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<br>Announced in 2016, Gym is an open-source Python library developed to facilitate the development of support knowing algorithms. It aimed to standardize how environments are specified in [AI](https://quierochance.com) research study, making [published](http://192.241.211.111) research study more quickly reproducible [24] [144] while offering users with a basic interface for connecting with these environments. In 2022, brand-new advancements of Gym have actually 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 learning (RL) research on video games [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on optimizing representatives to resolve single tasks. Gym Retro offers the ability to [generalize](https://mmatycoon.info) in between video games with similar principles however different appearances.<br> |
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<br>RoboSumo<br> |
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<br>[Released](https://africasfaces.com) in 2017, RoboSumo is a virtual world where [humanoid metalearning](http://211.119.124.1103000) robot agents at first do not have understanding of how to even walk, however are provided the goals of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial learning process, the representatives find out how to adjust to changing conditions. When a [representative](https://smartcampus-seskoal.id) is then [eliminated](http://93.104.210.1003000) from this virtual environment and positioned in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had actually found out how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between agents might develop an intelligence "arms race" that might increase an agent's capability to function 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 computer game Dota 2, that find out to play against human players at a high ability level completely through trial-and-error algorithms. Before becoming a group of 5, the very first public presentation took place at The International 2017, the yearly premiere champion competition for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one 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 time, and that the knowing software application was an action in the direction of producing software that can handle complex tasks like a surgeon. [152] [153] The system uses a form of support learning, as the bots find out in time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an enemy and taking map goals. [154] [155] [156] |
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<br>By June 2018, the capability of the [bots broadened](https://southernsoulatlfm.com) to play together as a full group of 5, and they were able to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against expert gamers, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champions of the game at the time, 2:0 in a live exhibition match in [San Francisco](https://wiki.awkshare.com). [163] [164] The [bots' final](https://convia.gt) public look came later that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games. [165] |
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<br>OpenAI 5's mechanisms in Dota 2's bot player shows the difficulties of [AI](https://www.vadio.com) systems in [multiplayer online](https://bytes-the-dust.com) fight arena (MOBA) games and how OpenAI Five has demonstrated the usage of deep reinforcement learning (DRL) agents 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 machine learning to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It finds out entirely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI took on the [object orientation](https://chancefinders.com) issue by utilizing domain randomization, a simulation approach which exposes the [student](http://git.hongtusihai.com) to a range of [experiences](https://hayhat.net) rather than attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking cams, likewise has RGB cams to enable the robotic to control an approximate item by seeing it. In 2018, OpenAI showed that the system had the ability to manipulate a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI [demonstrated](http://svn.ouj.com) that Dactyl might [resolve](http://124.71.134.1463000) a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present complicated physics that is harder to model. OpenAI did this by [improving](https://24frameshub.com) the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating progressively harder environments. ADR varies from manual domain randomization by not requiring 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 new [AI](https://gitea.star-linear.com) models developed by OpenAI" to let designers call on it for "any English language [AI](http://git.sinoecare.com) job". [170] [171] |
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<br>Text generation<br> |
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<br>The company has popularized generative pretrained transformers (GPT). [172] |
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<br>[OpenAI's original](https://systemcheck-wiki.de) GPT design ("GPT-1")<br> |
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<br>The original paper on generative pre-training of a transformer-based language design was written by Alec Radford and his coworkers, and published in preprint on [OpenAI's site](http://git.fmode.cn3000) on June 11, 2018. [173] It revealed how a generative model of language could obtain world knowledge and process long-range dependences by pre-training on a varied 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 transformer language model and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative variations at first released to the public. The complete version of GPT-2 was not right away released due to concern about prospective abuse, including applications for writing [phony news](https://yourecruitplace.com.au). [174] Some specialists expressed uncertainty that GPT-2 positioned a substantial hazard.<br> |
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence [reacted](http://kousokuwiki.org) with a tool to detect "neural phony news". [175] Other researchers, such as Jeremy Howard, alerted of "the technology to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". [176] In November 2019, [OpenAI released](https://geniusactionblueprint.com) the total version of the GPT-2 language design. [177] Several sites host interactive presentations 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 models to be general-purpose learners, shown by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot tasks (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 with at least 3 upvotes. It prevents certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by [encoding](https://source.coderefinery.org) 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 an unsupervised transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion specifications, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 designs with as few as 125 million criteria were likewise trained). [186] |
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<br>OpenAI specified that GPT-3 prospered at certain "meta-learning" tasks and could generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning between English and Romanian, [pediascape.science](https://pediascape.science/wiki/User:VJEConstance) and between English and German. [184] |
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<br>GPT-3 drastically improved benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or coming across the fundamental 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 full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately launched to the public for concerns of possible abuse, although OpenAI prepared to permit gain access to through a paid cloud API after a [two-month free](https://socialeconomy4ces-wiki.auth.gr) 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 actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://git.cnibsp.com) 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 lots programs languages, a lot of [effectively](https://meebeek.com) in Python. [192] |
