Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library created to assist in the development of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](https://git.blinkpay.vn) research, making released research more quickly reproducible [24] [144] while providing users with a basic interface for connecting 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 (RL) research on computer game [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on enhancing representatives to fix single tasks. Gym Retro offers the capability to [generalize](http://103.235.16.813000) between video games with comparable 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 robotic representatives at first do not have understanding of how to even walk, but are offered the goals of finding out to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the agents find out how to adapt to changing conditions. When a representative is then gotten rid of from this virtual environment and placed in a new virtual environment with high winds, the [representative](https://haloentertainmentnetwork.com) braces to remain upright, suggesting it had learned how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives might produce an intelligence "arms race" that could increase a representative's ability to operate 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 utilized in the competitive five-on-five video game Dota 2, that discover to play against human players at a high ability level entirely through experimental algorithms. Before ending up being a group of 5, the very first public demonstration occurred at The International 2017, the yearly premiere champion competition for the game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg [Brockman explained](https://www.k4be.eu) that the bot had actually discovered by playing against itself for two weeks of genuine time, and that the knowing software was an action in the [instructions](https://career.finixia.in) of producing software application that can handle complex tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of reinforcement learning, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:LawerenceJeanner) as the bots discover in time by playing against themselves numerous times a day for months, [it-viking.ch](http://it-viking.ch/index.php/User:AngelicaSnowball) and are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156]
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<br>By June 2018, the ability of the bots broadened to play together as a full group of 5, and they had the ability to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against professional 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 exhibition match in San Francisco. [163] [164] The bots' final public appearance came later that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those video games. [165]
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<br>OpenAI 5['s mechanisms](https://duyurum.com) in Dota 2's bot player shows the challenges of [AI](https://git.rt-academy.ru) systems in multiplayer online fight arena (MOBA) games and [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:Syreeta19K) how OpenAI Five has shown using deep support knowing (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 device learning to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It discovers entirely in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the item orientation issue by utilizing domain randomization, a simulation technique which exposes the student to a range of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking cams, also has RGB cams to allow the robot to control an approximate things by seeing it. In 2018, OpenAI revealed that the system had the ability to control 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 robot had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube present [complex](https://job.bzconsultant.in) physics that is harder to design. OpenAI did this by [enhancing](https://gitlab.ineum.ru) the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of producing progressively harder environments. ADR differs from manual domain randomization by not needing 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](https://git.limework.net) which it said was "for accessing brand-new [AI](https://hiphopmusique.com) models established by OpenAI" to let developers get in touch with it for "any English language [AI](https://git.kraft-werk.si) job". [170] [171]
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<br>Text generation<br>
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<br>The business has promoted generative pretrained transformers (GPT). [172]
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<br>OpenAI's original [GPT model](https://gitlab.tncet.com) ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language design was written by Alec Radford and his coworkers, and published in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative design of language could obtain world understanding and process long-range reliances by pre-training on a varied corpus with long stretches of adjoining text.<br>
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<br>GPT-2<br>
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<br>[Generative Pre-trained](https://gitlab.internetguru.io) Transformer 2 ("GPT-2") is an unsupervised transformer language design and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just limited demonstrative variations at first launched to the general public. The complete variation of GPT-2 was not instantly released due to concern about prospective abuse, consisting of applications for composing phony news. [174] Some experts revealed uncertainty that GPT-2 postured a significant threat.<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, cautioned of "the innovation to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be impossible to filter". [176] In November 2019, OpenAI released the total variation of the GPT-2 language model. [177] Several websites host interactive demonstrations of different instances of GPT-2 and other transformer designs. [178] [179] [180]
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<br>GPT-2's authors argue without supervision language designs to be general-purpose students, shown by GPT-2 attaining advanced precision and perplexity on 7 of 8 zero-shot jobs (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 slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by using byte pair encoding. This allows 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 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 specified that the complete variation of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as few as 125 million criteria were likewise trained). [186]
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<br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the purpose of a [single input-output](https://bytes-the-dust.com) pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer knowing between English and Romanian, and in between English and German. [184]
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<br>GPT-3 drastically enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs could be approaching or coming across the essential capability constraints of predictive language models. [187] Pre-training GPT-3 needed 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 model was not right away released 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 complimentary private beta that started in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed 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 of GPT-3 that has actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://chat.app8station.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://git.unicom.studio) working code in over a dozen shows languages, the majority of successfully in Python. [192]
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<br>Several problems with problems, style defects and security vulnerabilities were pointed out. [195] [196]
