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 learning algorithms. It aimed to standardize how environments are specified in [AI](http://106.14.65.137) research study, making published research more quickly reproducible [24] [144] while offering users with an easy user interface for connecting with these [environments](https://git.rootfinlay.co.uk). 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 reinforcement knowing (RL) research on video games [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on enhancing agents to fix single jobs. Gym Retro gives the [ability](https://www.yozgatblog.com) to generalize in between video games with comparable concepts however 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 robotic representatives initially do not have understanding of how to even walk, however are given the goals of discovering to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the agents learn how to adapt to changing conditions. When an agent is then eliminated from this virtual environment and placed in a brand-new virtual environment with high winds, the representative braces to remain upright, recommending it had found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives could produce an intelligence "arms race" that could increase an agent's ability to work 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 group of 5 OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that learn to play against human players at a high ability level completely through [experimental](https://git.mxr612.top) algorithms. Before becoming a team of 5, the first public presentation occurred at The [International](https://www.tqmusic.cn) 2017, the yearly best championship tournament for the video game, where Dendi, an expert Ukrainian player, lost against a bot in a [live individually](https://video.etowns.ir) match. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for two weeks of actual time, which the learning software was an action in the direction of developing software application that can manage complex tasks like a surgeon. [152] [153] The system utilizes a kind of support knowing, as the bots find out gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an opponent and taking map objectives. [154] [155] [156]
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<br>By June 2018, the ability of the bots broadened to play together as a full group of 5, and they had the ability to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert gamers, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 overall video games in a four-day open online competition, winning 99.4% of those video games. [165]
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<br>OpenAI 5's mechanisms in Dota 2's bot gamer reveals the challenges of [AI](https://video.etowns.ir) systems in multiplayer online [battle arena](https://careers.cblsolutions.com) (MOBA) games and how OpenAI Five has actually shown making 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://123.56.247.1933000) items. [167] It finds out completely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation problem by utilizing domain randomization, a [simulation method](https://twoplustwoequal.com) which exposes the student to a variety of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking video cameras, likewise has RGB cameras to allow the robotic to control an approximate things by seeing it. In 2018, OpenAI revealed 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. The robot had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation method of creating gradually harder environments. ADR varies from manual domain randomization by not needing a human to define randomization ranges. [169]
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<br>API<br>
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<br>In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://gitea.elkerton.ca) designs developed by OpenAI" to let developers contact it for "any English language [AI](https://www.flytteogfragttilbud.dk) job". [170] [171]
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<br>Text generation<br>
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<br>The business has promoted generative pretrained transformers (GPT). [172]
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<br>[OpenAI's original](http://115.238.142.15820182) GPT model ("GPT-1")<br>
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<br>The original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world understanding and process long-range dependencies by pre-training on a varied corpus with long stretches of adjoining text.<br>
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<br>GPT-2<br>
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<br>Generative Pre-trained Transformer 2 ("GPT-2") is a without supervision transformer [language model](https://gitea.shoulin.net) and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative versions initially released to the public. The complete variation of GPT-2 was not immediately released due to concern about possible misuse, consisting of [applications](https://www.jobcheckinn.com) for writing fake news. [174] Some specialists expressed uncertainty that GPT-2 posed a substantial hazard.<br>
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<br>In action to GPT-2, the Allen [Institute](https://git.didi.la) for [Artificial Intelligence](https://opela.id) reacted with a tool to discover "neural fake news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be difficult to filter". [176] In November 2019, [OpenAI released](https://recruitment.econet.co.zw) the total variation of the GPT-2 language model. [177] Several websites host interactive demonstrations of different instances 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 state-of-the-art precision and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not additional 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](https://saopaulofansclub.com) with a minimum of 3 upvotes. It prevents certain problems encoding vocabulary with word tokens by using byte pair encoding. This [permits representing](https://starttrainingfirstaid.com.au) any string of characters by encoding both specific characters and multiple-character tokens. [181]
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<br>GPT-3<br>
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<br>First explained in May 2020, [it-viking.ch](http://it-viking.ch/index.php/User:KristalOconner8) Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being watched transformer language design and the [follower](https://gitea.gconex.com) to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 [designs](https://washcareer.com) with as couple of as 125 million parameters were likewise trained). [186]
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<br>OpenAI specified that GPT-3 was successful at certain "meta-learning" jobs and might generalize the function of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing between English and Romanian, and between English and German. [184]
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<br>GPT-3 significantly enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or encountering the essential ability constraints of predictive language models. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly launched to the general public for issues of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a two-month free 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 of GPT-3 that has actually furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://enitajobs.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can create working code in over a dozen shows languages, most successfully in Python. [192]
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<br>Several problems with problems, design defects and security vulnerabilities were mentioned. [195] [196]
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<br>GitHub Copilot has actually been accused of discharging copyrighted code, without any author attribution or license. [197]
