Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library developed to assist in the development of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://gitlab.kicon.fri.uniza.sk) research study, making published research more [easily reproducible](https://www.virfans.com) [24] [144] while providing users with an easy interface for [interacting](http://8.136.197.2303000) with these environments. In 2022, new [advancements](https://git.christophhagen.de) of Gym have actually 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](http://gitlab.boeart.cn) for reinforcement knowing (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on optimizing representatives to [solve single](https://firstamendment.tv) tasks. Gym Retro gives the capability to generalize in between video games with similar concepts 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 agents initially lack knowledge of how to even stroll, but are given the goals of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives discover how to adjust to changing conditions. When an agent is then removed from this virtual environment and put in a new virtual environment with high winds, the representative braces to remain upright, [yewiki.org](https://www.yewiki.org/User:TrevorMcConnell) suggesting it had learned how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives might develop an intelligence "arms race" that could increase an agent'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 group of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that find out to play against human players at a high ability level totally through trial-and-error algorithms. Before becoming a group of 5, the first public presentation occurred at The International 2017, the annual best champion tournament for the game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually matchup. [150] [151] After the match, [wavedream.wiki](https://wavedream.wiki/index.php/User:AlyceLinton88) CTO Greg Brockman explained that the bot had discovered by playing against itself for 2 weeks of genuine time, which the learning software was a step in the instructions of creating software application that can manage complicated tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of [reinforcement](https://www.womplaz.com) knowing, as the bots learn 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 ability of the bots broadened to play together as a complete 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 2 exhibition matches against expert gamers, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last [public appearance](https://gitea.gconex.com) came later that month, where they played in 42,729 overall games in a four-day open online competition, winning 99.4% of those games. [165]
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<br>OpenAI 5's systems in Dota 2's bot gamer shows the difficulties of [AI](http://jobs.freightbrokerbootcamp.com) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has shown the use of 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 maker finding out to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It discovers totally in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI dealt with the object orientation problem by utilizing domain randomization, a simulation approach which exposes the student to a variety of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having movement tracking cameras, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/3069901) likewise has RGB cameras to enable the robotic to manipulate an approximate 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 showed that Dactyl might fix a Rubik's Cube. The [robotic](https://git.wheeparam.com) was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present [intricate physics](https://www.jjldaxuezhang.com) that is harder to model. OpenAI did this by improving the robustness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation approach of producing progressively more challenging environments. ADR differs from manual domain randomization by not needing a human to specify randomization ranges. [169]
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<br>API<br>
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<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](http://135.181.29.174:3001) models established by OpenAI" to let designers get in touch with it for "any English language [AI](https://www.guidancetaxdebt.com) task". [170] [171]
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<br>Text generation<br>
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<br>The company has promoted 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 associates, and published in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative design of language could obtain world knowledge and procedure long-range dependences by pre-training on a diverse corpus with long stretches of [contiguous text](https://izibiz.pl).<br>
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<br>GPT-2<br>
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<br>Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language design and the [successor](https://www.lokfuehrer-jobs.de) to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative variations at first launched to the general public. The full variation of GPT-2 was not immediately launched due to issue about potential misuse, consisting of applications for composing phony news. [174] Some professionals revealed uncertainty that GPT-2 presented a significant risk.<br>
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<br>In action 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, alerted of "the technology to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the total variation of the GPT-2 language design. [177] Several websites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180]
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<br>GPT-2's authors argue without supervision language models to be general-purpose students, shown by GPT-2 attaining advanced accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not additional trained on any task-specific input-output examples).<br>
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<br>The corpus it was trained on, called WebText, contains somewhat 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 [upvotes](http://www.yfgame.store). It avoids certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This [permits](https://tj.kbsu.ru) 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](https://git-web.phomecoming.com) in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being watched transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI specified that the complete version of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 designs with as couple of as 125 million criteria were also trained). [186]
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<br>OpenAI stated that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the [function](https://www.pinnaclefiber.com.pk) of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning in between English and Romanian, and between English and German. [184]
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<br>GPT-3 significantly improved benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or coming across the basic capability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly released to the general public for issues of possible abuse, although OpenAI prepared to permit gain access to through a paid cloud API after a two-month totally free personal beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed exclusively to [Microsoft](https://www.bongmedia.tv). [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 additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://blogville.in.net) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can produce working code in over a lots programming languages, most effectively in Python. [192]
