Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library developed to facilitate the advancement of support knowing algorithms. It aimed to standardize how environments are defined in [AI](http://git.yoho.cn) research study, making published research more quickly reproducible [24] [144] while supplying users with an easy interface for communicating with these environments. In 2022, new developments of Gym have actually been transferred 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](http://gitlab.pakgon.com) and research study generalization. Prior RL research study focused mainly on enhancing representatives to fix single tasks. Gym Retro provides the ability to generalize in between games with similar ideas 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 representatives at first do not have understanding of how to even walk, but are provided the objectives of finding out to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, [surgiteams.com](https://surgiteams.com/index.php/User:RolandoHorniman) the representatives discover how to adapt to altering conditions. When a representative is then gotten rid of from this virtual environment and put in a new virtual environment with high winds, the agent braces to remain upright, recommending it had actually learned how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might create an intelligence "arms race" that might increase an agent's capability to [function](https://in.fhiky.com) 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 group of 5 OpenAI-curated bots used in the [competitive five-on-five](https://www.thewaitersacademy.com) computer game Dota 2, that find out to play against human gamers at a high skill level totally through experimental algorithms. Before ending up being a team of 5, the first public demonstration happened at The International 2017, the yearly premiere championship tournament for the video game, where Dendi, a [professional Ukrainian](https://cmegit.gotocme.com) gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually found out by playing against itself for two weeks of [genuine](http://demo.qkseo.in) time, and that the learning software application was a step in the instructions of developing software that can manage complex tasks like a cosmetic surgeon. [152] [153] The system uses a type of support knowing, as the bots find out in time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an opponent and taking map goals. [154] [155] [156]
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<br>By June 2018, the capability of the bots expanded to play together as a complete group of 5, and they were able to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert players, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champions of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final [public appearance](https://www.passadforbundet.se) came later on that month, where they played in 42,729 total 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](https://yes.youkandoit.com) the obstacles of [AI](http://49.235.130.76) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually demonstrated the usage of deep support learning (DRL) agents to attain superhuman skills 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 robot hand, to manipulate physical things. [167] It learns entirely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI tackled the things orientation problem by using 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 motion tracking electronic cameras, likewise has RGB electronic cameras to allow the robot to control an approximate object by seeing it. In 2018, OpenAI revealed that the system had the ability to manipulate a cube and an octagonal prism. [168]
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<br>In 2019, [it-viking.ch](http://it-viking.ch/index.php/User:LillieYup4258164) OpenAI showed that Dactyl might fix a Rubik's Cube. The robot had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to model. OpenAI did this by enhancing the [effectiveness](http://zaxx.co.jp) of Dactyl to [perturbations](http://47.101.46.1243000) by using Automatic Domain [Randomization](https://gajaphil.com) (ADR), a simulation method of generating progressively more difficult environments. ADR varies from manual domain randomization by not needing a human to specify randomization varieties. [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 brand-new [AI](http://8.138.140.94:3000) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](https://media.motorsync.co.uk) job". [170] [171]
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<br>Text generation<br>
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<br>The business has actually popularized generative pretrained transformers (GPT). [172]
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<br>OpenAI's initial GPT design ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language design was written by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative design of language might obtain world knowledge and process long-range dependences 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 an unsupervised transformer language model and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative variations initially launched to the general public. The complete version of GPT-2 was not [instantly launched](https://wiki.project1999.com) due to issue about [prospective](https://avajustinmedianetwork.com) misuse, including applications for composing fake news. [174] Some professionals revealed uncertainty that GPT-2 posed a considerable threat.<br>
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to find "neural phony news". [175] Other researchers, such as Jeremy Howard, warned of "the innovation to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be difficult to filter". [176] In November 2019, [OpenAI launched](https://code.cypod.me) the complete version of the GPT-2 language model. [177] Several sites host interactive [presentations](https://www.jobs-f.com) of different instances of GPT-2 and other transformer models. [178] [179] [180]
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<br>GPT-2's authors argue without supervision language models to be general-purpose students, shown by GPT-2 attaining advanced accuracy and [perplexity](https://wakeuptaylor.boardhost.com) on 7 of 8 zero-shot tasks (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 somewhat 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both private 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 not being watched transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI specified that the complete variation of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were likewise trained). [186]
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<br>OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the purpose of a [single input-output](https://video.disneyemployees.net) pair. The GPT-3 [release paper](http://dev.zenith.sh.cn) [offered examples](http://120.36.2.2179095) of translation and cross-linguistic transfer knowing between English and Romanian, and between English and German. [184]
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<br>GPT-3 drastically improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or encountering the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately launched to the general public for concerns of possible abuse, although OpenAI prepared to permit gain access to through a paid cloud API after a two-month totally free personal beta that started in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://ysa.sa) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the model can develop working code in over a dozen programming languages, the majority of efficiently in Python. [192]
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<br>Several problems with problems, design flaws and security vulnerabilities were pointed out. [195] [196]
