These battery-powered kicks can increase walking speeds by a whopping 250%, Kurt "The CyberGuy" Knutsson reports. Are you tired of walking at a sluggish pace while everyone else zooms past you? Well, buckle up your shoe game because we have news that will knock your socks off. An innovation in the world of footwear has arrived - shoes that can make you walk 250% faster. Yes, you read that right, these shoes will have you blazing past everyone else on the street faster than you can say, "where can I get a pair?"

Image harmonization is a critical task in computer vision, which aims to adjust the foreground to make it compatible with the background. Recent works mainly focus on using global transformations (i.e., normalization and color curve rendering) to achieve visual consistency. However, these models ignore local visual consistency and their huge model sizes limit their harmonization ability on edge devices. In this paper, we propose a hierarchical dynamic network (HDNet) to adapt features from local to global view for better feature transformation in efficient image harmonization. Inspired by the success of various dynamic models, local dynamic (LD) module and mask-aware global dynamic (MGD) module are proposed in this paper. Specifically, LD matches local representations between the foreground and background regions based on semantic similarities, then adaptively adjust every foreground local representation according to the appearance of its $K$-nearest neighbor background regions. In this way, LD can produce more realistic images at a more fine-grained level, and simultaneously enjoy the characteristic of semantic alignment. The MGD effectively applies distinct convolution to the foreground and background, learning the representations of foreground and background regions as well as their correlations to the global harmonization, facilitating local visual consistency for the images much more efficiently. Experimental results demonstrate that the proposed HDNet significantly reduces the total model parameters by more than 80\% compared to previous methods, while still attaining state-of-the-art performance on the popular iHarmony4 dataset. Notably, the HDNet achieves a 4\% improvement in PSNR and a 19\% reduction in MSE compared to the prior state-of-the-art methods.

Named-entity recognition (NER) detects texts with predefined semantic labels and is an essential building block for natural language processing (NLP). Notably, recent NER research focuses on utilizing massive extra data, including pre-training corpora and incorporating search engines. However, these methods suffer from high costs associated with data collection and pre-training, and additional training process of the retrieved data from search engines. To address the above challenges, we completely frame NER as a machine reading comprehension (MRC) problem, called NER-to-MRC, by leveraging MRC with its ability to exploit existing data efficiently. Several prior works have been dedicated to employing MRC-based solutions for tackling the NER problem, several challenges persist: i) the reliance on manually designed prompts; ii) the limited MRC approaches to data reconstruction, which fails to achieve performance on par with methods utilizing extensive additional data. Thus, our NER-to-MRC conversion consists of two components: i) transform the NER task into a form suitable for the model to solve with MRC in a efficient manner; ii) apply the MRC reasoning strategy to the model. We experiment on 6 benchmark datasets from three domains and achieve state-of-the-art performance without external data, up to 11.24% improvement on the WNUT-16 dataset.

We tackle the problem of joint frequency and power allocation while emphasizing the generalization capability of a deep reinforcement learning model. Most of the existing methods solve reinforcement learning-based wireless problems for a specific pre-determined wireless network scenario. The performance of a trained agent tends to be very specific to the network and deteriorates when used in a different network operating scenario (e.g., different in size, neighborhood, and mobility, among others). We demonstrate our approach to enhance training to enable a higher generalization capability during inference of the deployed model in a distributed multi-agent setting in a hostile jamming environment. With all these, we show the improved training and inference performance of the proposed methods when tested on previously unseen simulated wireless networks of different sizes and architectures. More importantly, to prove practical impact, the end-to-end solution was implemented on the embedded software-defined radio and validated using over-the-air evaluation.

American rapper Snoop Dogg expressed confusion about recent developments in artificial intelligence, comparing the technology to movies he saw as a child. At the Milken Institute Global Conference in Beverly Hills this week, Snoop, whose given name is Calvin Broadus, turned his focus to artificial intelligence while discussing a strike of the Writers Guild of America. The writers strike is, in part, about the potential for artificial intelligence to take writing jobs. "I got a motherf---ing AI right now that they did made for me," Snoop said. "This n----- could talk to me. I'm like, man, this thing can hold a real conversation? Like it's blowing my mind because I watched movies on this as a kid years ago."

PETA has given the Bible's Book of Genesis a "vegan" makeover, using ChatGPT to recreate the story and "send a can't-be-missed animal rights message filled with vegan teachings." In PETA's vegan version of the Bible, animals are referred to as "beings" rather than "beasts" or "creatures" and plants like hemp and bamboo are used for clothing instead of animal skins because "no one with any fashion or moral sense would wear animal skins in the 21st century." Volunteers serve vegan hot dogs at the PETA Congressional Veggie Dog Lunch outside the Longworth House Office Building July 21, 2021 in Washington, DC. (Win McNamee/Getty Images) "The Bible has long been used to justify all forms of oppression, so we've used ChatGPT to make it clear that a loving God would never endorse exploitation of or cruelty to animals," says PETA President Ingrid Newkirk. "It took God only six days to create the entire world, but we realized it would take us years to rewrite the whole Bible, which is why we've started with just the first book." PETA OFFERS TO PAY FOR OSCAR MAYER WIENERMOBILE'S STOLEN CATALYTIC CONVERTER IF IT BECOMES VEGAN MOBILE In Genesis Chapter 22, Abraham travels to the land of Moriah, where instead of slaughtering a ram to demonstrate his faith, he "befriends a gentle lamb to show his reverence and respect for God's creation."

Kurt "The CyberGuy" Knutsson explains how an AI-generated radio DJ powered by the latest ChatGPT-4 technology can service across radio stations in the U.S. and Canada. ChatGPT has done it once again. The AI-powered chatbot is seemingly the answer to all. From assisting students with study materials to helping Twitter engineers with code corrections, ChatGPT has become a reliable source of information and assistance. Some preachers have even turned to ChatGPT for help in writing sermons.

The rapid progress in artificial intelligence in recent months is partly due to training on vast data sets of text and images, scraped for free from the internet. Although automated web scraping by search engines has been accepted by website owners for decades, the economic shift being brought about by AI has triggered a rethink.

Luddites had the right of things all the way back in the 1800s. When textile factory owners in early 19th century England used the industrialization of their industry as an excuse to underpay and overwork employees in dangerous, dehumanizing conditions, the secret organization of workers set about smashing the machines of the capitalists who exploited them. Today, the Writers' Guild of America faces a similar threat from those in control of a new transformative technology, generative AI, and it's part of the reason they're currently on strike for better working conditions. On March 7, 2023, WGA members voted to approve the 2023 Pattern of Demands by a count of 5,553 voting yes to 90 no's. On Tuesday morning, more than 11,000 members of the Writers Guild of America shut Hollywood down for the first time since 2007 when they last had to fight for their livelihoods.

The Monitor is a weekly column devoted to everything happening in the WIRED world of culture, from movies to memes, TV to Twitter. Earlier this week, on the red (technically striped) carpet of the Met Gala, The Dropout star Amanda Seyfried answered a tough question: What did she think about the then-impending Writers Guild of America strike? Wearing an elegant Oscar de La Renta dress made with 80,000 gold and platinum bugle beads, she told a Variety reporter that everything she'd heard from writer friends indicated they would picket if they couldn't reach an agreement with the Alliance of Motion Picture and Television Producers. Poised, draped in priceless garments and jewels, she remained firm. "I don't get what the problem is," she said.