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<br>Announced in 2016, Gym is an open-source Python library created to help with the development of support knowing algorithms. It aimed to standardize how environments are defined in [AI](https://www.buzzgate.net) research, making published research study more easily reproducible [24] [144] while providing users with a basic interface for connecting with these environments. In 2022, [brand-new developments](http://git.emagenic.cl) of Gym have 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 knowing (RL) research on video games [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on optimizing agents to fix single jobs. Gym Retro provides the capability to generalize in between video games with similar principles 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 robot agents initially lack understanding of how to even stroll, but are provided the goals of discovering to move and to press the [opposing representative](http://211.117.60.153000) out of the ring. [148] Through this adversarial learning process, the representatives find out how to adjust to altering conditions. When an agent is then removed from this virtual environment and placed in a brand-new virtual environment with high winds, the representative braces to remain upright, recommending it had actually discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives might create an intelligence "arms race" that might increase a representative's ability to operate even outside the context of the [competition](http://git.medtap.cn). [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 video game Dota 2, that discover to play against human gamers at a high ability level completely through trial-and-error algorithms. Before ending up being a team of 5, the very first public demonstration occurred at The International 2017, the annual best championship tournament for the game, where Dendi, an expert Ukrainian player, lost against a bot in a live one-on-one matchup. [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, which the learning software application was a step in the direction of developing software that can deal with complicated jobs like a cosmetic surgeon. [152] [153] The system uses a kind of reinforcement knowing, as the bots find out with time by playing against themselves hundreds of times a day for months, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2769752) 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 teams of amateur and . [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against professional players, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champs of the video game at the time, 2:0 in a live [exhibition match](https://www.cbmedics.com) in San Francisco. [163] [164] The bots' final public look came later on that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those [video games](http://gitlab.ileadgame.net). [165] |
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<br>OpenAI 5's mechanisms in Dota 2's bot player reveals the difficulties of [AI](https://www.elitistpro.com) systems in multiplayer online [battle arena](https://usvs.ms) (MOBA) video games and how OpenAI Five has demonstrated the use of deep reinforcement learning (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 finding out to train a Shadow Hand, a human-like robot hand, to control physical objects. [167] It discovers completely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation problem by utilizing domain randomization, a simulation approach which exposes the learner to a variety of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking cameras, likewise has RGB cameras to permit the robotic to manipulate an approximate item by seeing it. In 2018, OpenAI showed that the system was able to control a cube and an [octagonal prism](https://git.jzmoon.com). [168] |
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<br>In 2019, OpenAI showed that Dactyl could resolve a Rubik's Cube. The robot had the ability to resolve 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 the effectiveness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), [larsaluarna.se](http://www.larsaluarna.se/index.php/User:DarinGallegos) a simulation method of [creating](https://gitea.dokm.xyz) progressively harder environments. [ADR varies](http://101.43.151.1913000) from manual domain randomization by not requiring a human to define 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://406.gotele.net) designs developed by OpenAI" to let developers call on it for "any English language [AI](https://gitea.alaindee.net) task". [170] [171] |
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<br>Text generation<br> |
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<br>The company has actually promoted generative pretrained transformers (GPT). [172] |
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<br>OpenAI's original GPT model ("GPT-1")<br> |
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<br>The original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his coworkers, and [released](https://iraqitube.com) in preprint on OpenAI's website on June 11, 2018. [173] It showed how a [generative model](https://menfucks.com) of language might obtain world knowledge and process long-range dependencies by pre-training on a diverse corpus with long stretches of adjoining text.<br> |
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<br>GPT-2<br> |
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<br>Generative Pre-trained Transformer 2 ("GPT-2") is a without supervision transformer language model and the follower to OpenAI's initial GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just minimal [demonstrative variations](http://182.92.251.553000) at first released to the general public. The complete variation of GPT-2 was not immediately launched due to issue about prospective misuse, consisting of applications for writing phony news. [174] Some specialists revealed 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 with a tool to identify "neural phony news". [175] Other scientists, such as Jeremy Howard, alerted of "the innovation to totally 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 the complete version of the GPT-2 language model. [177] Several sites host interactive demonstrations of different circumstances of GPT-2 and other transformer models. [178] [179] [180] |
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<br>GPT-2's authors argue not being watched language models to be general-purpose learners, highlighted by GPT-2 attaining cutting edge precision and perplexity on 7 of 8 zero-shot jobs (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 a little 40 gigabytes of text from [URLs shared](https://finitipartners.com) in Reddit submissions with at least 3 upvotes. It prevents certain concerns 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 design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion specifications, [184] two orders of [magnitude bigger](https://glhwar3.com) than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 [designs](http://www.xn--1-2n1f41hm3fn0i3wcd3gi8ldhk.com) with as couple of as 125 million parameters were likewise trained). [186] |
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<br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" tasks and might generalize the function of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer knowing between English and Romanian, and between English and German. [184] |
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<br>GPT-3 considerably improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or experiencing the essential capability constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not right away launched to the general public for issues of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month free private beta that began 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 actually furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.execafrica.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the model can [produce](https://handsfarmers.fr) working code in over a dozen programs languages, most efficiently in Python. [192] |
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<br>Several problems with glitches, style flaws and security vulnerabilities were cited. [195] [196] |
