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 facilitate the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are specified in [AI](https://gofleeks.com) research, making released research more quickly reproducible [24] [144] while supplying users with a simple user interface for connecting with these environments. In 2022, new advancements 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 for support knowing (RL) research on computer game [147] using RL algorithms and study generalization. Prior RL research study focused mainly on optimizing agents to solve single jobs. Gym Retro offers the ability to generalize 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 at first do not have knowledge of how to even walk, but are offered the objectives of learning to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives find out how to adjust to altering conditions. When an agent is then gotten rid of from this virtual environment and placed in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might produce an intelligence "arms race" that might increase a representative's ability to operate even outside the context of the competition. [148]
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<br>OpenAI 5<br>
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<br>OpenAI Five is a team of 5 OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that [discover](https://www.activeline.com.au) to play against human players at a high ability level totally through [experimental algorithms](https://jobpile.uk). Before becoming a group of 5, the very first [public presentation](http://119.3.70.2075690) occurred at The International 2017, the yearly best champion competition for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had found out by playing against itself for two weeks of actual time, and that the knowing software application was an action in the instructions of creating software that can deal with intricate jobs like a surgeon. [152] [153] The system uses a kind of support knowing, as the bots discover gradually by playing against themselves numerous times a day for months, and are rewarded for [actions](https://161.97.85.50) such as eliminating an opponent and taking map goals. [154] [155] [156]
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<br>By June 2018, the capability of the bots broadened to play together as a complete team of 5, and they were able to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against expert gamers, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champs of the video game at the time, 2:0 in a live exhibit match in [San Francisco](http://git.jetplasma-oa.com). [163] [164] The bots' last public look came later that month, where they played in 42,729 total video games in a four-day open online competitors, winning 99.4% of those games. [165]
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<br>OpenAI 5's mechanisms in Dota 2's bot player shows the obstacles of [AI](https://www.sealgram.com) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually demonstrated making use of [deep reinforcement](http://wecomy.co.kr) knowing (DRL) representatives 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 utilizes [device discovering](http://xn--vk1b975azoatf94e.com) to train a Shadow Hand, a human-like robot hand, to control physical things. [167] It learns entirely in simulation using the very 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 student to a range of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having motion tracking electronic cameras, likewise has RGB cameras to permit the robot to manipulate an arbitrary things 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 fix a Rubik's Cube. The robotic was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce [complex physics](https://gitea.gumirov.xyz) that is harder to design. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating progressively more [challenging](http://47.121.132.113000) environments. ADR differs from manual domain randomization by not requiring a human to specify randomization varieties. [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://lstelecom.co.kr) models developed by OpenAI" to let designers contact it for "any English language [AI](https://git.mbyte.dev) task". [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 design](https://tiktack.socialkhaleel.com) was written by Alec Radford and [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:MarshaPolk22104) his associates, and [released](https://lubuzz.com) in preprint on [OpenAI's site](http://47.121.132.113000) on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world understanding and process long-range reliances by pre-training on a diverse 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 not being watched transformer language model and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just [restricted demonstrative](http://103.197.204.1633025) versions at first [released](https://parejas.teyolia.mx) to the public. The full variation of GPT-2 was not immediately launched due to concern about possible misuse, including applications for composing fake news. [174] Some experts [revealed uncertainty](https://oyotunji.site) that GPT-2 posed a considerable hazard.<br>
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<br>In [reaction](http://170.187.182.1213000) to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to spot "neural phony news". [175] Other scientists, such as Jeremy Howard, warned 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 released the total version of the GPT-2 language model. [177] Several sites host interactive demonstrations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180]
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<br>GPT-2's authors argue unsupervised language designs to be general-purpose students, shown by GPT-2 attaining advanced precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not more trained on any task-specific input-output examples).<br>
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<br>The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This permits 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 not being watched transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI stated that the complete version of GPT-3 contained 175 billion criteria, [184] two orders of [magnitude larger](http://dancelover.tv) than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as few as 125 million specifications were likewise trained). [186]
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<br>OpenAI stated that GPT-3 was successful at certain "meta-learning" tasks and might generalize the function of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer knowing in between English and Romanian, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:Marcy4075626057) and between English and German. [184]
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<br>GPT-3 significantly enhanced benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or experiencing the basic capability constraints of predictive language models. [187] Pre-training GPT-3 required a number of thousand petaflop/s-days [b] of calculate, [compared](http://plus-tube.ru) to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 [trained model](https://heovktgame.club) was not right away [launched](https://jobpile.uk) to the general public for [larsaluarna.se](http://www.larsaluarna.se/index.php/User:BettyS407541305) concerns of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month free private beta that started in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed exclusively to Microsoft. [190] [191]
