Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python [library](https://gitea.marvinronk.com) created to assist in the development of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://thisglobe.com) research, making released research more quickly reproducible [24] [144] while supplying users with a simple interface for [engaging](http://git.kdan.cc8865) with these environments. In 2022, brand-new advancements of Gym have been moved 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] using RL algorithms and [study generalization](https://jobz0.com). Prior RL research study focused mainly on enhancing representatives to resolve single jobs. Gym Retro provides the ability to generalize between games with similar ideas but different appearances.<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 agents at first do not have understanding of how to even walk, but are provided the goals of finding out to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the agents discover how to adapt to altering conditions. When an agent is then eliminated from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had found out how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives might create an intelligence "arms race" that might increase a representative's ability to operate even outside the context of the competition. [148]
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<br>OpenAI 5<br>
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<br>OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that learn to play against human gamers at a high skill level completely through trial-and-error algorithms. Before becoming a group of 5, the very first public presentation occurred at The International 2017, the yearly best champion competition for the game, where Dendi, a [professional Ukrainian](https://codeincostarica.com) gamer, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually learned by playing against itself for two weeks of actual time, and that the learning software application was a step in the instructions of creating software that can manage complicated jobs like a surgeon. [152] [153] The system uses a type of support knowing, as the bots find out [gradually](http://111.8.36.1803000) by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an enemy 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 complete team of 5, and they were able to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against [professional](https://82.65.204.63) gamers, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) the reigning 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 [appearance](https://hiphopmusique.com) came later that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those video games. [165]
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<br>OpenAI 5's systems in Dota 2's bot player shows the difficulties of [AI](https://82.65.204.63) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has actually shown using deep reinforcement [learning](https://www.medexmd.com) (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl uses device discovering to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It discovers totally in simulation using the same RL algorithms and [wiki.eqoarevival.com](https://wiki.eqoarevival.com/index.php/User:RETCameron) training code as OpenAI Five. OpenAI dealt with the things orientation problem by utilizing domain randomization, a simulation method which exposes the learner to a range of experiences rather than trying to fit to truth. The set-up for Dactyl, aside from having movement tracking video cameras, likewise has RGB video cameras to permit the robotic to control an arbitrary things by seeing it. In 2018, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:MillieTum68) 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 demonstrated that Dactyl could resolve a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. [Objects](http://it-viking.ch) like the Rubik's Cube introduce intricate physics that is harder to design. OpenAI did this by enhancing the [robustness](https://visualchemy.gallery) of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of producing gradually harder environments. [ADR differs](http://175.25.51.903000) from manual domain randomization by not [requiring](https://www.fionapremium.com) a human to specify randomization varieties. [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 new [AI](https://www.shopes.nl) designs established by OpenAI" to let developers get in touch with it for "any English language [AI](https://lepostecanada.com) job". [170] [171]
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<br>Text generation<br>
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<br>The business has popularized generative pretrained transformers (GPT). [172]
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<br>OpenAI's original GPT model ("GPT-1")<br>
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<br>The original 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](http://122.51.51.353000) and process long-range dependencies by pre-training on a diverse 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 and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative versions initially launched to the general public. The full version of GPT-2 was not right away launched due to concern about prospective abuse, consisting of [applications](https://iesoundtrack.tv) for composing fake news. [174] Some specialists revealed uncertainty that GPT-2 positioned a considerable hazard.<br>
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<br>In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to find "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 hush all other speech and be difficult to filter". [176] In November 2019, OpenAI released the total variation of the GPT-2 language design. [177] Several websites host interactive demonstrations of different circumstances of GPT-2 and other transformer models. [178] [179] [180]
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<br>GPT-2's authors argue not being watched language models to be general-purpose learners, illustrated by GPT-2 attaining state-of-the-art accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the model 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 a little 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain concerns encoding vocabulary with word tokens by utilizing byte pair [encoding](https://www.ausfocus.net). This allows representing any string of [characters](https://aws-poc.xpresso.ai) 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, Generative Pre-trained [a] Transformer 3 (GPT-3) is a without supervision transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 [contained](https://www.89u89.com) 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](https://iesoundtrack.tv) with as few as 125 million parameters were also trained). [186]
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<br>OpenAI specified that GPT-3 prospered at certain "meta-learning" tasks and could generalize the function of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning in between English and Romanian, and between English and German. [184]
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<br>GPT-3 drastically improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs could be approaching or experiencing the basic capability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately released to the general public for issues of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month totally free personal beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was certified specifically 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 additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://divsourcestaffing.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in [private](https://newnormalnetwork.me) beta. [194] According to OpenAI, the design can create working code in over a lots programs languages, a lot of successfully in Python. [192]
