Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library created to assist in the advancement of support knowing algorithms. It aimed to standardize how environments are defined in [AI](http://www.xn--he5bi2aboq18a.com) research study, making released research more quickly reproducible [24] [144] while offering users with an easy interface for interacting with these environments. In 2022, brand-new advancements of Gym have actually been relocated to the library Gymnasium. [145] [146]
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<br>Gym Retro<br>
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<br>Released in 2018, Gym Retro is a platform for support learning (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on optimizing agents to fix single jobs. Gym Retro offers the capability to generalize in between games with comparable principles but different looks.<br>
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<br>RoboSumo<br>
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<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents at first lack understanding of how to even stroll, however are offered the objectives of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the representatives discover how to adapt to [changing conditions](http://ufidahz.com.cn9015). When an agent is then gotten rid of from this [virtual environment](https://www.jobtalentagency.co.uk) and put in a new virtual environment with high winds, the representative braces to remain upright, recommending it had actually discovered how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents could produce an intelligence "arms race" that might increase an [agent's ability](http://ledok.cn3000) to operate even outside the context of the competitors. [148]
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<br>OpenAI 5<br>
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<br>OpenAI Five is a team of 5 OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that find out to play against human gamers at a high ability level entirely through trial-and-error algorithms. Before becoming a group of 5, the first public demonstration happened at The International 2017, the annual premiere championship competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually match. [150] [151] After the match, [CTO Greg](http://121.37.166.03000) Brockman explained that the bot had [learned](https://git.daviddgtnt.xyz) by playing against itself for two weeks of actual time, and that the knowing software application was a step in the instructions of creating software that can manage complicated tasks like a surgeon. [152] [153] The system utilizes a kind of reinforcement knowing, as the bots discover with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156]
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<br>By June 2018, the capability of the bots broadened to play together as a full group of 5, and they had the ability to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The [International](http://careers.egylifts.com) 2018, OpenAI Five played in two exhibit matches against professional gamers, however wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public look came later on that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those games. [165]
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<br>OpenAI 5's systems in Dota 2's bot player shows the challenges of [AI](http://easyoverseasnp.com) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually shown the use of deep reinforcement learning (DRL) representatives to attain superhuman competence in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl utilizes maker finding out to train a Shadow Hand, a human-like robotic hand, to [manipulate physical](http://120.79.211.1733000) things. [167] It discovers completely in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI took on the things orientation issue by utilizing domain randomization, a simulation technique which exposes the learner to a range of experiences rather than trying to fit to reality. The set-up for [yewiki.org](https://www.yewiki.org/User:LaraeBaxley2) Dactyl, aside from having motion tracking electronic cameras, likewise has [RGB cams](https://git.lodis.se) to enable the robot to control an approximate things by seeing it. In 2018, OpenAI showed that the system had the ability to control a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI showed that Dactyl might solve a [Rubik's Cube](http://betterlifenija.org.ng). The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce intricate physics that is harder to model. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of generating gradually harder environments. ADR differs from manual domain randomization by not needing a human to specify [randomization varieties](http://www.zjzhcn.com). [169]
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<br>API<br>
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<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](https://nojoom.net) designs developed by OpenAI" to let designers get in touch with it for "any English language [AI](https://git.epochteca.com) job". [170] [171]
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<br>Text generation<br>
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<br>The company has promoted generative pretrained transformers (GPT). [172]
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<br>OpenAI's original GPT design ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his associates, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world understanding and process long-range reliances by pre-training on a diverse corpus with long stretches of contiguous text.<br>
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<br>GPT-2<br>
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<br>Generative Pre-trained Transformer 2 ("GPT-2") is an [unsupervised](https://www.celest-interim.fr) transformer language design and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative variations initially released to the general public. The full version of GPT-2 was not right away launched due to concern about potential abuse, including applications for writing phony news. [174] Some professionals expressed uncertainty that GPT-2 positioned a significant threat.<br>
