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Romania braces for parliamentary vote after far right's poll upsetSeafood industry awaits TrumpEnter the World of 'Solo Leveling: Unlimited (SL:U)': Where Hunters Become Collectors 12-23-2024 10:48 PM CET | Sports Press release from: Getnews / PR Agency: ViralPunch Build Your Shadow Army: Collect, Upgrade, and Rise to Power in the World of Solo Leveling Image: https://www.globalnewslines.com/uploads/2024/12/76d281964044b30ef0fb46910e78fced.jpg Otherworld will launch "Solo Leveling: Unlimited (SL:U)", a digital collectible platform, and open its first season 'Prologue' to the public on December 23. This platform, based on the globally popular Korean webtoon "Solo Leveling", which has amassed over 14.3 billion cumulative views worldwide. The collectibles platform will operate on the Space Network, an independently constructed Layer 1 (L1) blockchain by OtherWorld, built on Avalanche. SL:U faithfully integrates the original storyline, characters, and style of the webtoon into a digital collectible platform. The immersive experience mirrors the protagonist's journey of opening dungeon gates, hunting monsters, and leveling up. Designed to captivate both existing fans and new users, the platform preserves the essence of the original story. Originally a web novel published in 2016, Solo Leveling gained worldwide acclaim as a webtoon before expanding into animations and games. Known for its unique narrative and compelling characters, the series has been a flagship title representing Korean webtoons globally, with a strong fanbase in regions such as North America and Japan. SL:U is an Interactive Collection and Reward System (C2E: Collect to Earn). SL:U offers a unique twist on collectible card experiences where collectors can open dungeon gates to acquire monster cards and uniquely power them up through upgrades. The platform rewards dedicated users with weekly rewards for those who successfully upgrade their card collections and exclusive Shadow Monarchs (NFTs) for top-ranking collectors each season. Built on blockchain technology, our reward system ensures complete transparency in distribution, eliminating common concerns about unclear reward mechanisms or manipulated algorithms found in traditional digital platforms. While Otherworld has incorporated blockchain technology, it aims to provide services that are user-friendly for the general public. SL:U offers login capabilities through familiar social media accounts, along with convenient payment options including easy payment systems and credit card transactions. Traditional blockchain services have presented barriers with their requirement for blockchain wallet logins and cryptocurrency payments for transactions, creating significant hurdles for mainstream users. These complications often discourage potential users from engaging with such services. To address these challenges, Otherworld collaborates with Crossmint to provide a seamless user experience that eliminates these traditional barriers to entry. Otherworld has built its own Layer 1 Space Network, but the platform isn't limited to a single blockchain. Through partnerships with Nestree and LayerZero, users can freely move their tokens and NFTs across different networks using the Nestree Bridge. This enables quick and flexible asset transfers between blockchains. To target the global market, SL:U has announced a range of partnerships. Joint marketing efforts with Animoca Brands Animation Foundation are in the works, while collaboration with popular Korean cosmetics brand VT-Cosmetic will feature a product lineup incorporating NFTs. The OWN Token, Otherworld's native cryptocurrency, will soon be added as a payment option in SL:U and is expected to gain broader utility across various platforms starting with this initiative. Otherworld holds exclusive Web3 business rights for 26 IPs from popular Kakao Page webtoons, including Solo Leveling and Ranker Who Lives a Second Time. The company plans to acquire more IPs to blur the boundaries between Web2 and Web3, further expanding digital content universes. It also aims to create an NFT-driven ecosystem for K-pop fans through a partnership with Cube Entertainment, utilizing K-pop artist IPs. Media Contact Company Name: Otherworld Contact Person: Mike Lee Email: Send Email [ http://www.universalpressrelease.com/?pr=enter-the-world-of-solo-leveling-unlimited-slu-where-hunters-become-collectors ] Country: South Korea Website: https://sololeveling.space This release was published on openPR.
