Graphic layout generation, a growing research field, plays a significant role in user engagement and information perception. Existing methods primarily treat layout generation as a numerical optimization task, focusing on quantitative aspects while overlooking the semantic information of layout, such as the relationship between each layout element. In this paper, we propose LayoutNUWA, the first model that treats layout generation as a code generation task to enhance semantic information and harness the hidden layout expertise of large language models~(LLMs). More concretely, we develop a Code Instruct Tuning (CIT) approach comprising three interconnected modules: 1) the Code Initialization (CI) module quantifies the numerical conditions and initializes them as HTML code with strategically placed masks; 2) the Code Completion (CC) module employs the formatting knowledge of LLMs to fill in the masked portions within the HTML code; 3) the Code Rendering (CR) module transforms the completed code into the final layout output, ensuring a highly interpretable and transparent layout generation procedure that directly maps code to a visualized layout. We attain significant state-of-the-art performance (even over 50\% improvements) on multiple datasets, showcasing the strong capabilities of LayoutNUWA. Our code is available at https://github.com/ProjectNUWA/LayoutNUWA.

Text summarization has a wide range of applications in many scenarios. The evaluation of the quality of the generated text is a complex problem. A big challenge to language evaluation is that there is a clear divergence between existing metrics and human evaluation. A document summary's quality can be assessed by human annotators on various criteria, both objective ones like grammar and correctness, and subjective ones like informativeness, succinctness, and appeal. Most of the automatic evaluation methods like BLUE/ROUGE may be not able to adequately capture the above dimensions. In this paper, we propose a new evaluation framework based on LLMs, which provides a comprehensive evaluation framework by comparing generated text and reference text from both objective and subjective aspects. First, we propose to model objective and subjective dimensions of generated text based on roleplayers prompting mechanism. Furthermore, we introduce a context-based prompting mechanism that is able to generate dynamic roleplayer profiles based on input context. Finally, we design a multi-roleplayer prompting technology based on batch prompting and integrate multiple outputs into the final evaluation results. Experimental results on three real datasets for summarization show that our model is highly competitive and has a very high consistency with human annotators.

Prompt learning approaches have made waves in natural language processing by inducing better few-shot performance while they still follow a parametric-based learning paradigm; the oblivion and rote memorization problems in learning may encounter unstable generalization issues. Specifically, vanilla prompt learning may struggle to utilize atypical instances by rote during fully-supervised training or overfit shallow patterns with low-shot data. To alleviate such limitations, we develop RetroPrompt with the motivation of decoupling knowledge from memorization to help the model strike a balance between generalization and memorization. In contrast with vanilla prompt learning, RetroPrompt constructs an open-book knowledge-store from training instances and implements a retrieval mechanism during the process of input, training and inference, thus equipping the model with the ability to retrieve related contexts from the training corpus as cues for enhancement. Extensive experiments demonstrate that RetroPrompt can obtain better performance in both few-shot and zero-shot settings. Besides, we further illustrate that our proposed RetroPrompt can yield better generalization abilities with new datasets. Detailed analysis of memorization indeed reveals RetroPrompt can reduce the reliance of language models on memorization; thus, improving generalization for downstream tasks. Code is available in https://github.com/zjunlp/PromptKG/tree/main/research/RetroPrompt.

Piers Morgan weighs in on the return of Bill Maher's'Real Time' amid writers strike on'One Nation with Brian Kilmeade.' After initially declaring his show would return amid the writers strike, talk show host Bill Maher announced Monday he has reversed that decision for the time being. "Real Time with Bill Maher's" 21st season was cut short after Hollywood writers went on strike in May. Writers are asking for higher pay, a guaranteed number of writers per room, better residuals and safeguards around the use of artificial intelligence (AI) in the writing process in their list of demands. With no foreseeable end to the strike, Maher initially revealed that the show would return without writers and simply skip the segments that rely on writers.