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<br>In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural fake news". [175] Other scientists, such as Jeremy Howard, cautioned of "the innovation to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the total variation of the GPT-2 language design. [177] Several websites host interactive demonstrations of various circumstances of GPT-2 and other transformer models. [178] [179] [180]
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<br>GPT-2's authors argue unsupervised language designs to be general-purpose learners, highlighted by GPT-2 attaining advanced precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not more trained on any task-specific input-output examples).<br>
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<br>The corpus it was trained on, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both individual characters and multiple-character tokens. [181]
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<br>GPT-3<br>
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<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language model and the [follower](https://www.jobs-f.com) to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion criteria, [184] two orders of magnitude larger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 designs with as few as 125 million specifications were also trained). [186]
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<br>OpenAI specified that GPT-3 prospered at certain "meta-learning" jobs and could generalize the function of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer knowing in between English and Romanian, and in between [English](https://radi8tv.com) and German. [184]
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<br>GPT-3 significantly enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or [experiencing](https://gitea.shoulin.net) the fundamental ability constraints of predictive language models. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not right away released to the public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month [totally free](http://lnsbr-tech.com) personal beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed solely to Microsoft. [190] [191]
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<br>Codex<br>
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<br>Announced in mid-2021, Codex is a [descendant](http://115.29.202.2468888) of GPT-3 that has actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://114.55.171.231:3000) powering the code autocompletion tool GitHub [Copilot](https://www.jobtalentagency.co.uk). [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the design can create working code in over a lots programs languages, [wiki.asexuality.org](https://wiki.asexuality.org/w/index.php?title=User_talk:MatthiasDoughart) a lot of effectively in Python. [192]
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<br>Several problems with problems, design flaws and security vulnerabilities were cited. [195] [196]
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<br>GitHub Copilot has been implicated of producing copyrighted code, without any author [attribution](http://blueroses.top8888) or license. [197]
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<br>OpenAI revealed that they would discontinue assistance for Codex API on March 23, 2023. [198]
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<br>GPT-4<br>
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<br>On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They revealed that the updated innovation passed a simulated law school bar exam with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could likewise check out, analyze or create approximately 25,000 words of text, and write code in all significant programs languages. [200]
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<br>Observers reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained some of the problems with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal different technical details and statistics about GPT-4, such as the exact size of the design. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, OpenAI revealed and released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision criteria, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) benchmark compared to 86.5% by GPT-4. [207]
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller version of GPT-4o changing GPT-3.5 Turbo on the ChatGPT interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI expects it to be especially useful for business, startups and designers looking for to automate services with [AI](https://gogs.tyduyong.com) representatives. [208]
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<br>o1<br>
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<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have been developed to take more time to think of their reactions, causing higher accuracy. These designs are especially reliable in science, coding, and reasoning jobs, and were made available to [ChatGPT](https://rassi.tv) Plus and Staff member. [209] [210] In December 2024, o1-preview was changed by o1. [211]
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<br>o3<br>
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<br>On December 20, 2024, OpenAI unveiled o3, the follower of the o1 reasoning design. OpenAI likewise unveiled o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this design is not available for public usage. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the [opportunity](https://www.atlantistechnical.com) to obtain early access to these models. [214] The design is called o3 instead of o2 to avoid confusion with telecommunications providers O2. [215]
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<br>Deep research<br>
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<br>Deep research is a representative established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to perform comprehensive web surfing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools enabled, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120]
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<br>Image classification<br>
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<br>CLIP<br>
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<br>Revealed in 2021, CLIP ([Contrastive Language-Image](https://kommunalwiki.boell.de) Pre-training) is a model that is trained to examine the semantic similarity in between text and images. It can significantly be used for image classification. [217]
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<br>Text-to-image<br>
