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 facilitate the advancement of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](https://wiki.snooze-hotelsoftware.de) research, making published research study more quickly reproducible [24] [144] while offering users with a simple interface for communicating with these environments. In 2022, new advancements 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](http://gitlab.signalbip.fr) is a platform for reinforcement learning (RL) research on computer game [147] using RL algorithms and research study generalization. Prior RL research [study focused](http://football.aobtravel.se) mainly on optimizing agents to solve single jobs. Gym Retro provides the capability to generalize in between video games with similar concepts however different 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](https://feelhospitality.com) at first do not have knowledge of how to even stroll, but are provided the objectives of discovering to move and to push the opposing agent out of the ring. [148] Through this [adversarial knowing](https://git.tea-assets.com) procedure, the representatives learn how to adapt to [changing conditions](https://demo.titikkata.id). When an agent is then removed from this virtual environment and placed in a [brand-new](https://git.xjtustei.nteren.net) virtual environment with high winds, the representative braces to remain upright, suggesting it had found out how to balance in a [generalized](https://myvip.at) way. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents could develop 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 group of 5 OpenAI-curated bots utilized in the competitive five-on-five computer [game Dota](https://git.tea-assets.com) 2, [wiki.whenparked.com](https://wiki.whenparked.com/User:ShantellAdkins3) that find out to play against human players at a high ability level entirely through trial-and-error algorithms. Before becoming a group of 5, [surgiteams.com](https://surgiteams.com/index.php/User:JulietBoswell) the first public demonstration happened at The International 2017, the yearly best [championship competition](https://git.tea-assets.com) for the video game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for 2 weeks of actual time, and that the learning software application was an action in the [direction](http://8.140.229.2103000) of producing software that can deal with complex jobs like a surgeon. [152] [153] The system utilizes a type of reinforcement knowing, as the bots find out in time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an opponent 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 had the ability to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against professional gamers, but ended up losing both [video games](https://git.qingbs.com). [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 total games in a [four-day](https://src.strelnikov.xyz) open online competition, 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://2flab.com) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually demonstrated making use of deep reinforcement learning (DRL) representatives to attain superhuman competence in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl uses machine finding out to train a Shadow Hand, [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:SophieBloom4921) a human-like robotic hand, to control physical items. [167] It learns completely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the item orientation problem by utilizing domain randomization, a simulation technique which exposes the [learner](https://gitcode.cosmoplat.com) to a range of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having movement tracking electronic cameras, also has RGB electronic cameras to permit the robot to control an arbitrary things by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI demonstrated that Dactyl might fix a Rubik's Cube. The robotic was able to solve the puzzle 60% of the time. [Objects](https://careers.ecocashholdings.co.zw) like the [Rubik's Cube](https://git.dsvision.net) present [complex physics](https://albion-albd.online) that is harder to design. OpenAI did this by improving the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of [producing gradually](https://humlog.social) harder environments. ADR varies 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](https://rapid.tube) models developed by OpenAI" to let designers contact it for "any English language [AI](http://111.8.36.180:3000) job". [170] [171]
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<br>Text generation<br>
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<br>The business has popularized generative pretrained transformers (GPT). [172]
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<br>OpenAI's initial GPT model ("GPT-1")<br>
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<br>The original paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his coworkers, and released in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world knowledge and procedure 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](http://git.cqbitmap.com8001) language model and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just limited demonstrative versions initially launched to the general public. The full variation of GPT-2 was not instantly released due to issue about possible abuse, consisting of applications for writing phony news. [174] Some specialists revealed uncertainty that GPT-2 presented a considerable risk.<br>
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<br>In action to GPT-2, the Allen [Institute](https://csmsound.exagopartners.com) for Artificial Intelligence reacted with a tool to find "neural fake news". [175] Other researchers, such as Jeremy Howard, cautioned of "the innovation to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the complete version of the GPT-2 language design. [177] Several [websites](http://git.ningdatech.com) host interactive presentations 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 modern accuracy 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, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) contains a little 40 gigabytes of text from URLs shared in [Reddit submissions](https://gogs.rg.net) with a minimum of 3 upvotes. It prevents certain issues encoding [vocabulary](https://lets.chchat.me) with word tokens by using byte pair encoding. This allows 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 without supervision transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as few as 125 million parameters were likewise trained). [186]
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<br>OpenAI stated that GPT-3 prospered at certain "meta-learning" jobs and could generalize the purpose 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 dramatically enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 required a number of 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 immediately [launched](https://bdstarter.com) to the general public for concerns of possible abuse, although OpenAI planned to allow gain access to through a paid cloud API after a two-month free [private](https://trulymet.com) beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was certified 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.mtapi.io) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the model can develop working code in over a dozen programs languages, many effectively in Python. [192]