Busy schedule gives Packers no time to celebrate their lopsided win over 49ersDutch police find gnome made of MDMA during drug bustNovember 25, 2024 This article has been reviewed according to Science X's editorial process and policies . Editors have highlightedthe following attributes while ensuring the content's credibility: fact-checked trusted source proofread by Jennifer Chu, Massachusetts Institute of Technology Visualizing the potential impacts of a hurricane on people's homes before it hits can help residents prepare and decide whether to evacuate. MIT scientists have developed a method that generates satellite imagery from the future to depict how a region would look after a potential flooding event. The method combines a generative artificial intelligence model with a physics-based flood model to create realistic, birds-eye-view images of a region, showing where flooding is likely to occur given the strength of an oncoming storm. The work is published in the journal IEEE Transactions on Geoscience and Remote Sensing . As a test case, the team applied the method to Houston and generated satellite images depicting what certain locations around the city would look like after a storm comparable to Hurricane Harvey, which hit the region in 2017. The team compared these generated images with actual satellite images taken of the same regions after Harvey hit. They also compared AI-generated images that did not include a physics-based flood model. The team's physics-reinforced method generated satellite images of future flooding that were more realistic and accurate. The AI-only method, in contrast, generated images of flooding in places where flooding is not physically possible. The team's method is a proof-of-concept, meant to demonstrate a case in which generative AI models can generate realistic, trustworthy content when paired with a physics-based model. In order to apply the method to other regions to depict flooding from future storms, it will need to be trained on many more satellite images to learn how flooding would look in other regions. "The idea is: One day, we could use this before a hurricane, where it provides an additional visualization layer for the public," says Björn Lütjens, a postdoc in MIT's Department of Earth, Atmospheric and Planetary Sciences, who led the research while he was a doctoral student in MIT's Department of Aeronautics and Astronautics (AeroAstro). "One of the biggest challenges is encouraging people to evacuate when they are at risk. Maybe this could be another visualization to help increase that readiness." To illustrate the potential of the new method, which they have dubbed the "Earth Intelligence Engine," the team has made it available as an online resource for others to try. The study's MIT co-authors include Brandon Leshchinskiy; Aruna Sankaranarayanan; and Dava Newman, professor of AeroAstro and director of the MIT Media Lab; along with collaborators from multiple institutions. Generative adversarial images The new study is an extension of the team's efforts to apply generative AI tools to visualize future climate scenarios. "Providing a hyper-local perspective of climate seems to be the most effective way to communicate our scientific results ," says Newman, the study's senior author. "People relate to their own ZIP code, their local environment where their family and friends live. Providing local climate simulations becomes intuitive, personal, and relatable." For this study, the authors used a conditional generative adversarial network, or GAN, a type of machine learning method that can generate realistic images using two competing ("adversarial") neural networks. The first "generator" network is trained on pairs of real data, such as satellite images before and after a hurricane. The second "discriminator" network is then trained to distinguish between the real satellite imagery and the one synthesized by the first network. Each network automatically improves its performance based on feedback from the other network. The idea, then, is that such an adversarial push and pull should ultimately produce synthetic images that are indistinguishable from the real thing. Nevertheless, GANs can still produce "hallucinations," or factually incorrect features in an otherwise realistic image that shouldn't be there. "Hallucinations can mislead viewers," says Lütjens, who began to wonder whether such hallucinations could be avoided, such that generative AI tools can be trusted to help inform people, particularly in risk-sensitive scenarios. "We were thinking: How can we use these generative AI models in a climate-impact setting, where having trusted data sources is so important?" Discover the latest in science, tech, and space with over 100,000 subscribers who rely on Phys.org for daily insights. Sign up for our free newsletter and get updates on breakthroughs, innovations, and research that matter— daily or weekly . Flood hallucinations In their new work, the researchers considered a risk-sensitive scenario in which generative AI is tasked with creating satellite images of future flooding that