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 help with the development of reinforcement knowing algorithms. It aimed to standardize how environments are specified in [AI](http://ptube.site) research, making [published](http://engineerring.net) research study more easily reproducible [24] [144] while [supplying](http://121.40.209.823000) users with an easy user interface for interacting with these environments. In 2022, brand-new developments 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 is a platform for reinforcement knowing (RL) research on video games [147] using RL algorithms and study generalization. Prior RL research focused mainly on enhancing agents to fix single tasks. Gym Retro offers the ability to generalize in between games with comparable principles but various looks.<br>
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<br>RoboSumo<br>
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<br>Released in 2017, [bio.rogstecnologia.com.br](https://bio.rogstecnologia.com.br/mia335414507) RoboSumo is a virtual world where humanoid metalearning robot representatives at first lack [knowledge](http://39.105.128.46) of how to even walk, but are offered the goals of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the agents learn how to adapt to [altering conditions](https://pakfindjob.com). When a representative is then eliminated from this virtual environment and put in a brand-new virtual environment with high winds, the representative braces to remain upright, suggesting it had found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor [Mordatch argued](https://akrs.ae) that competitors between agents could produce an intelligence "arms race" that could increase a representative's capability to work even outside the context of the competitors. [148]
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<br>OpenAI 5<br>
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<br>OpenAI Five is a team of 5 OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that find out to play against human gamers at a high skill level totally through experimental algorithms. Before ending up being a group of 5, the first public demonstration took place at The International 2017, the yearly premiere championship competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a [live one-on-one](https://celflicks.com) matchup. [150] [151] After the match, CTO Greg Brockman [explained](https://paanaakgit.iran.liara.run) that the bot had discovered by playing against itself for 2 weeks of actual time, which the learning software application was a step in the instructions of creating software that can manage intricate tasks like a surgeon. [152] [153] The system uses a form of support learning, as the bots find out over time by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an enemy and taking map goals. [154] [155] [156]
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<br>By June 2018, the capability of the bots expanded to play together as a complete team of 5, and they had the ability to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 [exhibition matches](http://git.sysoit.co.kr) against [professional](http://shiningon.top) players, but ended up losing both games. [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 exhibition match in San Francisco. [163] [164] The bots' last public appearance came later that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those games. [165]
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<br>OpenAI 5['s systems](https://git.howdoicomputer.lol) in Dota 2's bot player reveals the challenges of [AI](https://tylerwesleywilliamson.us) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has actually demonstrated using deep support knowing (DRL) agents 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 maker finding out to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It learns completely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI took on the things orientation problem by utilizing domain randomization, a simulation approach 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 electronic cameras, likewise has RGB cameras to allow the robotic to control an [arbitrary object](http://git.andyshi.cloud) by seeing it. In 2018, OpenAI showed 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 robot had the ability to solve the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to model. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of creating progressively harder environments. ADR varies from manual domain randomization by not needing a human to define randomization ranges. [169]
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<br>API<br>
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<br>In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](http://www.grainfather.de) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](https://www.aspira24.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 initial GPT model ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his colleagues, [genbecle.com](https://www.genbecle.com/index.php?title=Utilisateur:Millard1035) and published in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world knowledge and procedure long-range reliances by pre-training on a [varied corpus](http://47.99.119.17313000) 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 successor to OpenAI's initial GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just minimal demonstrative variations initially launched to the general public. The full variation of GPT-2 was not right away [released](https://fydate.com) due to issue about potential misuse, consisting of applications for [pipewiki.org](https://pipewiki.org/wiki/index.php/User:ElizbethItw) composing phony news. [174] Some experts revealed uncertainty that GPT-2 [positioned](https://devfarm.it) a significant hazard.<br>
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<br>In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to discover "neural fake news". [175] Other scientists, such as Jeremy Howard, cautioned of "the technology to absolutely 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 version of the GPT-2 language model. [177] Several websites host interactive presentations of different instances of GPT-2 and [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11860868) other [transformer designs](https://empregos.acheigrandevix.com.br). [178] [179] [180]
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<br>GPT-2's authors argue without supervision language designs to be general-purpose learners, illustrated by GPT-2 attaining advanced precision and [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:LaneHaining) perplexity on 7 of 8 zero-shot tasks (i.e. the model was not further trained on any task-specific input-output examples).<br>
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<br>The corpus it was trained on, called WebText, contains a little 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 utilizing byte pair encoding. This allows representing any string of characters by encoding both specific characters and [multiple-character](https://owangee.com) 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 design and [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) the successor to GPT-2. [182] [183] [184] OpenAI specified that the complete version of GPT-3 contained 175 billion parameters, [184] 2 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 also trained). [186]
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<br>OpenAI mentioned that GPT-3 was successful at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer knowing in between [English](https://git.partners.run) and Romanian, and between English and German. [184]
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<br>GPT-3 significantly enhanced benchmark results over GPT-2. OpenAI warned that such [scaling-up](http://www.topverse.world3000) of language designs could be approaching or encountering the essential capability constraints of predictive language models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly released to the general public for issues of possible abuse, although OpenAI prepared to enable gain access to through a paid cloud API after a two-month complimentary personal 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://timviecvtnjob.com) [powering](https://gitlog.ru) the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can create working code in over a dozen programs languages, most effectively in Python. [192]
