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<br>Announced in 2016, Gym is an open-source Python library designed to facilitate the development of reinforcement learning algorithms. It aimed to [standardize](https://thunder-consulting.net) how environments are defined in [AI](http://47.92.26.237) research, making released research study more easily reproducible [24] [144] while offering users with an easy interface for interacting with these environments. In 2022, new developments of Gym have actually been relocated to the library Gymnasium. [145] [146] |
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<br>Gym Retro<br> |
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<br>Released in 2018, Gym Retro is a platform for support learning (RL) research on computer game [147] using RL algorithms and study generalization. Prior RL research focused mainly on enhancing agents to resolve single tasks. Gym Retro provides the ability to generalize in between video games with [comparable concepts](https://barbersconnection.com) but various looks.<br> |
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<br>RoboSumo<br> |
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<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first lack understanding of how to even walk, but are provided the objectives of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives learn how to adapt to altering conditions. When a representative is then removed from this virtual environment and placed in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had found out how to balance in a generalized method. [148] [149] [OpenAI's Igor](https://www.findnaukri.pk) Mordatch argued that competitors between agents could create an intelligence "arms race" that might increase an agent's ability to work 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 ability level totally through trial-and-error algorithms. Before ending up being a group of 5, the first public presentation occurred at The International 2017, the annual premiere champion competition for the video 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 found out by playing against itself for two weeks of actual time, and that the knowing software was a step in the direction of creating software application that can handle intricate jobs like a surgeon. [152] [153] The system uses a type of reinforcement knowing, 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 to play together as a full team of 5, and they had the ability to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against professional players, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world [champions](https://mp3talpykla.com) of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public look came later that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those games. [165] |
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<br>OpenAI 5['s mechanisms](https://gitlab-zdmp.platform.zdmp.eu) in Dota 2's bot gamer reveals the obstacles of [AI](http://39.108.83.154:3000) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually demonstrated the usage of deep reinforcement learning (DRL) agents to attain superhuman competence in Dota 2 matches. [166] |
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<br>Dactyl<br> |
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<br>Developed in 2018, Dactyl uses [device discovering](http://git.tbd.yanzuoguang.com) to train a Shadow Hand, a human-like robot hand, to [control physical](http://35.207.205.183000) items. [167] It discovers entirely in simulation using the very same RL algorithms and [training](https://fydate.com) code as OpenAI Five. OpenAI tackled the item orientation problem by utilizing domain randomization, a simulation method which exposes the student to a variety of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having movement tracking electronic cameras, also has RGB electronic cameras to permit the robot to control an arbitrary object by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI showed that Dactyl might resolve a Rubik's Cube. The robotic had the [ability](https://lastpiece.co.kr) to fix the puzzle 60% of the time. Objects like the [Rubik's Cube](https://103.1.12.176) introduce complex physics that is harder to design. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation approach of producing gradually more hard environments. ADR varies from manual domain randomization by not requiring a human to define randomization ranges. [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 brand-new [AI](https://careers.cblsolutions.com) models developed by OpenAI" to let developers contact it for "any English language [AI](https://stationeers-wiki.com) task". [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 original GPT model ("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 colleagues, and published in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative model of language might obtain world understanding 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 a not being watched transformer language model and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only minimal demonstrative variations initially launched to the general public. The full variation of GPT-2 was not immediately launched due to concern about prospective abuse, [consisting](https://camtalking.com) of applications for composing phony news. [174] Some experts revealed uncertainty that GPT-2 positioned a substantial danger.<br> |
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<br>In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to spot "neural phony news". [175] Other scientists, such as Jeremy Howard, alerted 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 launched the total variation of the GPT-2 language design. [177] Several sites host interactive demonstrations of different instances of GPT-2 and other transformer models. [178] [179] [180] |
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<br>GPT-2's authors argue unsupervised language models to be general-purpose learners, shown by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not further 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](https://git.saphir.one) 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 both specific characters and multiple-character tokens. [181] |
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<br>GPT-3<br> |
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<br>First [explained](http://106.14.125.169) in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being watched transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion specifications, [184] 2 orders of [magnitude bigger](https://git.jackyu.cn) than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were likewise trained). [186] |
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<br>OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" jobs and could generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing in between English and Romanian, and in between English and German. [184] |
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<br>GPT-3 drastically enhanced [benchmark outcomes](https://git.kraft-werk.si) over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or coming across the essential ability constraints of predictive language designs. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the full 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, although OpenAI prepared to allow gain access to through a [paid cloud](https://kittelartscollege.com) 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 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 [additionally](https://asromafansclub.com) been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://f225785a.80.robot.bwbot.org) 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 create working code in over a lots programming languages, a lot of efficiently in Python. [192] |
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<br>Several problems with problems, design flaws and security vulnerabilities were cited. [195] [196] |
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<br>GitHub Copilot has been accused of discharging copyrighted code, without any author attribution or license. [197] |