could be trustworthy enough to inform decisions of how to prepare and potentially evacuate people out of harm's way. Typically, policymakers can get an idea of where flooding might occur based on visualizations in the form of color-coded maps. These maps are the final product of a pipeline of physical models that usually begins with a hurricane track model, which then feeds into a wind model that simulates the pattern and strength of winds over a local region. This is combined with a flood or storm surge model that forecasts how wind might push any nearby body of water onto land. A hydraulic model then maps out where flooding will occur based on the local flood infrastructure and generates a visual, color-coded map of flood elevations over a particular region. "The question is: Can visualizations of satellite imagery add another level to this, that is a bit more tangible and emotionally engaging than a color-coded map of reds, yellows, and blues, while still being trustworthy?" Lütjens says. The team first tested how generative AI alone would produce satellite images of future flooding. They trained a GAN on actual satellite images taken by satellites as they passed over Houston before and after Hurricane Harvey. When they tasked the generator to produce new flood images of the same regions, they found that the images resembled typical satellite imagery , but a closer look revealed hallucinations in some images, in the form of floods where flooding should not be possible (for instance, in locations at higher elevation). To reduce hallucinations and increase the trustworthiness of the AI-generated images, the team paired the GAN with a physics-based flood model that incorporates real, physical parameters and phenomena, such as an approaching hurricane's trajectory, storm surge, and flood patterns. With this physics-reinforced method, the team generated satellite images around Houston that depict the same flood extent, pixel by pixel, as forecasted by the flood model . "We show a tangible way to combine machine learning with physics for a use case that's risk-sensitive, which requires us to analyze the complexity of Earth's systems and project future actions and possible scenarios to keep people out of harm's way," Newman says. "We can't wait to get our generative AI tools into the hands of decisionmakers at the local community level, which could make a significant difference and perhaps save lives." More information: Björn Lütjens et al, Generating Physically-Consistent Satellite Imagery for Climate Visualizations, IEEE Transactions on Geoscience and Remote Sensing (2024). DOI: 10.1109/TGRS.2024.3493763 Click the link for the Earth Intelligence Engine tool . Provided by Massachusetts Institute of Technology This story is republished courtesy of MIT News ( web.mit.edu/newsoffice/ ), a popular site that covers news about MIT research, innovation and teaching.
By Haleluya Hadero | The Associated Press Amazon has introduced a handful of robots in its warehouses that the e-commerce giant says will improve efficiency and reduce employee injuries . Two robotic arms named Robin and Cardinal can lift packages that weigh up to 50 pounds. A third, called Sparrow, picks up items from bins and puts them in other containers. Proteus, an autonomous mobile robot that operates on the floor, can move carts around a warehouse. The bipedal, humanoid robot Digit is being tested to help move empty totes with its hands. And there’s also Sequoia, a containerized storage system that can present totes to employees in a way that allows them to avoid stretching or squatting to grab inventory. Amazon says Robin is currently being used in dozens of warehouses. The others are in a testing stage or haven’t been rolled out widely. But the company says it’s already seeing benefits, such as reducing the time it takes to fulfill orders and helping employees avoid repetitive tasks. However, automation also carries drawbacks for workers , who would have to be retrained for new positions if the robots made their roles obsolete. In October, Amazon held an event at a Nashville, Tennessee, warehouse where the company had integrated some of the robots. The Associated Press spoke with Julie Mitchell, the director of Amazon’s robotic sortation technologies, about where the company hopes to go from here. The conversation has been edited for length and clarity. Q: When you’re working on robotics, how long does it typically take to roll out new technology? A: This journey that we’ve been on has taken a couple of years. Luckily for us, we’ve been at this for over a decade. So we have a lot of core technology that we can build on top of. We started these particular robots – Cardinal and Proteus – in this building in November 2022. We came in and began playing around with what it would look like to pack and move a production order. Less than two years later, we are at scale and shipping 70% of the items in this building through that robotics system. Q: So, two years? A: We talk about “build, test and scale” and that’s about a two-year cycle for us right now. Q: It’s challenging to build