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<br>Several problems with glitches, design defects and security vulnerabilities were pointed out. [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 discontinue 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 updated technology passed a simulated law school bar test with a rating 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, analyze or approximately 25,000 words of text, and compose code in all major programs languages. [200]
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<br>Observers reported that the iteration of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based version, with the caution that GPT-4 retained a few of the problems with earlier revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has actually declined to reveal different technical details and statistics about GPT-4, such as the precise size of the model. [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 [produce](https://2flab.com) text, images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision criteria, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) benchmark 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 beneficial for business, start-ups and developers seeking to automate services with [AI](http://207.148.91.145:3000) agents. [208]
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<br>o1<br>
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<br>On September 12, 2024, OpenAI launched the o1[-preview](https://nycu.linebot.testing.jp.ngrok.io) and o1-mini designs, which have been created to take more time to consider their reactions, resulting in higher accuracy. These models are especially effective in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was changed by o1. [211]
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<br>o3<br>
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<br>On December 20, 2024, OpenAI unveiled o3, the successor of the o1 thinking model. OpenAI also revealed o3-mini, a lighter and quicker version of OpenAI o3. Since December 21, 2024, this design is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the opportunity to obtain early access to these models. [214] The design is called o3 instead of o2 to avoid confusion with telecommunications providers O2. [215]
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<br>Deep research<br>
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<br>Deep research study is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform comprehensive web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools enabled, 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 design that is trained to analyze the semantic similarity between text and images. It can especially 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](https://dirkohlmeier.de) that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to interpret natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and create corresponding images. It can create pictures of [practical objects](https://www.top5stockbroker.com) ("a stained-glass window with a picture of a blue strawberry") along with items that do not exist in truth ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.<br>
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<br>DALL-E 2<br>
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<br>In April 2022, OpenAI revealed DALL-E 2, an [updated variation](http://gitlab.together.social) of the model with more realistic results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new primary 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 create images from intricate descriptions without manual prompt engineering and [render complex](http://gitlab.xma1.de) 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 produce videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of produced videos is unknown.<br>
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<br>Sora's advancement team named it after the Japanese word for "sky", to represent its "unlimited imaginative potential". [223] Sora's technology is an adjustment of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos accredited for that function, but did not expose the number or the exact 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, stating that it might create videos approximately one minute long. It also shared a technical report highlighting the techniques used to train the model, and the design's capabilities. [225] It acknowledged a few of its imperfections, including struggles mimicing intricate physics. [226] Will [Douglas](https://3flow.se) Heaven of the MIT Technology Review called the presentation videos "remarkable", however noted that they should have been cherry-picked and may not represent Sora's [typical](https://jobwings.in) output. [225]
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<br>Despite uncertainty from some academic leaders following Sora's public demonstration, notable entertainment-industry figures have shown significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's capability to generate practical video from text descriptions, mentioning its prospective to transform storytelling and material development. He said that his enjoyment about Sora's possibilities was so strong that he had chosen to stop briefly plans for broadening his Atlanta-based film studio. [227]
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<br>Speech-to-text<br>
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<br>Whisper<br>
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<br>Released in 2022, Whisper is a general-purpose speech recognition model. [228] It is trained on a big dataset of varied audio and is also a multi-task design that can carry out multilingual speech recognition along with 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 predict subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a tune produced by MuseNet tends to begin fairly but then fall into turmoil the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were used as early as 2020 for the [internet psychological](https://astonvillafansclub.com) 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 produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs song samples. OpenAI specified the tunes "reveal local musical coherence [and] follow conventional chord patterns" however acknowledged that the songs do not have "familiar larger musical structures such as choruses that duplicate" and that "there is a significant gap" in between Jukebox and human-generated music. The Verge specified "It's technologically impressive, even if the outcomes sound like mushy variations of songs that might feel familiar", while Business Insider specified "surprisingly, some of the resulting songs are memorable and sound legitimate". [234] [235] [236]
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<br>User user interfaces<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI introduced the Debate Game, which [teaches machines](https://pakkalljob.com) to discuss toy issues in front of a human judge. The function is to research whether such a method may assist in [auditing](http://hulaser.com) [AI](https://crmthebespoke.a1professionals.net) choices and in developing explainable [AI](https://www.grandtribunal.org). [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 often studied in interpretability. [240] Microscope was produced to analyze the functions that form inside these neural networks easily. The models included are AlexNet, VGG-19, various versions of Inception, and different variations 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 interface that permits users to ask questions in natural language. The system then responds with an answer within seconds.<br>
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