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<br>OpenAI announced that they would stop assistance 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 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the upgraded technology passed a simulated law school bar exam with a score around the leading 10% of [test takers](https://forum.freeadvice.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise read, analyze or produce up to 25,000 words of text, and compose code in all significant programs languages. [200] |
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<br>[Observers](http://dev.catedra.edu.co8084) reported that the iteration of ChatGPT utilizing GPT-4 was an [enhancement](http://git.indep.gob.mx) on the previous GPT-3.5-based version, with the caveat that GPT-4 [retained](http://gitlab.code-nav.cn) some of the issues with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has decreased to expose numerous technical [details](http://123.57.58.241) and data 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 and generate text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision standards, 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 launched GPT-4o mini, a smaller sized version of GPT-4o replacing 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 expects it to be particularly useful for enterprises, start-ups and designers looking for to automate services with [AI](https://www.tobeop.com) representatives. [208] |
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<br>o1<br> |
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<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been developed to take more time to consider their responses, resulting in greater precision. These models are particularly effective in science, coding, and reasoning tasks, [wiki.lafabriquedelalogistique.fr](https://wiki.lafabriquedelalogistique.fr/Utilisateur:Florine06B) and were made available to [ChatGPT](https://meeting2up.it) 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 reasoning model. OpenAI likewise revealed o3-mini, a lighter and faster 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, safety and security scientists had the opportunity to obtain early access to these designs. [214] The design is called o3 instead of o2 to avoid confusion with telecoms providers O2. [215] |
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<br>Deep research study<br> |
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<br>Deep research is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of [OpenAI's](https://git.purplepanda.cc) o3 model to carry out comprehensive web surfing, data 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 a precision 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 [examine](https://phoebe.roshka.com) the semantic resemblance in between text and images. It can significantly 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 model 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 an unfortunate capybara") and create matching images. It can develop images of reasonable items ("a stained-glass window with a picture of a blue strawberry") in addition to objects that do not exist in truth ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.<br> |
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<br>DALL-E 2<br> |
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<br>In April 2022, OpenAI revealed DALL-E 2, an upgraded version of the design with more reasonable outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new fundamental system for transforming 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, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:NolanBrito91) OpenAI announced DALL-E 3, a more effective model much better able to generate images from complicated descriptions without manual timely engineering and render [complex details](http://110.42.178.1133000) like hands and text. [221] It was launched 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 design that can generate videos based on brief [detailed triggers](https://10-4truckrecruiting.com) [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 produced videos is unidentified.<br> |
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<br>Sora's advancement group named it after the Japanese word for "sky", [wavedream.wiki](https://wavedream.wiki/index.php/User:SelmaStanfield1) to [signify](https://co2budget.nl) its "limitless innovative capacity". [223] Sora's innovation is an adjustment of the innovation behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using [publicly-available videos](http://git.indep.gob.mx) in addition to 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](https://jr.coderstrust.global) videos to the public on February 15, 2024, stating that it could generate videos approximately one minute long. It also shared a technical report highlighting the approaches used to train the model, and the design's capabilities. [225] It acknowledged a few of its drawbacks, including battles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", but 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 demonstration, notable entertainment-industry figures have shown considerable interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to [generate](https://mmatycoon.info) sensible video from text descriptions, citing its possible to transform storytelling and content creation. He said that his enjoyment about Sora's possibilities was so strong that he had decided to stop briefly prepare for broadening his Atlanta-based 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](https://git.collincahill.dev) in 2022, Whisper is a general-purpose speech recognition design. [228] It is trained on a big dataset of diverse audio and is also a multi-task model that can perform 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 forecast subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 designs. According to The Verge, [genbecle.com](https://www.genbecle.com/index.php?title=Utilisateur:ToryYoo02084230) a song produced by MuseNet tends to begin fairly but then fall into mayhem the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for the web mental thriller Ben Drowned to develop music for the titular character. [232] [233] |
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<br>Jukebox<br> |
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<br>Released in 2020, Jukebox is an open-sourced algorithm to produce music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs song samples. OpenAI stated the tunes "reveal regional musical coherence [and] follow standard chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that duplicate" which "there is a significant space" between Jukebox and human-generated music. The Verge mentioned "It's technologically outstanding, even if the outcomes sound like mushy variations of tunes that may feel familiar", while Business Insider stated "remarkably, some of the resulting tunes are catchy and sound legitimate". [234] [235] [236] |
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<br>User user interfaces<br> |
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<br>Debate Game<br> |
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<br>In 2018, OpenAI introduced the Debate Game, which teaches makers to discuss toy problems in front of a human judge. The function is to research whether such an approach might help in auditing [AI](https://fishtanklive.wiki) decisions and in establishing explainable [AI](https://niaskywalk.com). [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 eight neural network designs which are often studied in interpretability. [240] Microscope was developed to evaluate the [features](https://hcp.com.gt) that form inside these neural networks quickly. The designs consisted of are AlexNet, VGG-19, various versions of Inception, and various variations of CLIP Resnet. [241] |
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<br>ChatGPT<br> |
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<br>[Launched](https://dvine.tv) in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that supplies a conversational interface that enables users to ask concerns in natural language. The system then responds with a response within seconds.<br> |
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