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<br>Announced in 2016, Gym is an open-source Python library designed to assist in the advancement of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](https://gitlab.dev.cpscz.site) research, making published research more quickly reproducible [24] [144] while offering users with an easy interface for communicating with these [environments](https://quierochance.com). In 2022, new [advancements](https://xremit.lol) 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, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:Shad9988863) Gym Retro is a platform for support learning (RL) research on video games [147] utilizing RL algorithms and [study generalization](https://vacancies.co.zm). Prior RL research focused mainly on enhancing agents to solve single jobs. Gym Retro provides the ability to generalize between games with comparable principles 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 robot representatives initially lack understanding of how to even stroll, however are given the goals of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial learning process, the agents discover how to adapt to changing conditions. When a representative is then eliminated from this virtual environment and placed in a brand-new virtual environment with high winds, the braces to remain upright, recommending it had learned how to balance in a generalized way. [148] [149] OpenAI's Igor [Mordatch](https://hlatube.com) argued that competitors between agents could develop an intelligence "arms race" that could increase a [representative's capability](https://funitube.com) 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 group of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that discover to play against human players at a high skill level completely through trial-and-error algorithms. Before ending up being a team of 5, the first public demonstration occurred at The International 2017, the [annual premiere](http://new-delhi.rackons.com) champion tournament for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for 2 weeks of real time, which the learning software was a step in the direction of [producing software](https://www.trabahopilipinas.com) application that can manage complicated jobs like a cosmetic surgeon. [152] [153] The system utilizes a type of support learning, as the bots learn over 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 objectives. [154] [155] [156] |
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<br>By June 2018, the ability of the bots expanded to play together as a full group of 5, and they had the ability to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert gamers, but 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 exhibit match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 total video 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 gamer reveals the obstacles of [AI](http://www.hnyqy.net:3000) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated the use of deep support knowing (DRL) representatives 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 device discovering to train a Shadow Hand, a human-like robot hand, to control physical objects. [167] It discovers totally in simulation using the very same RL algorithms and [training](https://phdjobday.eu) code as OpenAI Five. OpenAI dealt with the item orientation issue by utilizing domain randomization, a simulation method which exposes the [student](http://163.228.224.1053000) to a range of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having [movement tracking](https://www.gabeandlisa.com) cams, likewise has RGB video cameras to enable the robot to manipulate an arbitrary item by seeing it. In 2018, OpenAI showed that the system was able to control a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce [intricate physics](http://dimarecruitment.co.uk) that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating gradually more hard environments. ADR differs 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 revealed a multi-purpose API which it said was "for accessing new [AI](https://yooobu.com) models established by OpenAI" to let developers contact it for "any English language [AI](http://yanghaoran.space:6003) 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 initial GPT model ("GPT-1")<br> |
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<br>The initial paper on [generative pre-training](http://121.36.62.315000) of a [transformer-based language](https://www.empireofember.com) design was composed by Alec Radford and his colleagues, and published in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative model of language could obtain world understanding and process long-range reliances by pre-training on a diverse corpus with long stretches of 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 design and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative variations initially launched to the general public. The full variation of GPT-2 was not immediately launched due to concern about possible misuse, consisting of applications for writing fake news. [174] Some experts revealed uncertainty that GPT-2 [postured](https://zkml-hub.arml.io) a significant danger.<br> |
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to find "neural fake news". [175] Other researchers, [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1089696) 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 muffle all other speech and be difficult to filter". [176] In November 2019, [OpenAI released](http://xintechs.com3000) the total version of the GPT-2 language model. [177] Several sites host interactive demonstrations of various instances 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, highlighted by GPT-2 attaining advanced precision and perplexity 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 [prevents](https://git.the-kn.com) certain concerns encoding vocabulary with word tokens by [utilizing byte](https://boonbac.com) pair encoding. This permits representing any string of characters by encoding both individual characters and multiple-character tokens. [181] |
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<br>GPT-3<br> |
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<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as few as 125 million criteria were also trained). [186] |
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<br>OpenAI stated that GPT-3 was successful 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 knowing between English and Romanian, and in between English and [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:Syreeta19K) German. [184] |
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<br>GPT-3 drastically improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or encountering the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, 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 public for issues of possible abuse, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:CatalinaHoffnung) although OpenAI prepared to allow gain access to through a paid cloud API after a two-month complimentary personal beta that began in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was certified exclusively to Microsoft. [190] [191] |
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<br>Codex<br> |
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<br>Announced in mid-2021, Codex is a [descendant](https://malidiaspora.org) of GPT-3 that has actually furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://47.100.81.115) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the design can develop working code in over a lots programs languages, most efficiently in Python. [192] |
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<br>Several concerns with problems, design flaws and security vulnerabilities were cited. [195] [196] |
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<br>GitHub Copilot has actually been implicated of emitting copyrighted code, with no author attribution or license. [197] |
