It looks like Fake Drake won't be taking home a Grammy. Recording Academy CEO Harvey Mason Jr. said this week that although the organization will consider music with limited AI-generated voices or instrumentation for award recognition, it will only honor songs written and performed "mostly by a human." "At this point, we are going to allow AI music and content to be submitted, but the Grammys will only be allowed to go to human creators who have contributed creatively in the appropriate categories," Mason said in an interview with Grammy.com. "If there's an AI voice singing the song or AI instrumentation, we'll consider it. But in a songwriting-based category, it has to have been written mostly by a human. Same goes for performance categories – only a human performer can be considered for a Grammy. If AI did the songwriting or created the music, that's a different consideration. But the Grammy will go to human creators at this point."

A tourist submersible taking passengers down to the Titanic wreck site has gone missing with a search currently underway. Former Navy submariner Bryan Clark joins'Fox & Friends' to discuss. The Titan submarine OceanGate has been charging tourists around $250,000 each to ride in is operated by an inexpensive video game controller, its CEO revealed in a video interview last year. Stockton Rush, during a segment aired by "CBS Sunday Morning," said "we run the whole thing with this game controller" while holding up what appears to be a modified Logitech F710 wireless gamepad. The device first debuted in 2011, according to the gaming website Dexerto, and a refurbished version of it currently retails for $30 on Amazon.

There are three problems existing in the popular data-to-text datasets. First, the large-scale datasets either contain noise or lack real application scenarios. Second, the datasets close to real applications are relatively small in size. Last, current datasets bias in the English language while leaving other languages underexplored. To alleviate these limitations, in this paper, we present CATS, a pragmatic Chinese answer-to-sequence dataset with large scale and high quality. The dataset aims to generate textual descriptions for the answer in the practical TableQA system. Further, to bridge the structural gap between the input SQL and table and establish better semantic alignments, we propose a Unified Graph Transformation approach to establish a joint encoding space for the two hybrid knowledge resources and convert this task to a graph-to-text problem. The experiment results demonstrate the effectiveness of our proposed method. Further analysis on CATS attests to both the high quality and challenges of the dataset.

Although it has potential to support English as a foreign language (EFL) students' writing, to effectively collaborate with it, a student must learn to engineer prompts, that is, the skill of crafting appropriate instructions so that ChatGPT produces desired outputs. However, writing an appropriate prompt for ChatGPT is not straightforward for non-technical users who suffer a trial-and-error process. This paper examines the content of EFL students' ChatGPT prompts when completing a writing task and explores patterns in the quality and quantity of the prompts. The data come from iPad screen recordings of secondary school EFL students who used ChatGPT and other SOTA chatbots for the first time to complete the same writing task. The paper presents a case study of four distinct pathways that illustrate the trial-and-error process and show different combinations of prompt content and quantity. The cases contribute evidence for the need to provide prompt engineering education in the context of the EFL writing classroom, if students are to move beyond an individual trial-anderror process, learning a greater variety of prompt content and more sophisticated prompts to support their writing. Keywords: artificial intelligence; chatbots; prompt engineering; writing; case study; ChatGPT 1. Introduction ChatGPT's incredible popularity indicates many people's desire to transform their world of education, work and leisure through chatbots. Previously, chatbots followed a rule-based design with limited capabilities to respond accurately to user queries, especially with unfamiliar inputs.

Astronaut Sally Ride became the first American woman in space on this day in history, June 18, 1983. Born on May 26, 1951, in Los Angeles, Ride earned bachelor's degrees in English and physics from Stanford University in California before staying at Stanford and earning a PhD in physics in 1978. Shortly before earning her doctorate, Ride saw an ad for a newspaper that piqued her interest. NASA was recruiting for astronauts -- and, for the first time, the agency would include women in its astronaut class. "Over 8,000 men and women applied to the space program that year. Of the 35 individuals accepted, six were women, and I was one of them. This was in January 1978," said Ride in quotes listed on a tribute page on NASA's website.

In recent years, discussions of responsible AI practices have seen growing support for "participatory AI" approaches, intended to involve members of the public in the design and development of AI systems. Prior research has identified a lack of standardised methods or approaches for how to use participatory approaches in the AI development process. At present, there is a dearth of evidence on attitudes to and approaches for participation in the sites driving major AI developments: commercial AI labs. Through 12 semi-structured interviews with industry practitioners and subject-matter experts, this paper explores how commercial AI labs understand participatory AI approaches and the obstacles they have faced implementing these practices in the development of AI systems and research. We find that while interviewees view participation as a normative project that helps achieve "societally beneficial" AI systems, practitioners face numerous barriers to embedding participatory approaches in their companies: participation is expensive and resource intensive, it is "atomised" within companies, there is concern about exploitation, there is no incentive to be transparent about its adoption, and it is complicated by a lack of clear context. These barriers result in a piecemeal approach to participation that confers no decision-making power to participants and has little ongoing impact for AI labs. This papers contribution is to provide novel empirical research on the implementation of public participation in commercial AI labs, and shed light on the current challenges of using participatory approaches in this context.

A Russian soldier was seen surrendering to a Ukrainian drone May 9 in edited video released by Ukraine's 92nd Mechanized Brigade. A Russian soldier whose surrender to Ukrainian forces was captured on drone camera, spoke for the first time about his experience. Ruslan Anitin, a draftee who was cornered alone by the Ukrainian military near the city of Bakhmut, surrendered by communicating via an aerial drone's camera. "It felt like it was never going to involve us at all," Anitin said of the conflict during an interview with the Wall Street Journal about his experience. A Russian soldier was seen surrendering to a Ukrainian drone May 9 in edited video released by Ukraine's 92nd Mechanized Brigade.

There's no question that artificial intelligence is changing our lives. A bot that sounds almost human can author your emails, teach you a new language, book your trip,s or even be your friend. Check out direct links to try those out here. One woman I spoke with on my national radio show even married her AI companion. No kidding, she says he's the perfect partner.

John Rich shared his unfiltered opinions on the state of country music today and if AI would make it better or worse. John Rich is less concerned with the advancements in artificial intelligence than he is with the expansion of country music, questioning if the technology could produce better quality music than what country artists are releasing now. "Could AI do any worse than some of the country singers that are out there right now?" Rich wondered during an interview with Fox News Digital, without naming names. One thing's for sure, according to Rich: AI has nothing on the legends. "Listen, you can't replicate the great songwriters. I mean, you're talking about Albert Einstein honky-tonk songwriters."

Using 52K self-instruct demonstrations, LLaMA-Adapter only introduces 1.2M learnable parameters upon the frozen LLaMA 7B model, and costs less than one hour for fine-tuning on 8 A100 GPUs. Specifically, we adopt a set of learnable adaption prompts, and prepend them to the word tokens at higher transformer layers. Then, a zero-initialized attention mechanism with zero gating is proposed, which adaptively injects the new instructional cues into LLaMA, while effectively preserves its pre-trained knowledge. With our efficient training, LLaMA-Adapter can generate high-quality responses, comparable to Alpaca with fully fine-tuned 7B parameters. Besides language commands, our approach can be simply extended to multi-modal instructions for learning image-conditioned LLaMA model, which achieves superior reasoning performance on ScienceQA and COCO Caption benchmarks. Furthermore, we also evaluate the zero-initialized attention mechanism for fine-tuning other pre-trained models (ViT, RoBERTa) on traditional vision and language tasks, demonstrating the superior generalization capacity of our approach.