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<br>GitHub Copilot has been implicated of discharging copyrighted code, with no author attribution or license. [197] |
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<br>OpenAI announced that they would cease 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](https://cvmobil.com) in accepting text or image inputs. [199] They announced that the upgraded innovation passed a simulated law school bar examination with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, analyze or generate as much as 25,000 words of text, and write code in all significant shows languages. [200] |
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<br>Observers reported that the iteration of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caution that GPT-4 retained some of the issues with earlier modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal various technical details and stats about GPT-4, such as the accurate size of the design. [203] |
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<br>GPT-4o<br> |
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<br>On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and generate text, images and [pediascape.science](https://pediascape.science/wiki/User:VJEConstance) audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision standards, setting brand-new records 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 released GPT-4o mini, a smaller version 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 useful for enterprises, startups and designers looking for to automate services with [AI](http://poscotech.co.kr) 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 designs, which have actually been designed to take more time to think of their actions, leading to higher precision. These models are particularly efficient in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Team members. [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 revealed o3, the successor of the o1 [reasoning design](https://groups.chat). OpenAI likewise unveiled o3-mini, a lighter and much faster version of OpenAI o3. As of December 21, 2024, this model is not available for public usage. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the chance to obtain early access to these designs. [214] The model is called o3 instead of o2 to avoid confusion with telecoms companies O2. [215] |
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<br>Deep research<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](https://thedatingpage.com) o3 design to carry out substantial web browsing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 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) standard. [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 evaluate the semantic similarity between text and images. It can significantly 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 model that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to translate natural [language](https://i-medconsults.com) inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and create corresponding images. It can produce pictures of sensible objects ("a stained-glass window with a picture of a blue strawberry") along with objects that do not exist in truth ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.<br> |
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<br>DALL-E 2<br> |
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<br>In April 2022, OpenAI announced DALL-E 2, an [upgraded](http://poscotech.co.kr) version of the model with more sensible outcomes. [219] In December 2022, OpenAI published on GitHub software application for [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:JanelleJevons) Point-E, a brand-new primary system for transforming a text description into a 3-dimensional model. [220] |
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<br>DALL-E 3<br> |
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<br>In September 2023, OpenAI revealed DALL-E 3, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) a more effective model better able to produce images from intricate descriptions without manual prompt 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 short detailed triggers [223] along with 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 created videos is unknown.<br> |
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<br>Sora's development group called it after the Japanese word for "sky", to represent its "limitless creative capacity". [223] Sora's innovation is an adaptation of the technology behind the [DALL ·](http://120.92.38.24410880) E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos [accredited](https://www.emploitelesurveillance.fr) for that function, however did not reveal the number or the [precise sources](https://git.cloudtui.com) of the videos. [223] |
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<br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, stating that it could create videos approximately one minute long. It likewise shared a technical report highlighting the methods used to train the model, and the [model's abilities](https://gitlab.liangzhicn.com). [225] It acknowledged a few of its imperfections, including struggles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "remarkable", but noted that they need to have been cherry-picked and might not represent Sora's normal output. [225] |
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<br>Despite [uncertainty](https://akinsemployment.ca) from some academic leaders following [Sora's public](https://jobs.sudburychamber.ca) demonstration, significant entertainment-industry figures have revealed considerable interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the innovation's ability to produce sensible video from text descriptions, citing its potential to change storytelling and [material creation](https://www.srapo.com). He said that his excitement about Sora's possibilities was so strong that he had chosen to stop briefly prepare 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 big dataset of varied audio and is also a multi-task model that can perform multilingual speech acknowledgment 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](https://nodlik.com) to forecast subsequent musical notes in MIDI music files. It can produce songs with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to begin fairly however then fall under turmoil the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for the internet 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 is an open-sourced algorithm to produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs tune samples. OpenAI mentioned the tunes "reveal local musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes do not have "familiar larger musical structures such as choruses that duplicate" which "there is a considerable gap" between Jukebox and human-generated music. The [Verge stated](http://gitlab.qu-in.com) "It's highly impressive, even if the outcomes sound like mushy variations of songs that may feel familiar", while Business Insider stated "remarkably, a few 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 launched the Debate Game, which teaches makers to debate toy problems in front of a human judge. The function is to research whether such an approach might assist in auditing [AI](https://sea-crew.ru) choices and in developing explainable [AI](http://gitea.anomalistdesign.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 considerable layer and nerve cell of eight neural [network models](https://admithel.com) which are typically studied in interpretability. [240] Microscope was developed to evaluate the features that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, various versions of Inception, and different versions of CLIP Resnet. [241] |
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<br>ChatGPT<br> |
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<br>[Launched](https://playtube.app) in November 2022, ChatGPT is a synthetic intelligence tool developed on top of GPT-3 that provides a conversational user interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.<br> |
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