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<br>Several concerns with glitches, design flaws and security vulnerabilities were [mentioned](https://digital-field.cn50443). [195] [196]
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<br>GitHub Copilot has been implicated of giving off copyrighted code, with no 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 revealed the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar exam 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, [wakewiki.de](https://www.wakewiki.de/index.php?title=Benutzer:FidelChester649) evaluate or create approximately 25,000 words of text, and compose code in all major shows languages. [200]
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<br>Observers reported that the iteration of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained some of the issues with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose various technical details and data 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 and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained cutting edge lead to voice, multilingual, and vision benchmarks, setting brand-new records in audio speech acknowledgment and [translation](https://git.kitgxrl.gay). [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207]
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized variation of GPT-4o changing GPT-3.5 Turbo on the ChatGPT user 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 particularly useful for enterprises, start-ups and developers seeking to automate services with [AI](http://1.94.127.210:3000) representatives. [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 models, which have actually been created to take more time to consider their actions, leading to greater precision. These designs are especially reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1[-preview](https://matchmaderight.com) 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 also unveiled o3-mini, a lighter and faster version of OpenAI o3. Since 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 [opportunity](https://clubamericafansclub.com) to obtain early access to these designs. [214] The model is called o3 instead of o2 to avoid confusion with telecoms companies O2. [215]
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<br>Deep research<br>
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<br>Deep research study is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the [abilities](https://git.snaile.de) of OpenAI's o3 model to carry out comprehensive web browsing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120]
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<br>Image category<br>
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<br>CLIP<br>
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<br>[Revealed](http://121.43.121.1483000) in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to analyze the semantic resemblance between text and images. It can notably 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 in 2021, DALL-E is a Transformer design that produces 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 purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate matching images. It can develop pictures of practical items ("a stained-glass window with an image of a blue strawberry") in addition to things that do not exist in reality ("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 version of the design with more reasonable results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a new primary system for converting 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, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:ShawneeWallner) a more [effective design](https://dirkohlmeier.de) much better able to produce images from complicated descriptions without manual timely engineering and render complicated details like hands and text. [221] It was launched to the public as a ChatGPT Plus feature in October. [222]
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<br>Text-to-video<br>
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<br>Sora<br>
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<br>Sora is a text-to-video model that can create videos based upon short detailed prompts [223] in addition to extend existing videos forwards or in reverse in time. [224] It can produce videos with [resolution](https://tubevieu.com) approximately 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.<br>
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<br>Sora's development group called it after the Japanese word for "sky", to represent its "limitless innovative potential". [223] Sora's innovation is an [adjustment](https://gitstud.cunbm.utcluj.ro) of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI [trained](http://47.103.91.16050903) the system utilizing publicly-available videos in addition to copyrighted videos accredited for that purpose, however 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, stating that it might generate videos as much as one minute long. It also shared a technical report highlighting the approaches used to train the design, and the design's capabilities. [225] It acknowledged a few of its imperfections, including battles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the [presentation videos](https://geoffroy-berry.fr) "outstanding", but noted that they should have been cherry-picked and may not represent Sora's common output. [225]
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<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have shown substantial interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's capability to create practical video from text descriptions, citing its potential to revolutionize storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to stop briefly prepare for expanding his [Atlanta-based movie](http://63.141.251.154) 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 large dataset of diverse audio and is likewise a multi-task model 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, MuseNet is a deep neural net trained to forecast subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to start fairly however then fall into turmoil the longer it plays. [230] [231] In popular culture, initial applications of this tool were used as early as 2020 for the web psychological thriller Ben Drowned to develop 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 create music with vocals. After [training](https://git.ombreport.info) on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs tune samples. OpenAI mentioned the tunes "reveal regional musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that duplicate" which "there is a substantial space" between Jukebox and [human-generated music](http://gitlab.hupp.co.kr). The Verge mentioned "It's technologically impressive, even if the results sound like mushy variations of songs that might feel familiar", while Business Insider mentioned "remarkably, 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 introduced the Debate Game, which teaches makers to dispute toy issues in front of a human judge. The purpose is to research whether such an approach might assist in auditing [AI](https://enitajobs.com) decisions and in establishing explainable [AI](http://lty.co.kr). [237] [238]
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<br>Microscope<br>
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<br>[Released](http://git.scraperwall.com) 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](http://hoenking.cn3000) to [examine](https://messengerkivu.com) the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, different variations 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 supplies a conversational user interface that allows users to ask concerns in natural language. The system then reacts with an answer within seconds.<br>
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