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<br>Several concerns with glitches, [design flaws](https://video.clicktruths.com) and security vulnerabilities were mentioned. [195] [196]
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<br>GitHub Copilot has actually been accused of releasing copyrighted code, without any author attribution or license. [197]
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<br>OpenAI announced that they would terminate assistance for Codex API on March 23, 2023. [198]
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<br>GPT-4<br>
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<br>On March 14, 2023, OpenAI revealed the release of Generative Pre-trained [Transformer](https://ugit.app) 4 (GPT-4), capable of [accepting text](https://xhandler.com) or image inputs. [199] They [revealed](http://engineerring.net) that the [updated innovation](https://nuswar.com) passed a simulated law school bar test 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, analyze or produce up to 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 iteration, with the caveat that GPT-4 retained some of the problems with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal different technical details and statistics about GPT-4, such as the exact size of the model. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained cutting edge lead to voice, multilingual, and vision criteria, setting brand-new records in audio speech recognition and translation. [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 launched GPT-4o mini, a smaller variation of GPT-4o changing GPT-3.5 Turbo on the ChatGPT interface. Its [API costs](http://ledok.cn3000) $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 business, [startups](https://wishjobs.in) and developers seeking to automate services with [AI](http://193.123.80.202:3000) 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 been created to take more time to think of their responses, [causing](https://somalibidders.com) higher precision. These designs are particularly reliable in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and [Employee](https://nbc.co.uk). [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 revealed o3, the [successor](https://juventusfansclub.com) of the o1 thinking model. OpenAI also unveiled o3-mini, a lighter and [faster variation](https://ready4hr.com) of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, [security](https://library.kemu.ac.ke) and security scientists had the [opportunity](http://www.topverse.world3000) to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecommunications services supplier O2. [215]
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<br>Deep research<br>
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<br>Deep research study is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out substantial web surfing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools enabled, 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 examine the semantic resemblance between text and images. It can notably 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 that develops 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 bag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and generate matching images. It can develop pictures of reasonable items ("a stained-glass window with a picture of a blue strawberry") along with objects 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 revealed DALL-E 2, an upgraded version of the design with more reasonable results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new fundamental system for converting 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 effective model better able to create images from intricate descriptions without manual timely engineering and render intricate details like hands and text. [221] It was released 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 produce videos based on brief detailed prompts [223] as well as extend existing videos forwards or backwards in time. [224] It can create videos with [resolution](https://peopleworknow.com) approximately 1920x1080 or 1080x1920. The maximal length of created videos is unidentified.<br>
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<br>Sora's development group called it after the Japanese word for "sky", to signify its "limitless innovative potential". [223] Sora's innovation is an adaptation of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using [publicly-available videos](https://gitter.top) along with copyrighted videos accredited for that function, however did not reveal the number or the specific sources of the videos. [223]
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<br>OpenAI demonstrated some Sora-created high-definition videos to the public on February 15, 2024, stating that it might generate videos approximately one minute long. It likewise shared a technical report highlighting the approaches used to train the model, and the design's abilities. [225] It acknowledged a few of its shortcomings, [consisting](https://www.ndule.site) of battles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", but kept in mind that they must 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 demo, notable entertainment-industry figures have actually shown significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's ability to produce sensible video from text descriptions, mentioning its prospective to change storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had chosen to [pause strategies](https://amigomanpower.com) for broadening 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 varied audio and is also a multi-task design that can carry out multilingual speech acknowledgment 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 anticipate subsequent musical notes in MIDI music files. It can create tunes with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to start fairly however then fall under chaos the longer it plays. [230] [231] In popular culture, initial applications of this tool were used as early as 2020 for the [internet psychological](https://devfarm.it) 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 to produce music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs song [samples](https://clubamericafansclub.com). OpenAI specified the tunes "reveal local musical coherence [and] follow standard chord patterns" however that the tunes do not have "familiar larger musical structures such as choruses that duplicate" and that "there is a considerable gap" in between Jukebox and human-generated music. The Verge mentioned "It's highly outstanding, even if the outcomes seem like mushy variations of songs that may feel familiar", while Business Insider stated "surprisingly, some of the resulting tunes are memorable 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 discuss toy problems in front of a human judge. The function is to research whether such a method might help in auditing [AI](https://nytia.org) decisions and in [establishing explainable](http://114.132.245.2038001) [AI](https://bence.net). [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 considerable layer and nerve cell of eight neural network designs which are frequently studied in interpretability. [240] Microscope was [produced](http://steriossimplant.com) to examine the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various versions of Inception, and different versions of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, [it-viking.ch](http://it-viking.ch/index.php/User:ArnetteV70) ChatGPT is an expert system tool constructed on top of GPT-3 that provides a conversational user interface that allows users to ask concerns in natural language. The system then responds with an answer within seconds.<br>
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