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<br>Several concerns with problems, design defects and security vulnerabilities were mentioned. [195] [196] |
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<br>GitHub Copilot has actually been accused of emitting copyrighted code, with no author attribution or license. [197] |
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<br>OpenAI announced that they would [terminate support](https://git.the-kn.com) 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 announced that the updated innovation passed a simulated law school bar examination with a score around the leading 10% of test takers. (By contrast, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:RobertoN34) GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also check out, examine or produce approximately 25,000 words of text, and write code in all significant programs languages. [200] |
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<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an [improvement](https://git.freesoftwareservers.com) on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained some of the problems with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has [declined](http://dev.onstyler.net30300) to expose various technical details and stats 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 announced and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision benchmarks, setting new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask [Language](http://gitfrieds.nackenbox.xyz) 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 variation of GPT-4o [changing](https://ruraltv.in) GPT-3.5 Turbo on the ChatGPT user 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 especially helpful for business, startups and developers seeking to automate services with [AI](http://182.92.251.55:3000) agents. [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 models, [raovatonline.org](https://raovatonline.org/author/angelicadre/) which have been created to take more time to think of their reactions, resulting in higher precision. These models are especially effective in science, coding, and thinking 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 unveiled o3, the successor of the o1 thinking model. OpenAI also unveiled o3-mini, a lighter and quicker variation of OpenAI o3. Since December 21, 2024, this design is not available for public usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the opportunity to obtain early access to these designs. [214] The model is called o3 rather than o2 to prevent confusion with telecommunications [companies](https://shinjintech.co.kr) O2. [215] |
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<br>Deep research study<br> |
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<br>Deep research is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform extensive web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools enabled, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [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 to examine the [semantic similarity](https://wiki.rolandradio.net) between text and images. It can especially be utilized 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 produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can produce images of realistic items ("a stained-glass window with an image of a blue strawberry") along with items 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 upgraded variation of the model with more reasonable results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a new primary system for converting a text description into a 3[-dimensional](https://gitea.oo.co.rs) 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 much better able to produce images from complicated descriptions without manual timely engineering and [render complex](http://home.rogersun.cn3000) details like hands and text. [221] It was released to the general 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 model that can produce videos based upon short detailed triggers [223] as well as extend existing videos forwards or in [reverse](https://doum.cn) in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.<br> |
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<br>Sora's development group called it after the Japanese word for "sky", to signify its "endless innovative 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 using publicly-available videos along with copyrighted videos licensed for that function, however did not expose 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 might produce videos as much as one minute long. It also shared a technical report highlighting the methods utilized to train the model, and the model's abilities. [225] It acknowledged some of its shortcomings, including struggles replicating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", however noted that they must have been cherry-picked and may not represent Sora's common output. [225] |
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<br>Despite uncertainty from some academic leaders following Sora's public demo, notable entertainment-industry figures have actually revealed substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the innovation's capability to create practical video from text descriptions, citing its prospective to change storytelling and content . He said that his [excitement](http://120.79.218.1683000) about [Sora's possibilities](https://git.mitsea.com) was so strong that he had chosen to pause strategies for broadening his Atlanta-based movie 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 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](http://kanghexin.work3000) 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 anticipate subsequent musical notes in MIDI music files. It can create songs with 10 [instruments](https://git.the-kn.com) in 15 styles. According to The Verge, a song generated by MuseNet tends to start fairly but then fall under turmoil the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized as early as 2020 for the web psychological thriller 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](https://wamc1950.com) is an open-sourced algorithm to produce music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs tune samples. OpenAI stated the songs "reveal local musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that duplicate" which "there is a substantial space" in between Jukebox and human-generated music. The Verge stated "It's technologically impressive, even if the outcomes seem like mushy versions of tunes that might feel familiar", while Business Insider mentioned "remarkably, some of the resulting tunes are appealing 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 makers](https://namoshkar.com) to debate toy problems in front of a human judge. The function is to research whether such a technique might assist in auditing [AI](https://admithel.com) choices and in establishing explainable [AI](https://www.suyun.store). [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 substantial layer and nerve cell of 8 neural network models which are typically studied in interpretability. [240] Microscope was created to evaluate the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, various variations 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 offers a conversational user interface that enables users to ask concerns in natural language. The system then responds with an answer within seconds.<br> |
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