Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library designed to assist in the advancement of support knowing algorithms. It aimed to standardize how environments are specified in [AI](https://gitlab.lycoops.be) research, making released research more easily reproducible [24] [144] while supplying users with an easy user interface for connecting with these environments. In 2022, new advancements of Gym have been moved 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 (RL) research on computer game [147] using RL algorithms and research study generalization. Prior RL research focused mainly on optimizing representatives to resolve single jobs. Gym Retro offers the capability to generalize in between video games with comparable ideas however 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 representatives initially do not have understanding of how to even walk, however are given the objectives of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the agents find out how to adapt to altering conditions. When an agent is then gotten rid of from this virtual environment and positioned in a brand-new virtual environment with high winds, the representative braces to remain upright, suggesting it had actually [discovered](https://git.todayisyou.co.kr) how to stabilize in a generalized way. [148] [149] OpenAI's Igor [Mordatch](https://wiki.cemu.info) argued that competition between agents might produce an intelligence "arms race" that could increase an agent's capability to operate even outside the context of the [competition](https://nytia.org). [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 computer game Dota 2, that find out to play against human gamers at a high ability level entirely through trial-and-error algorithms. Before ending up being a group of 5, the very first public presentation took place at The International 2017, the annual best championship competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually 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 actual time, and that the knowing software was an action in the instructions of developing software that can handle complicated jobs like a cosmetic surgeon. [152] [153] The system utilizes a kind of support knowing, as the bots find out over time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an opponent and [wavedream.wiki](https://wavedream.wiki/index.php/User:Jada43H59015) taking [map goals](https://www.cbl.health). [154] [155] [156]
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<br>By June 2018, the [capability](https://git.i2edu.net) of the [bots broadened](https://maarifatv.ng) to play together as a complete team of 5, and they had the ability to beat teams of [amateur](https://www.joboptimizers.com) and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against professional players, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champions of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public appearance came later on that month, where they played in 42,729 total games in a four-day open online competition, [winning](http://180.76.133.25316300) 99.4% of those games. [165]
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<br>OpenAI 5's systems in Dota 2's bot gamer shows the challenges of [AI](http://121.40.234.130:8899) systems in [multiplayer online](https://www.gritalent.com) fight arena (MOBA) video games and how OpenAI Five has demonstrated using deep support learning (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl utilizes device [finding](https://git.ashcloudsolution.com) out to train a Shadow Hand, a human-like robotic hand, to control physical items. [167] It discovers entirely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation problem by utilizing domain randomization, a simulation technique which exposes the student to a variety of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking cams, also has RGB video cameras to enable the robotic to control an approximate item by seeing it. In 2018, OpenAI showed 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 robot had the ability to solve the puzzle 60% of the time. Objects like the [Rubik's Cube](http://hellowordxf.cn) [introduce complex](https://www.employment.bz) [physics](http://expand-digitalcommerce.com) that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of producing gradually more tough environments. ADR varies from manual domain randomization by not requiring a human to [define randomization](https://karis.id) [varieties](http://git.liuhung.com). [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](https://m1bar.com) designs developed by OpenAI" to let developers contact it for "any English language [AI](https://gitea.qi0527.com) job". [170] [171]
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<br>Text generation<br>
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<br>The company has popularized generative pretrained transformers (GPT). [172]
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<br>OpenAI's original GPT model ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language model was written by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world knowledge and process long-range reliances 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 without supervision transformer language design and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative versions initially launched to the general public. The complete version of GPT-2 was not right away released due to issue about prospective abuse, [including applications](https://103.1.12.176) for writing phony news. [174] Some specialists revealed uncertainty that GPT-2 positioned a significant hazard.<br>
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<br>In [response](https://social.ppmandi.com) to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "neural phony news". [175] Other researchers, 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 hush all other speech and be difficult to filter". [176] In November 2019, OpenAI released the total variation of the GPT-2 language design. [177] Several sites host interactive presentations of different instances of GPT-2 and other transformer designs. [178] [179] [180]
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<br>GPT-2's authors argue not being watched language designs to be general-purpose learners, illustrated by GPT-2 attaining state-of-the-art accuracy and [larsaluarna.se](http://www.larsaluarna.se/index.php/User:Gertie4309) 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 somewhat 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by utilizing 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 design and the successor to GPT-2. [182] [183] [184] OpenAI stated that the full version of GPT-3 contained 175 billion parameters, [184] two orders of magnitude larger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were likewise trained). [186]
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<br>OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the purpose of a [single input-output](https://gitea.xiaolongkeji.net) pair. The GPT-3 release paper provided 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 outcomes over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or experiencing the basic capability constraints of predictive language designs. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of compute, [compared](https://testgitea.cldevops.de) to 10s of petaflop/s-days for the full 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 planned](https://recruitment.econet.co.zw) to allow gain access to through a paid cloud API after a two-month 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://git.e365-cloud.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 develop working code in over a dozen shows languages, the majority of efficiently in Python. [192]