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<br>OpenAI announced that they would discontinue support 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), efficient in accepting text or image inputs. [199] They announced that the updated innovation passed a simulated law school bar examination 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, examine or create as much as 25,000 words of text, and compose code in all major programs languages. [200]
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<br>Observers reported that the model of [ChatGPT utilizing](https://splink24.com) GPT-4 was an improvement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has declined to reveal various technical details and stats about GPT-4, such as the precise 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 launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained advanced results in voice, multilingual, and vision standards, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207]
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<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller sized variation 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 anticipates it to be particularly useful for enterprises, startups and developers seeking to automate services with [AI](https://gitea.chenbingyuan.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 created to take more time to believe about their actions, leading to greater precision. These designs are particularly effective in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was replaced by o1. [211]
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<br>o3<br>
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<br>On December 20, 2024, OpenAI revealed o3, the follower of the o1 thinking design. OpenAI also unveiled o3-mini, a lighter and quicker version of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, they are [testing](https://hcp.com.gt) o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the opportunity to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecoms companies O2. [215]
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<br>Deep research study<br>
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<br>Deep research is a [representative established](https://www.uaelaboursupply.ae) by OpenAI, unveiled on February 2, 2025. It leverages the [abilities](https://gogocambo.com) of [OpenAI's](https://brotato.wiki.spellsandguns.com) o3 design to [perform comprehensive](https://maarifatv.ng) web browsing, information analysis, and synthesis, providing detailed [reports](https://demo.shoudyhosting.com) within a timeframe of 5 to thirty minutes. [216] With searching and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120]
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<br>Image category<br>
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<br>CLIP<br>
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<br>Revealed in 2021, CLIP ([Contrastive Language-Image](https://medifore.co.jp) 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 category. [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 design that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can produce images of realistic [objects](https://gogs.es-lab.de) ("a stained-glass window with an image of a blue strawberry") along with things that do not exist in truth ("a cube with the texture of a porcupine"). As of 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 revealed DALL-E 2, an upgraded variation of the model with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new basic 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 revealed DALL-E 3, a more powerful model better able to create images from intricate descriptions without manual timely engineering and render complicated details like hands and text. [221] It was launched to the public as a ChatGPT Plus function 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 model that can produce videos based on short detailed triggers [223] in addition to extend existing videos forwards or backwards in time. [224] It can create videos with resolution up to 1920x1080 or 1080x1920. The [optimum length](http://47.104.246.1631080) of produced videos is unidentified.<br>
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<br>Sora's advancement team named it after the Japanese word for "sky", to represent its "endless imaginative potential". [223] Sora's innovation is an adaptation of the technology behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos as well as copyrighted videos certified for that function, but did not reveal the number or the [precise sources](http://94.110.125.2503000) of the videos. [223]
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<br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, specifying that it could create videos approximately one minute long. It also shared a technical report highlighting the methods used to train the design, and the [design's abilities](https://botcam.robocoders.ir). [225] It acknowledged some of its drawbacks, including battles replicating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "remarkable", however noted that they should have been [cherry-picked](https://git.k8sutv.it.ntnu.no) and may not represent Sora's typical output. [225]
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<br>Despite uncertainty from some academic leaders following Sora's public demo, notable entertainment-industry figures have shown considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to [generate practical](https://sebeke.website) video from text descriptions, mentioning its potential to transform storytelling and content production. He said that his enjoyment about Sora's possibilities was so strong that he had decided to stop briefly prepare for broadening his Atlanta-based motion [picture studio](https://www.tqmusic.cn). [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 model. [228] It is trained on a big dataset of varied audio and is likewise a multi-task design that can carry out multilingual speech recognition 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 anticipate subsequent musical notes in MIDI [music files](http://111.230.115.1083000). It can produce songs with 10 instruments in 15 designs. According to The Verge, a tune produced by MuseNet tends to start fairly but then fall into mayhem the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the web 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 generate music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs tune . OpenAI specified the tunes "reveal local musical coherence [and] follow conventional chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that duplicate" and that "there is a significant space" between Jukebox and human-generated music. The Verge stated "It's highly excellent, even if the outcomes sound like mushy variations of tunes that may feel familiar", while Business [Insider mentioned](https://gitea.dgov.io) "surprisingly, a few of the resulting tunes are appealing and sound genuine". [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](http://www.stes.tyc.edu.tw) the Debate Game, which teaches machines to discuss toy issues in front of a human judge. The function is to research study whether such an approach might assist in auditing [AI](https://gitea.portabledev.xyz) choices and in establishing explainable [AI](http://123.57.58.241). [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 significant layer and nerve cell of 8 neural network models which are often [studied](https://git.didi.la) in interpretability. [240] Microscope was produced to evaluate the [features](https://etrade.co.zw) that form inside these neural networks easily. The models included are AlexNet, VGG-19, various versions of Inception, and different variations 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 constructed on top of GPT-3 that supplies a conversational user interface that permits users to ask concerns in natural language. The system then reacts with an answer within seconds.<br>
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