robots that can physically grab products. How does Amazon work through that? A: As you can probably imagine, we have so many items, so it’s an exceptional challenge. We rely on data and putting our first prototype in a real building, where we expose it to all the things we need it to do. Then we drive down all the reasons that it fails. We give it a lot of sample sizes in a very short period of time. For example, a couple of years ago, we launched our Robin robotics arm – a package manipulation robot – and we’re at 3 billion picks. So the ability to launch into our network, rapidly collect data, scale and iterate has enabled us to go fast. The challenge itself can be boiled down to three simple things: you need to perceive the scene, plan your motion and then execute. Today, those are three different parts of our system. Artificial intelligence is going to help us change all of that, and it’s going to be more outcome-driven, like asking it to pick up a bottle of water. We’re on the verge, so that’s why I’m personally excited to be here at the onset of generative AI and use it to dramatically improve the performance of our robotics. Q: How do you think about the impact of automation on Amazon’s workforce as you’re developing the technology? A: With the technology we’ve deployed here, we’re creating new roles for individuals that can acquire new skills to fulfill those roles. And these new skills are not something that is too difficult to achieve. You don’t need an engineering degree, Ph.D. or any really technical skills to support our robotics systems. We designed the systems so they’re easy to service and train on the job to be a reliability maintenance engineer. We are working backwards from the idea that we want to employ more skilled labor. These opportunities are obviously higher paid than the entry level jobs in our buildings. And partnering with MIT has helped us understand what matters most to our team as we’re deploying these technologies across our network. Q: Are you experiencing any challenges as you introduce these robots in your warehouses? A: Not in the adoption. We’re integrating it. But these are complex systems and this is the real world, so things go wrong. For example, we had bad weather due to the storms in the Southeast. When I look at the robotics systems data, I can tell the weather is bad outside because that dramatically affects how the ship dock works. When trucks don’t arrive on time or when they can’t leave, you see bottlenecks in the building in strange ways. Containers build up, we have to put them in different places, and then humans need to recover them. So communication between what our robotics system is doing and what we need employees in the building to do to recover is important. It’s a collaboration of automation and humans to deal with real-world problems. It’s not a matter of having robotics take over but making it one system of humans and robotics working together to accomplish the goal of shipping the product.
Former US President Bill Clinton, 78, rushed to hospital and undergoing testing
A recent clip from Korean TV show Abnormal Summit is quickly going viral. Men of different countries discussed the various taboos in their own cultures. A man from Canada discussed the topic of “mansplaining,” which is typically defined as “to explain something to a woman in a condescending way that assumes she has no knowledge about the topic.” Those from other countries, including the U.S., agreed that mansplaining is considered a taboo in their culture. However, when Korean host Sung Si Kyung addressed the topic, he had a different take on the subject. Listening to that, it seems like it would really annoy men, too. — Sung Si Kyung They continued by stating, “I have a voice, too.” The reaction from the other hosts quickly went viral as the moment gained massive attention on social media. The moment launched various viral tweets and reactions from netizens who were appalled. “That’s why your country’s population and fertility is dropping” ahh face pic.twitter.com/8iyWDu1gud — Supersipra (@Supersipra1) November 22, 2024 imagine being so misogynist you got white men stumped & speechless https://t.co/F00Qakx22B — sunny side up (@yuri4yuris) November 22, 2024 In the video, netizens pointed out the host’s speechless and baffled reaction as a relatable yet hilarious moment. 영상으로 보면 마크 표정 더어이없는게 보임 https://t.co/nuw2TMsXsV pic.twitter.com/8FBa4iDzyL — E (@E123ONE) November 22, 2024 “LOL, the mansplaining comes right out, insane lmao” “Sung Si Kyung should only use that mouth for singing. Seriously, his brain is hopeless.” “Mark’s expression says it all.” “Mark’s expression lmao” “The ultimate old-fashioned guy.” “Sung Si Kyung always says stuff like that lol” “Good, good. It’s spreading worldwide lol” “LOL, such a consistent person.” “The original tweet had an explanation about mansplaining, and there’s a mention of him mansplaining—made me laugh.” Check out the full Tweet below. Reactions of Korean men after hearing about "mansplaining" pic.twitter.com/B2TY06uaoB — Korean Men Archives (@KM__arch) November 22, 2024