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<br>Several concerns with glitches, design flaws and security vulnerabilities were cited. [195] [196]
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<br>GitHub Copilot has been implicated of giving off [copyrighted](https://littlebigempire.com) code, without any 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), capable of accepting text or image inputs. [199] They revealed that the upgraded technology passed a simulated law school bar exam 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 could also read, evaluate or produce up to 25,000 words of text, and compose code in all significant shows languages. [200]
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<br>Observers reported that the version of [ChatGPT utilizing](http://209.141.61.263000) GPT-4 was an on the previous GPT-3.5-based version, with the caution that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to [reveal numerous](https://lets.chchat.me) technical details and statistics 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 create text, images and audio. [204] GPT-4o attained advanced results in voice, multilingual, and [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:ElaneBriseno6) vision standards, setting 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 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 particularly helpful for business, start-ups and designers seeking to [automate](https://boonbac.com) services with [AI](https://heovktgame.club) 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 models, which have actually been created to take more time to think about their actions, leading to greater accuracy. These designs are particularly efficient in science, coding, and thinking tasks, 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 design. OpenAI also unveiled o3-mini, a lighter and faster version 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 researchers had the opportunity to obtain early access to these models. [214] The model is called o3 instead of o2 to prevent confusion with telecommunications providers O2. [215]
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<br>Deep research<br>
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<br>Deep research is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 model to carry out extensive web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [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 model that is trained to evaluate 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](http://playtube.ythomas.fr) in 2021, DALL-E is a Transformer design that develops images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to analyze natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and produce corresponding images. It can produce pictures of reasonable things ("a stained-glass window with an image of a blue strawberry") as well as things 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 announced DALL-E 2, an upgraded variation of the design with more practical outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new rudimentary 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 announced DALL-E 3, a more powerful model better able to produce images from complex descriptions without manual timely engineering and render [intricate details](https://aijoining.com) like hands and text. [221] It was [released](https://51.75.215.219) to the general 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 produce videos based on short detailed prompts [223] as well as extend existing videos forwards or backwards in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of created videos is unknown.<br>
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<br>[Sora's development](https://git.newpattern.net) team named it after the Japanese word for "sky", to symbolize its "endless creative capacity". [223] Sora's innovation is an adaptation of the innovation behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos accredited for that purpose, but did not expose 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 might generate videos approximately one minute long. It likewise shared a technical report highlighting the methods used to train the model, and the model's capabilities. [225] It acknowledged a few of its drawbacks, consisting of battles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", however kept in mind that they must have been cherry-picked and might not represent Sora's typical output. [225]
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<br>Despite uncertainty from some scholastic leaders following [Sora's public](https://media.labtech.org) demonstration, notable entertainment-industry figures have shown substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's ability to create practical video from text descriptions, citing its possible to change storytelling and content production. He said that his excitement about Sora's possibilities was so strong that he had chosen to [pause plans](https://sossphoto.com) for [expanding](https://theglobalservices.in) 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 model. [228] It is trained on a large dataset of diverse audio and is likewise a multi-task model that can carry out multilingual speech acknowledgment in addition to speech translation and language identification. [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 songs with 10 instruments in 15 designs. According to The Verge, a song generated by MuseNet tends to start fairly but then fall into mayhem the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were [utilized](http://112.124.19.388080) as early as 2020 for the web psychological thriller Ben Drowned to develop music for the [titular character](https://www.kmginseng.com). [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](https://gofleeks.com) the tunes "reveal regional musical coherence [and] follow standard chord patterns" but acknowledged that the tunes lack "familiar larger musical structures such as choruses that repeat" and that "there is a substantial space" in between Jukebox and human-generated music. The Verge mentioned "It's technologically outstanding, even if the results seem like mushy versions of tunes that may feel familiar", while Business Insider specified "surprisingly, some of the resulting tunes are appealing and sound genuine". [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 devices to dispute toy problems in front of a human judge. The purpose is to research study whether such a method may help in auditing [AI](https://eliteyachtsclub.com) decisions and in [establishing explainable](https://www.jobsalert.ai) [AI](http://www.asystechnik.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](http://116.236.50.1038789) which are typically studied in interpretability. [240] Microscope was produced to [examine](https://git.xhkjedu.com) the functions that form inside these neural networks easily. The designs included are AlexNet, VGG-19, various variations 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 is a synthetic intelligence tool developed on top of GPT-3 that offers a conversational user interface that permits users to ask concerns in natural language. The system then responds with a response within seconds.<br>
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