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<br>GitHub Copilot has been accused of emitting copyrighted code, with no author [attribution](http://www.aiki-evolution.jp) 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 announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the updated innovation passed a simulated law school bar examination with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, examine or [generate](https://www.hammerloop.com) approximately 25,000 words of text, and compose code in all major programming languages. [200]
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<br>Observers reported that the model of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has declined to reveal different technical details and stats about GPT-4, such as the precise size of the model. [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 generate text, images and audio. [204] GPT-4o [attained modern](https://www.ajirazetu.tz) results in voice, multilingual, and vision criteria, setting new [records](https://wiki.communitydata.science) in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207]
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<br>On July 18, 2024, [OpenAI launched](http://tools.refinecolor.com) 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 expects it to be especially helpful for business, start-ups and developers looking for [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:BernadetteConawa) to automate services with [AI](https://gitlab.chabokan.net) representatives. [208]
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<br>o1<br>
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<br>On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have actually been developed to take more time to consider their reactions, causing higher accuracy. These models are especially reliable in science, coding, and [thinking](http://211.91.63.1448088) tasks, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was [changed](http://hmind.kr) 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 thinking design. OpenAI likewise revealed o3-mini, a lighter and much faster variation of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, safety and [links.gtanet.com.br](https://links.gtanet.com.br/zarakda51931) security scientists had the opportunity to obtain early access to these designs. [214] The model is called o3 instead of o2 to avoid confusion with telecommunications services service provider O2. [215]
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<br>Deep research<br>
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<br>Deep research study is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to carry out comprehensive web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and [Python tools](http://124.222.6.973000) made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [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 Pre-training) is a model that is trained to analyze 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](https://empleos.contatech.org) in 2021, DALL-E is a Transformer design that creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to analyze natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can produce pictures of sensible items ("a stained-glass window with an image of a blue strawberry") in addition to objects that do not exist in reality ("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 updated version of the model with more sensible outcomes. [219] In December 2022, OpenAI published on GitHub software for Point-E, a new fundamental 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 effective model better able to create images from complicated descriptions without manual timely engineering and render complex 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 design that can generate videos based upon short detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with resolution up to 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.<br>
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<br>Sora's development team called it after the Japanese word for "sky", to signify its "limitless creative potential". [223] Sora's technology is an adjustment of the innovation behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system [utilizing](https://superblock.kr) publicly-available videos as well as copyrighted videos certified for that function, however did not expose the number or the precise sources of the videos. [223]
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<br>OpenAI showed some [Sora-created high-definition](https://gogs.2dz.fi) videos to the general public on February 15, 2024, specifying that it could generate videos as much as one minute long. It likewise shared a technical report highlighting the techniques used to train the model, and the model's capabilities. [225] It acknowledged some of its shortcomings, [including battles](https://www.atlantistechnical.com) mimicing complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", however kept in mind that they need to have been cherry-picked and might not represent Sora's [typical output](https://finitipartners.com). [225]
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<br>Despite uncertainty from some scholastic leaders following [Sora's public](https://xremit.lol) demonstration, notable entertainment-industry figures have actually revealed significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to produce realistic video from text descriptions, citing its possible to transform storytelling and content production. He said that his excitement about Sora's possibilities was so strong that he had actually decided to pause strategies for expanding his [Atlanta-based film](http://154.209.4.103001) 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](https://estekhdam.in) is a general-purpose speech acknowledgment model. [228] It is trained on a big dataset of varied audio and [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:EMKMichaela) is also a multi-task model that can carry out multilingual speech recognition as well as speech translation and language recognition. [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 musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 designs. According to The Verge, a tune produced by [MuseNet](http://macrocc.com3000) tends to begin fairly but then fall under mayhem the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for the web mental [thriller](http://111.47.11.703000) Ben Drowned to create 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](https://www.informedica.llc) a genre, artist, and a snippet of lyrics and outputs song samples. OpenAI mentioned the tunes "reveal regional musical coherence [and] follow standard chord patterns" but acknowledged that the songs lack "familiar larger musical structures such as choruses that duplicate" which "there is a substantial gap" between Jukebox and human-generated music. The Verge specified "It's highly outstanding, even if the results seem like mushy versions of songs that may feel familiar", while Business Insider stated "surprisingly, some of the resulting songs are appealing and sound legitimate". [234] [235] [236]
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<br>User interfaces<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI launched the Debate Game, which teaches devices to debate toy problems in front of a human judge. The function is to research whether such a technique may assist in auditing [AI](https://maxmeet.ru) decisions and in developing explainable [AI](https://git.cnpmf.embrapa.br). [237] [238]
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<br>Microscope<br>
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<br>Released in 2020, [239] is a collection of visualizations of every substantial layer and nerve cell of 8 neural network models which are often studied in interpretability. [240] Microscope was [developed](https://git.randomstar.io) to analyze the features that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various variations of Inception, and various variations of [CLIP Resnet](https://eelam.tv). [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, [ChatGPT](https://repo.correlibre.org) is an artificial intelligence tool built on top of GPT-3 that provides a conversational user interface that allows users to ask concerns in natural language. The system then reacts with a response within seconds.<br>
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