Birda co-founders John and Natalie White shared details of their social birding network with Fox News Digital. An AI-powered bird feeder called Bird Buddy doesn't only feed the birds -- it takes candid photos and identifies the species of each bird as it lands for a snack. Bird Buddy CEO Franci Zidar, whose company is based in Kalamazoo, Michigan, told Fox News Digital that the product uses artificial intelligence technology to take clear and "interesting" snapshots of the birds that come to feed. WHAT IS ARTIFICIAL INTELLIGENCE (AI)? The smart bird feeder then detects the type of bird species -- and sends a notification with the photo and bird info to its owner's mobile device.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. With artificial intelligence seemingly infiltrating every facet of our lives, one church decided to experiment with the technology for one of its services last week. The Violet Crown City Church, located in Austin, held an AI-generated service on Sunday, describing the experiment as "uncharted territory." "This Sunday we're entering somewhat uncharted territory by letting ChatGPT create the order of worship, prayers, sermon, liturgy, and even an original song for our 10 a.m. ChatGPT logo and AI Artificial Intelligence words are seen in this illustration taken, May 4, 2023. "The purpose is to invite us to consider the nature of truth and challenge our assumptions about what God can make sacred and inspired." The church acknowledged such an experiment would be easy to write off, but encouraged its members to keep an open mind. "[W]hy not attend instead and experience it for yourself?" the church said, clarifying that this would be a "one-time experiment and not something we'll likely do again." The church assuaged any worries that "Skynet" – a reference to the fictional AI system in the Terminator franchise – had taken control of the church. One church attendee told KXAN he was able to worship, but the service ultimately lacked the human touch. "I'm not sure that AI can actually express the emotions of love and kindness and empathy," Chambers said. "I think that we must practice love and express that.

Kara Frederick, tech director at the Heritage Foundation, discusses the need for regulations on artificial intelligence as lawmakers and tech titans discuss the potential risks. FIRST ON FOX: A new GOP-led bill aims to stop U.S. tax dollars from going toward a United Nations-run program that uses artificial intelligence to help weed out content deemed to be misinformation or hate speech. Rep. Ben Cline, R-Va., is introducing the End The U.N. Censorship Act this week. AI has emerged as a top priority for lawmakers on Capitol Hill this year. Its advancements, as well as its pitfalls, have inspired a slew of legislation as Washington, D.C., races to get ahead of the rapidly emerging technology.

Meet Madison and Jackson, the AI narrators or "digital voices" soon to be reading some of the audiobooks on Apple Books. They sound nothing like Siri or Alexa or the voice telling you about the unexpected item in the bagging area of your supermarket checkout. They sound warm, natural, animated. With their advanced levels of realism, Apple's new AI voices present the genuine possibility that the listener will be unaware of their artificiality. Even the phrase used in Apple's catalogues of digitally-narrated audiobooks – "this is an Apple Books audiobook narrated by a digital voice based on a human narrator" – is ambiguous.

People should not assume a positive outcome from the artificial intelligence boom, the UK's competition watchdog has warned, citing risks including a proliferation of false information, fraud and fake reviews as well as high prices for using the technology. The Competition and Markets Authority said people and businesses could benefit from a new generation of AI systems but dominance by entrenched players and flouting of consumer protection law posed a number of potential threats. The CMA made the warning in an initial review of foundation models, the technology that underpins AI tools such as the ChatGPT chatbot and image generators such as Stable Diffusion. The emergence of ChatGPT in particular has triggered a debate over the impact of generative AI – a catch-all term for tools that produce convincing text, image and voice outputs from typed human prompts – on the economy by eliminating white-collar jobs in areas such as law, IT and the media, as well as the potential for mass-producing disinformation targeting voters and consumers. The CMA chief executive, Sarah Cardell, said the speed at which AI was becoming a part of everyday life for people and businesses was "dramatic", with the potential for making millions of everyday tasks easier as well as boosting productivity – a measure of economic efficiency, or the amount of output generated by a worker for each hour worked.

It's no coincidence that many programs using artificial intelligence techniques are open source and thus completely free. This is because the early approaches originated in academia, where free licences for software are common practice in order to promote collaboration and further development. Here, however, it is not about frameworks and libraries for forms of AI, but about tangible and useful applications of artificial intelligence for your own computer. The term AI encompasses various methods such as neural networks, machine learning, deep learning, or natural language processing. In the following compilation, all these approaches are represented. The various approaches to pattern recognition, machine-processed decision trees, and automation of tasks are built on training data and models that are already ready. The availability of this data is one of the reasons why useful AI techniques are available in freely available software today at all.