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<br>OpenAI revealed 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 test with a score around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, examine or generate approximately 25,000 words of text, and compose code in all major programming [languages](http://tmdwn.net3000). [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 iteration, with the caveat that GPT-4 retained a few of the problems with earlier revisions. [201] GPT-4 is also [capable](https://easy-career.com) of taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal numerous 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 released GPT-4o, which can [process](https://www.hrdemployment.com) and create text, images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision criteria, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller variation of GPT-4o replacing 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 beneficial for business, startups and developers looking for to [automate services](https://imidco.org) with [AI](http://193.140.63.43) agents. [208] |
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<br>o1<br> |
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<br>On September 12, 2024, [OpenAI launched](https://rejobbing.com) the o1-preview and o1-mini models, which have been developed to take more time to consider their reactions, leading to greater accuracy. These models are particularly effective in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was changed by o1. [211] |
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<br>o3<br> |
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<br>On December 20, 2024, OpenAI unveiled o3, the successor of the o1 thinking design. OpenAI likewise unveiled o3-mini, a lighter and quicker variation of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and [security scientists](https://fewa.hudutech.com) had the opportunity to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecommunications [companies](https://neoshop365.com) O2. [215] |
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<br>Deep research<br> |
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<br>Deep research is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to [perform comprehensive](https://abalone-emploi.ch) web surfing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools 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 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 design that is trained to analyze the [semantic resemblance](http://gitea.digiclib.cn801) between text and images. It can notably be utilized 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 design that produces images from textual descriptions. [218] DALL-E utilizes 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 create images of practical objects ("a stained-glass window with a picture of a blue strawberry") along with items 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 updated variation of the model with more realistic results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new primary system for converting a text description into a 3[-dimensional design](https://timviec24h.com.vn). [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 much better able to produce images from complex descriptions without manual timely engineering and render intricate details like hands and text. [221] It was released to the public as a ChatGPT Plus feature in October. [222] |
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<br>Text-to-video<br> |
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<br>Sora<br> |
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<br>Sora is a text-to-video model that can generate videos based upon brief detailed triggers [223] in addition to extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution as much as 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 symbolize its "unlimited innovative capacity". [223] Sora's technology is an adaptation of the innovation behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos certified for that function, but did not reveal the number or the exact 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 create videos up to one minute long. It also shared a technical report highlighting the methods utilized to train the design, and the model's abilities. [225] It acknowledged a few of its imperfections, consisting of struggles mimicing [complex physics](https://gryzor.info). [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but kept in mind that they should have been cherry-picked and might 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 actually revealed significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the [innovation's capability](http://123.111.146.2359070) to create [practical](http://39.99.158.11410080) video from text descriptions, citing its [potential](https://ambitech.com.br) to revolutionize storytelling and content [production](https://hiremegulf.com). He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to pause prepare for expanding his Atlanta-based motion picture studio. [227] |
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<br>Speech-to-text<br> |
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<br>Whisper<br> |
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<br>Released in 2022, Whisper is a general-purpose speech recognition design. [228] It is trained on a big dataset of diverse audio and is likewise a multi-task model that can carry out multilingual speech recognition in addition to speech translation and language [recognition](http://yanghaoran.space6003). [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 produce songs with 10 instruments in 15 designs. According to The Verge, a tune produced by MuseNet tends to start fairly however 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 produce music for the titular character. [232] [233] |
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<br>Jukebox<br> |
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<br>Released in 2020, [Jukebox](http://sanaldunyam.awardspace.biz) is an open-sourced algorithm to create music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs song samples. OpenAI stated the songs "reveal local musical coherence [and] follow conventional chord patterns" but acknowledged that the songs lack "familiar bigger musical structures such as choruses that duplicate" which "there is a considerable gap" in between Jukebox and [human-generated music](https://gl.cooperatic.fr). The Verge specified "It's technologically outstanding, even if the results sound like mushy variations of songs that might feel familiar", while Business Insider [mentioned](https://www.infinistation.com) "remarkably, a few of the resulting tunes 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 released the Debate Game, which [teaches devices](http://f225785a.80.robot.bwbot.org) to dispute toy issues in front of a human judge. The purpose is to research study whether such an [approach](https://jobs.cntertech.com) might help in auditing [AI](https://gayplatform.de) decisions and in establishing explainable [AI](https://git.muehlberg.net). [237] [238] |
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<br>Microscope<br> |
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<br>Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and nerve cell of eight neural network models which are often studied in interpretability. [240] Microscope was developed to examine the functions that form inside these neural networks quickly. The designs consisted of are AlexNet, VGG-19, different variations of Inception, and different 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 developed on top of GPT-3 that provides a conversational user interface that permits users to ask concerns in natural language. The system then responds with an answer within seconds.<br> |
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