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<br>Announced in 2016, Gym is an open-source Python library created to help with the development of [support learning](https://diskret-mote-nodeland.jimmyb.nl) algorithms. It aimed to standardize how environments are specified in [AI](https://guiding-lights.com) research, making published research more quickly reproducible [24] [144] while providing users with a simple user interface for interacting with these environments. In 2022, brand-new developments of Gym have been transferred to the library Gymnasium. [145] [146] |
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<br>Gym Retro<br> |
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<br>Released in 2018, Gym Retro is a platform for [reinforcement knowing](https://career.finixia.in) (RL) research on computer game [147] utilizing RL algorithms and [larsaluarna.se](http://www.larsaluarna.se/index.php/User:BettyS407541305) study generalization. Prior RL research focused mainly on optimizing representatives to fix single jobs. Gym Retro offers the capability to [generalize](https://workonit.co) between games with similar ideas but different appearances.<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](http://git.youkehulian.cn) at first lack knowledge of how to even walk, but are provided the objectives of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the representatives learn how to adjust to altering conditions. When an agent is then eliminated from this virtual environment and put in a brand-new virtual environment with high winds, the [agent braces](https://studentvolunteers.us) to remain upright, suggesting it had learned how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives could produce an intelligence "arms race" that might increase a representative's ability to function even outside the context of the competitors. [148] |
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<br>OpenAI 5<br> |
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<br>OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that discover to play against [human gamers](https://granthers.com) at a high skill level totally through trial-and-error algorithms. Before becoming a team of 5, the first public presentation took place at The International 2017, the annual best champion tournament for the video game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had found out by playing against itself for 2 weeks of real time, and that the knowing software was an action in the instructions of developing software application that can deal with complicated jobs like a cosmetic surgeon. [152] [153] The system uses a form of [support](http://www.hyingmes.com3000) learning, as the bots learn gradually by playing against themselves hundreds of times a day for months, and are rewarded for actions such as [eliminating](https://code.in-planet.net) an enemy and taking map objectives. [154] [155] [156] |
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<br>By June 2018, the capability of the bots expanded to play together as a full group of 5, and they were able to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two against expert gamers, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public appearance came later on that month, where they played in 42,729 total video games in a four-day open online competition, [gratisafhalen.be](https://gratisafhalen.be/author/dulcie01x5/) 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 challenges of [AI](https://www.cittamondoagency.it) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated making use of [deep reinforcement](https://bphomesteading.com) learning (DRL) agents to attain superhuman skills in Dota 2 matches. [166] |
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<br>Dactyl<br> |
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<br>Developed in 2018, Dactyl uses maker discovering to train a Shadow Hand, a human-like robot hand, to control physical things. [167] It learns totally in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI tackled the [item orientation](https://src.strelnikov.xyz) problem by using domain randomization, a simulation method which exposes the student to a range of experiences rather than [attempting](http://39.105.128.46) to fit to reality. The set-up for [pipewiki.org](https://pipewiki.org/wiki/index.php/User:ShellieGenders) Dactyl, aside from having movement tracking cams, also has RGB cameras to permit the robot to control an approximate object by seeing it. In 2018, OpenAI revealed that the system had the ability to control a cube and [surgiteams.com](https://surgiteams.com/index.php/User:Mirta17E66502287) an [octagonal prism](http://blueroses.top8888). [168] |
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<br>In 2019, OpenAI demonstrated that Dactyl could solve a [Rubik's Cube](https://mychampionssport.jubelio.store). The robot was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of creating gradually 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](http://8.137.12.29:3000) models established by OpenAI" to let developers get in touch with it for "any English language [AI](https://getquikjob.com) job". [170] [171] |
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<br>Text generation<br> |
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<br>The business has actually promoted generative pretrained transformers (GPT). [172] |
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<br>OpenAI's initial GPT design ("GPT-1")<br> |
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<br>The initial paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative design of language might obtain world understanding and procedure 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 announced in February 2019, with only restricted demonstrative versions initially launched to the public. The full version of GPT-2 was not instantly released due to concern about potential abuse, consisting of [applications](https://pingpe.net) for composing phony news. [174] Some professionals expressed [uncertainty](https://socialcoin.online) that GPT-2 posed a considerable risk.<br> |
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to find "neural phony news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation 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 the complete variation of the GPT-2 language design. [177] Several websites host interactive presentations 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 students, shown by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot tasks (i.e. the model 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 somewhat 40 [gigabytes](https://www.postajob.in) of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by using byte 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 follower to GPT-2. [182] [183] [184] OpenAI mentioned that the full version of GPT-3 contained 175 billion parameters, [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 parameters were likewise trained). [186] |
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<br>OpenAI mentioned 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 offered examples of translation and cross-linguistic transfer learning in between English and Romanian, and in between English and German. [184] |
