Audio editing is applicable for various purposes, such as adding background sound effects, replacing a musical instrument, and repairing damaged audio. Recently, some diffusion-based methods achieved zero-shot audio editing by using a diffusion and denoising process conditioned on the text description of the output audio. However, these methods still have some problems: 1) they have not been trained on editing tasks and cannot ensure good editing effects; 2) they can erroneously modify audio segments that do not require editing; 3) they need a complete description of the output audio, which is not always available or necessary in practical scenarios. In this work, we propose AUDIT, an instruction-guided audio editing model based on latent diffusion models. Specifically, AUDIT has three main design features: 1) we construct triplet training data (instruction, input audio, output audio) for different audio editing tasks and train a diffusion model using instruction and input (to be edited) audio as conditions and generating output (edited) audio; 2) it can automatically learn to only modify segments that need to be edited by comparing the difference between the input and output audio; 3) it only needs edit instructions instead of full target audio descriptions as text input. AUDIT achieves state-of-the-art results in both objective and subjective metrics for several audio editing tasks (e.g., adding, dropping, replacement, inpainting, super-resolution). Demo samples are available at https://audit-demo.github.io/.

In this paper, we study the problem of claim verification in the context of claims about fictional stories in a low-shot learning setting. To this end, we generate two synthetic datasets and then develop an end-to-end pipeline and model that is tested on both benchmarks. To test the efficacy of our pipeline and the difficulty of benchmarks, we compare our models' results against human and random assignment results. Our code is available at https://github.com/Derposoft/plot_hole_detection.

FOX Business correspondent Lydia Hu has the latest on jobs at risk as AI further develops on'America's Newsroom.' A recent experiment from a research team at BYU examined the ways in which artificial intelligence can predict how different demographics will vote in elections. The study – conducted by a team of political and computer science professors and graduate students at BYU – examined ways in which AI could be used as a substitute for human responders in survey-style research. ChatGPT 4 displayed on smartphone with OpenAI logo seen on screen in the background, in Brussels, Belgium. To see whether this was possible, the team tested the accuracy of programmed algorithms of a GPT-3 model, which mimics the relationship between human ideas, attitudes and sociocultural contexts of various demographics.

Our reverence towards stars and celebrities was not borne of the 19th century's cinematic revolution, but rather has been a resilient aspect of our culture for millennia. Ancient tales of immortal gods rising again and again after fatal injury, the veneration and deification of social and political leaders, Madame Tussauds' wax museums and the Academy Awards' annual In Memoriam segment, they're are all facets of the human compulsion to put well-known thought leaders, tastemakers and trendsetters up on pedestals. And with a new, startlingly lifelike generation of generative artificial intelligence (gen-AI) at our disposal, today's celebrities could potentially remain with us long after their natural deaths. American Historian Daniel Boorstin once quipped, "to be famous is to be well known for being well-known." With the rise of social media, achieving celebrity is now easier than ever, for better or worse.

In this document, we offer a review of recent literature on the future of work. This review was commissioned by The Alan Turing Institute for the purpose of informing the Institute's research strategy aiming to further data science and artificial intelligence research to address real-world problems. The second section addresses potential drivers of the changing nature of work; disparate impacts of technology on different tasks; challenges for young people to boost employability; impacts of the changing nature of work on the disenfranchised; and proposals for policies and governance models to manage the transitions related to the future of work.

And nowhere is that more true than in photography. I've certainly had fun with it on more than my share of photos. But the more I attempt to be a "serious" photographer, the less I want to rely on artificial intelligence to do my job for me. That's not to say it doesn't have its place. And AI certainly has its place in the world of art. A recent encounter with the "Neural filters" in Adobe Photoshop has me rethinking things a little, though.

Fox News correspondent Matt Finn has the latest on the impact of AI technology that some say could outpace humans on'Special Report.' Former Google CEO Eric Schmidt said the tech industry will face a "reckoning" over artificial intelligence, comparing the potential dangers of the technology to the risks associated with social media when the platforms were first rolled out years ago. "What happened with social media is we, including myself, just offered social media because we had a simple model of how humans would use social media. But, instead, look at how social media was used to interfere in elections, to cause harm. People have died over social media," Schmidt told ABC News on Sunday.

Anyone who stares at a screen all day probably doesn't want to do so when they unwind with a book. But the convenience of getting a new read instantaneously and carrying a full bookcase in your pocket is pretty appealing. Ereaders combine the best of paper and computers, and they're capable of storing dozens of books at a time. Amazon dominates in this market, but that doesn't mean there aren't worthy competitors. We tested out some of the best ereaders available to help you find which is right for you. Plenty of apps will let you download and read a novel on a phone or tablet. What makes ereaders different is the screen: nearly all of them use technology from a company called E Ink. It manufactures electronic paper displays (EPD) composed of three sheets: one containing millions of microcapsules filled with black and white ink particles sandwiched between transparent electrode layers.

Subscribe now to get Fox News First in your email. And here's what you need to know to start your day ... BEHIND CLOSED DOORS - Judge presiding over Trump arraignment makes decision on live cameras in courtroom. Continue reading … 'A JOKE' - LSU women's basketball star Angel Reese laughs off Jill Biden's White House wish. 'UNACCEPTABLE' - Dem lawmakers lose committee assignments after storming state capitol building. SHOW OF SUPPORT - Fans send actor well wishes after he reveals he's high-risk for Alzheimer's.

Rewards play a crucial role in reinforcement learning (RL). A good choice of reward function motivates an agent to explore and learn which actions are valuable. The feedback that an agent receives via rewards allows them to update their behavior and learn useful policies. However, designing reward functions is complicated and cumbersome, even for domain experts. Automatically inferring a reward function is more desirable for end-users interacting with a system.