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<br>Several concerns with problems, style defects and security vulnerabilities were mentioned. [195] [196]
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<br>GitHub Copilot has been accused of emitting copyrighted code, with no author attribution or license. [197]
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<br>OpenAI revealed that they would terminate support for Codex API on March 23, [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1091356) 2023. [198]
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<br>GPT-4<br>
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<br>On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar exam with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise read, evaluate or create up to 25,000 words of text, and write code in all significant shows languages. [200]
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<br>Observers reported that the model of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained some of the issues with earlier revisions. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has decreased to reveal various technical details and stats about GPT-4, such as the accurate size of the design. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision criteria, setting 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 launched GPT-4o mini, a smaller sized variation of GPT-4o replacing GPT-3.5 Turbo on the [ChatGPT interface](https://chaakri.com). Its API costs $0.15 per million [input tokens](https://career.logictive.solutions) and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI expects it to be particularly helpful for business, start-ups and [designers](https://hr-2b.su) looking for to automate services with [AI](http://a21347410b.iask.in:8500) representatives. [208]
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<br>o1<br>
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<br>On September 12, 2024, [OpenAI launched](http://www.jimtangyh.xyz7002) the o1-preview and o1-mini designs, which have actually been created to take more time to think of their reactions, causing greater accuracy. These designs are especially reliable in science, coding, and [thinking](https://germanjob.eu) jobs, and were made available to ChatGPT 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 revealed o3, the successor of the o1 thinking model. OpenAI also unveiled o3-mini, a lighter and quicker version of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these models. [214] The model is called o3 instead of o2 to avoid confusion with telecommunications providers O2. [215]
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<br>Deep research study<br>
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<br>Deep research study is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of [OpenAI's](https://divsourcestaffing.com) o3 design to [perform extensive](https://www.towingdrivers.com) web surfing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 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) benchmark. [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 Pre-training) is a model that is [trained](http://211.117.60.153000) to [analyze](https://jobs.com.bn) the semantic resemblance 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 produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can create pictures of [realistic objects](https://gallery.wideworldvideo.com) ("a stained-glass window with an image of a blue strawberry") in addition to items 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 updated variation of the model with more reasonable outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new basic system for converting a text description into a 3-dimensional model. [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 much better able to create images from intricate descriptions without manual timely engineering and render intricate details like hands and text. [221] It was released to the general 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 generate videos based upon brief detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.<br>
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<br>Sora's advancement team named it after the Japanese word for "sky", to represent its "limitless imaginative capacity". [223] Sora's technology is an adjustment of the technology behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos certified for that purpose, but did not reveal the number or the specific sources of the videos. [223]
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<br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it could create videos up to one minute long. It likewise shared a technical report highlighting the methods utilized to train the model, and the design's capabilities. [225] It acknowledged a few of its imperfections, including battles replicating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", however noted 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 academic leaders following Sora's public demo, significant entertainment-industry figures have shown substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's ability to generate sensible video from text descriptions, citing its potential to reinvent storytelling and content creation. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to stop briefly prepare for broadening his Atlanta-based film 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 recognition design. [228] It is trained on a large dataset of diverse audio and is likewise a multi-task design that can carry out multilingual speech recognition along with speech translation and language [identification](https://www.huntsrecruitment.com). [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. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a tune generated by MuseNet tends to start fairly however then fall under chaos the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for the internet mental thriller Ben Drowned to produce 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 genre, artist, and a bit of lyrics and outputs song samples. OpenAI specified the songs "show local 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 substantial gap" between Jukebox and human-generated music. The Verge mentioned "It's technologically impressive, even if the outcomes seem like mushy versions of songs that may feel familiar", while Business Insider specified "surprisingly, a few of the resulting songs are memorable 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 introduced the Debate Game, which teaches devices to debate toy problems in front of a human judge. The purpose is to research study whether such an approach might assist in auditing [AI](http://stay22.kr) decisions and in developing explainable [AI](https://www.gabeandlisa.com). [237] [238]
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<br>Microscope<br>
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<br>Released in 2020, Microscope [239] is a [collection](http://lty.co.kr) of visualizations of every substantial layer and neuron of 8 neural network designs which are typically studied in interpretability. [240] Microscope was created to examine the features that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, different variations of Inception, and various versions of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that provides a conversational user interface that enables users to ask concerns in natural language. The system then responds with a response within seconds.<br>
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