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<br>GPT-3 drastically improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or experiencing the basic ability constraints of predictive language models. [187] Pre-training GPT-3 [required numerous](https://www.ignitionadvertising.com) 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 model was not instantly launched to the general public for issues of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month totally free personal beta that started in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was licensed solely 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://followgrown.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can produce working code in over a lots programming languages, a lot of efficiently in Python. [192] |
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<br>Several problems with glitches, design defects and security [vulnerabilities](http://supervipshop.net) were cited. [195] [196] |
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<br>GitHub Copilot has actually been implicated of releasing copyrighted code, without any author attribution or license. [197] |
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<br>OpenAI revealed that they would terminate 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 Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the upgraded innovation passed a [simulated law](http://stackhub.co.kr) school bar examination 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 could also check out, evaluate or generate up to 25,000 words of text, and write code in all significant programs languages. [200] |
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<br>Observers reported that the iteration of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has actually declined to reveal numerous technical details and data about GPT-4, such as the [precise size](https://gruppl.com) of the model. [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 generate text, images and audio. [204] GPT-4o attained advanced results in voice, multilingual, and vision benchmarks, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller sized variation of GPT-4o [replacing](http://sgvalley.co.kr) 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, start-ups and designers looking for to automate services with [AI](http://git.airtlab.com: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 designs, which have been designed to take more time to believe about their reactions, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2672496) causing greater accuracy. These designs are particularly effective in science, coding, and reasoning 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 follower of the o1 reasoning model. OpenAI likewise unveiled o3-mini, a lighter and [quicker](https://afrocinema.org) version of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, [security](http://git.cxhy.cn) and security researchers had the chance to obtain early access to these models. [214] The model is called o3 rather than 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 study is an agent developed by OpenAI, unveiled on February 2, 2025. It [leverages](https://unitenplay.ca) the abilities of OpenAI's o3 design to [perform extensive](https://gitea.potatox.net) web browsing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With searching 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 design that is trained to evaluate the semantic resemblance in between text and images. It can significantly be used 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](https://bphomesteading.com) in 2021, DALL-E is a Transformer design that creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of a sad capybara") and create matching images. It can create images of reasonable things ("a stained-glass window with an image of a blue strawberry") in addition to things 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 variation of the design with more reasonable outcomes. [219] In December 2022, OpenAI published on GitHub software for Point-E, a new simple 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, OpenAI announced DALL-E 3, a more effective model better able to generate images from complex descriptions without manual prompt engineering and render intricate details like hands and text. [221] It was launched 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 design that can create videos based on brief detailed prompts [223] in addition to extend existing videos forwards or backwards in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.<br> |
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<br>Sora's development group named it after the Japanese word for "sky", to represent its "limitless creative potential". [223] Sora's technology is an adjustment 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, however did not expose the number or the exact sources 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, mentioning that it could generate videos up to one minute long. It also shared a technical report highlighting the approaches utilized to train the model, and the design's abilities. [225] It acknowledged a few of its imperfections, including struggles mimicing intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", [forum.pinoo.com.tr](http://forum.pinoo.com.tr/profile.php?id=1322189) however noted that they need to have been cherry-picked and may not represent Sora's typical output. [225] |
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<br>Despite uncertainty from some scholastic leaders following [Sora's public](http://kpt.kptyun.cn3000) demonstration, notable entertainment-industry figures have shown considerable interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's capability to [produce reasonable](https://lidoo.com.br) video from text descriptions, citing its potential to change storytelling and content development. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to [pause plans](https://www.niveza.co.in) for expanding 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 diverse audio and is also a multi-task design that can perform multilingual speech recognition along with 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](https://socialcoin.online) net trained to predict subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 styles. According to The Verge, a tune generated by MuseNet tends to start fairly but then fall under mayhem the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were utilized as early as 2020 for the web mental 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 is an open-sourced algorithm to generate music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI specified the tunes "reveal regional musical coherence [and] follow conventional chord patterns" however acknowledged that the songs lack "familiar bigger musical structures such as choruses that repeat" which "there is a considerable space" between Jukebox and human-generated music. The Verge stated "It's technically excellent, even if the outcomes seem like mushy versions of songs that might feel familiar", while Business Insider stated "remarkably, some of the resulting tunes are appealing and sound genuine". [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 machines to debate toy issues in front of a human judge. The purpose is to research study whether such a technique might help in auditing [AI](http://124.220.187.142:3000) choices and in developing explainable [AI](https://login.discomfort.kz). [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 models which are typically 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 artificial intelligence tool constructed on top of GPT-3 that provides a conversational interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.<br> |
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