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<br>DALL-E<br>
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<br>Revealed in 2021, DALL-E is a Transformer model that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and generate corresponding images. It can create images of practical things ("a stained-glass window with an image of a blue strawberry") along with objects that do not exist in truth ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.<br>
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<br>DALL-E 2<br>
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<br>In April 2022, OpenAI announced DALL-E 2, an upgraded version of the design with more [practical](https://hilife2b.com) results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new primary system for converting a text description into a 3-dimensional design. [220]
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<br>DALL-E 3<br>
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<br>In September 2023, OpenAI announced DALL-E 3, a more powerful design better able to generate images from complicated descriptions without manual timely engineering and render complicated details like hands and text. [221] It was released to the public as a ChatGPT Plus feature in October. [222]
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<br>Text-to-video<br>
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<br>Sora<br>
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<br>Sora is a text-to-video design that can produce videos based upon prompts [223] in addition to extend existing videos forwards or backwards in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of produced videos is unidentified.<br>
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<br>Sora's advancement group called it after the Japanese word for "sky", to [symbolize](https://wiki.uqm.stack.nl) its "limitless imaginative potential". [223] Sora's innovation is an adaptation of the innovation behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos certified for that function, but did not expose the number or the specific sources of the videos. [223]
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<br>[OpenAI demonstrated](http://git.daiss.work) some Sora-created high-definition videos to the public on February 15, 2024, specifying that it might generate videos as much as one minute long. It also shared a technical report highlighting the methods used to train the design, and the model's capabilities. [225] It [acknowledged](https://jobportal.kernel.sa) some of its imperfections, including struggles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", but kept in mind that they need to have been cherry-picked and may not represent Sora's normal output. [225]
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<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have actually revealed considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's ability to produce practical video from text descriptions, citing its prospective to reinvent storytelling and [pipewiki.org](https://pipewiki.org/wiki/index.php/User:TOUJocelyn) content production. He said that his enjoyment about Sora's possibilities was so strong that he had chosen to stop briefly prepare for broadening his Atlanta-based motion picture studio. [227]
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<br>Speech-to-text<br>
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<br>Whisper<br>
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<br>Released in 2022, Whisper is a general-purpose speech [acknowledgment](https://aggm.bz) model. [228] It is trained on a large dataset of varied audio and is also a multi-task design that can perform multilingual speech acknowledgment in addition to speech translation and language identification. [229]
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<br>Music generation<br>
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<br>MuseNet<br>
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<br>Released in 2019, MuseNet is a deep neural net trained to [predict subsequent](https://origintraffic.com) musical notes in MIDI music files. It can generate songs with 10 instruments in 15 styles. According to The Verge, a song created by [MuseNet](http://120.77.213.1393389) tends to begin fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the internet mental thriller Ben Drowned to develop music for the titular character. [232] [233]
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<br>Jukebox<br>
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<br>Released in 2020, Jukebox is an open-sourced algorithm to produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs song samples. OpenAI stated the tunes "reveal regional musical coherence [and] follow traditional chord patterns" but acknowledged that the songs do not have "familiar larger musical structures such as choruses that duplicate" which "there is a considerable space" between Jukebox and [human-generated music](https://nakshetra.com.np). The Verge mentioned "It's highly outstanding, even if the outcomes sound like mushy versions of tunes that might feel familiar", while Business Insider specified "surprisingly, a few of the resulting tunes are catchy and sound legitimate". [234] [235] [236]
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<br>Interface<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI released the Debate Game, which teaches makers to discuss toy issues in front of a human judge. The function is to research whether such a method may help in auditing [AI](https://realestate.kctech.com.np) choices and in establishing explainable [AI](https://wiki.dulovic.tech). [237] [238]
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<br>Microscope<br>
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<br>Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of eight neural network designs which are often studied in interpretability. [240] Microscope was created to examine the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various variations of Inception, and different [variations](http://connect.lankung.com) of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, ChatGPT is an artificial intelligence tool developed on top of GPT-3 that offers a conversational user interface that enables users to ask questions in natural language. The system then reacts with a response within seconds.<br>
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