partnerships between a major news organization and an artificial intelligence company.

Now, a rising group of authors, musicians, news organizations and social media companies has been pushing back, arguing that the use of their content to train AI is a massive shift in the way the internet works, especially since some of the AI tools being trained on human-made content are already being used to replace human workers. A wave of lawsuits has washed over the industry in the past two weeks alleging improper data use, including class-action suits against OpenAI and Google, and lawsuits against OpenAI from the comedian Sarah Silverman and two prominent fiction authors.

American regulators now appear to be clamping down on generative AI in earnest. The Washington Post has learned the Federal Trade Commission (FTC) has launched an investigation into OpenAI, the creator of ChatGPT and DALL-E. Officials have requested documents showing how the company tackles risks stemming from its large language AI models. The FTC is concerned the company may be violating consumer protection laws through "unfair or deceptive" practices that could hurt the public's privacy, security or reputation. The Commission is particularly interested in information linked to a bug that leaked ChatGPT users' sensitive data, including payments and chat histories.

The US's top competition watchdog has opened an investigation into OpenAI, the maker of ChatGPT, on claims it has run afoul of consumer protection laws by putting personal reputations and data at risk. The move marks the strongest regulatory threat to the Microsoft-backed startup that kicked off the frenzy in generative artificial intelligence, enthralling consumers and businesses while raising concerns about its potential risks. The Federal Trade Commission (FTC) this week sent a 20-page demand for records about how OpenAI addresses risks related to its AI models. The agency is investigating whether the company engaged in unfair or deceptive practices that resulted in "reputational harm" to consumers. One of the questions has to do with steps OpenAI has taken to address the potential for its products to "generate statements about real individuals that are false, misleading, or disparaging".

The US Federal Trade Commission has sent a request for information to startup OpenAI Inc. as part of a probe into its ChatGPT conversational AI bot, according to a person familiar with the request. The document request was sent recently to the Microsoft Corp.-backed AI company seeking information on whether ChatGPT harms consumers, according to the person, who asked not to be named discussing a non-public investigation. FTC Chair Lina Khan, who is set to appear before Congress Thursday, has raised concerns about AI, saying enforcers "need to be vigilant early" with transformative tools like artificial intelligence. The Washington Post earlier reported on the FTC's probe.

WASHINGTON--The Federal Trade Commission is investigating whether OpenAI's ChatGPT artificial-intelligence system has harmed individuals by publishing false information about them, according to a letter the agency sent to the company.