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<br>GitHub Copilot has actually been accused of emitting copyrighted code, with no author attribution or license. [197]
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<br>OpenAI revealed that they would [discontinue assistance](https://armconnection.com) for Codex API on March 23, 2023. [198]
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<br>GPT-4<br>
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<br>On March 14, 2023, OpenAI 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 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 might likewise read, evaluate or produce approximately 25,000 words of text, and compose code in all significant shows [languages](http://120.26.108.2399188). [200]
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<br>Observers reported that the model of [ChatGPT utilizing](https://nse.ai) GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is likewise [efficient](http://haiji.qnoddns.org.cn3000) in taking images as input on ChatGPT. [202] OpenAI has actually declined to [reveal numerous](http://candidacy.com.ng) technical details and statistics about GPT-4, such as the exact size of the design. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, [OpenAI revealed](https://git.cyu.fr) and released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained state-of-the-art lead to voice, multilingual, and vision standards, setting brand-new records in audio speech recognition and [translation](https://jamboz.com). [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 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 anticipates it to be especially useful for enterprises, startups and developers looking for to [automate services](https://www.medicalvideos.com) with [AI](https://dubaijobzone.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 actually been developed to take more time to consider their actions, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:ChristyPetherick) causing greater [precision](http://120.55.164.2343000). These models are especially reliable in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1[-preview](https://socialpix.club) was replaced by o1. [211]
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<br>o3<br>
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<br>On December 20, 2024, OpenAI unveiled o3, the successor of the o1 thinking model. OpenAI also revealed o3-mini, a lighter and faster version of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these designs. [214] The model is called o3 rather than o2 to prevent confusion with [telecommunications companies](https://aidesadomicile.ca) O2. [215]
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<br>Deep research<br>
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<br>Deep research is an agent developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to carry out extensive web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [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 examine the semantic similarity 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 creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version 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 produce matching images. It can develop pictures of reasonable objects ("a stained-glass window with an image 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 variation of the model with more sensible results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new rudimentary system for transforming a text description into a 3[-dimensional design](https://www.securityprofinder.com). [220]
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<br>DALL-E 3<br>
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<br>In September 2023, OpenAI revealed DALL-E 3, a more effective model better able to generate images from complex descriptions without manual timely engineering and render complicated details like hands and [gratisafhalen.be](https://gratisafhalen.be/author/rebbeca9609/) text. [221] It was [released](http://43.137.50.31) to the public as a ChatGPT Plus function 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 prompts [223] along with extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of produced videos is unknown.<br>
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<br>Sora's advancement group called it after the Japanese word for "sky", to signify its "unlimited creative capacity". [223] Sora's innovation is an adaptation of the innovation behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos licensed for that purpose, but did not reveal the number or the specific sources of the videos. [223]
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<br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, specifying that it could produce videos approximately one minute long. It also shared a technical report highlighting the techniques utilized to train the design, and the model's capabilities. [225] It acknowledged some of its shortcomings, consisting of battles replicating [complicated physics](http://gitlab.gavelinfo.com). [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", however kept in mind that they need to have been cherry-picked and might not represent Sora's common output. [225]
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<br>Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have revealed significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's ability to produce practical video from text descriptions, citing its possible to reinvent storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had chosen to stop briefly 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](http://161.97.176.30) is a general-purpose speech recognition model. [228] It is trained on a large dataset of diverse audio and is also a multi-task design that can carry out 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, [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:WinstonNajera5) MuseNet is a deep neural net trained to forecast subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 designs. According to The Verge, a song generated by MuseNet tends to begin fairly but then fall under chaos the longer it plays. [230] [231] In popular culture, preliminary 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](https://trustemployement.com) to create music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs tune samples. OpenAI stated the songs "reveal regional musical coherence [and] follow conventional chord patterns" however acknowledged that the songs do not have "familiar bigger musical structures such as choruses that duplicate" and [surgiteams.com](https://surgiteams.com/index.php/User:LatanyaZiegler) that "there is a substantial space" between Jukebox and human-generated music. The Verge specified "It's technologically impressive, even if the results sound like mushy variations of songs that may feel familiar", while Business Insider stated "remarkably, some of the resulting songs are catchy 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 released the Debate Game, which teaches makers to discuss toy issues in front of a human judge. The function is to research study whether such a method may help in auditing [AI](https://www.stormglobalanalytics.com) decisions and in developing explainable [AI](https://careerjunction.org.in). [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 significant layer and nerve cell of eight neural network designs which are frequently studied in interpretability. [240] Microscope was produced to examine the features that form inside these [neural networks](https://localjobpost.com) quickly. The designs consisted of are AlexNet, VGG-19, various versions of Inception, and various versions of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, [ChatGPT](https://www.mepcobill.site) is an expert system tool developed on top of GPT-3 that provides a conversational user interface that enables users to ask questions in natural language. The system then responds with a response within seconds.<br>
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