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<br>Codex<br>
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<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://supremecarelink.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the model can produce working code in over a dozen programming languages, most effectively in Python. [192]
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<br>Several problems with problems, design defects and security vulnerabilities were mentioned. [195] [196]
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<br>GitHub Copilot has actually been implicated of discharging copyrighted code, with no author attribution or license. [197]
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<br>OpenAI revealed that they would cease assistance for [Codex API](https://zudate.com) 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), capable of accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar examination with a score around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise read, examine or create up to 25,000 words of text, and write code in all significant shows languages. [200]
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<br>Observers reported that the iteration of [ChatGPT](https://publiccharters.org) using GPT-4 was an enhancement on the previous GPT-3.5-based version, 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 declined to reveal various 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 announced and released GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained cutting edge lead to voice, multilingual, and vision standards, setting brand-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 version of GPT-4o [changing](https://gitea.portabledev.xyz) 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, [surgiteams.com](https://surgiteams.com/index.php/User:RolandoHorniman) compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be particularly helpful for enterprises, start-ups and developers looking for to automate services with [AI](https://repo.amhost.net) agents. [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 designs, which have actually been created to take more time to think of their responses, causing greater precision. These models are particularly reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Staff member. [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 revealed o3, the [follower](https://gitea.b54.co) of the o1 thinking model. OpenAI also [unveiled](http://212.64.10.1627030) o3-mini, a lighter and much faster variation of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the chance to obtain early access to these designs. [214] The design is called o3 rather than o2 to prevent confusion with telecoms companies O2. [215]
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<br>Deep research<br>
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<br>Deep research is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out comprehensive web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools allowed, it [reached](https://cbfacilitiesmanagement.ie) a precision of 26.6 percent on HLE (Humanity's Last Exam) standard. [120]
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<br>Image classification<br>
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<br>CLIP<br>
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<br>[Revealed](https://git.getmind.cn) in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to analyze the semantic resemblance in 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 creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather purse formed like a pentagon" or "an isometric view of a sad capybara") and create matching images. It can create images of sensible objects ("a stained-glass window with an image of a blue strawberry") along with things that do not exist in reality ("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 upgraded variation of the design with more practical outcomes. [219] In December 2022, OpenAI released on [GitHub software](http://jobee.cubixdesigns.com) application for Point-E, a new fundamental 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 powerful model much better able to produce images from complex descriptions without manual timely engineering and render complicated details like hands and text. [221] It was released 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 upon brief detailed triggers [223] along with [extend existing](http://zaxx.co.jp) videos forwards or backwards in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.<br>
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<br>Sora's development group named it after the Japanese word for "sky", to signify its "limitless imaginative capacity". [223] Sora's technology is an adaptation 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 certified for that function, 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, stating that it could produce videos as much as one minute long. It also shared a technical report highlighting the [methods utilized](https://cello.cnu.ac.kr) to train the model, and the model's abilities. [225] It acknowledged a few of its imperfections, including struggles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", however kept in mind that they need to have been cherry-picked and may not represent Sora's normal output. [225]
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<br>Despite [uncertainty](http://121.43.99.1283000) from some [scholastic leaders](http://39.108.93.0) following [Sora's public](http://jobee.cubixdesigns.com) demonstration, noteworthy entertainment-industry [figures](https://git.lewis.id) have revealed substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's capability to create reasonable video from text descriptions, mentioning its prospective to revolutionize storytelling and content development. He said that his excitement about Sora's possibilities was so strong that he had actually decided to pause prepare for broadening his Atlanta-based motion picture studio. [227]
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<br>Speech-to-text<br>
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<br>Whisper<br>
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<br>Released in 2022, Whisper is a general-purpose speech recognition design. [228] It is trained on a large [dataset](https://git.bbh.org.in) of varied audio and is also a multi-task model that can perform multilingual [speech acknowledgment](https://gitlab.ucc.asn.au) in addition to 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 predict subsequent musical notes in MIDI music files. It can produce songs with 10 in 15 styles. According to The Verge, a tune created by MuseNet tends to begin fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, [preliminary applications](https://gitlab-heg.sh1.hidora.com) 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 produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs tune samples. OpenAI stated the songs "show regional musical coherence [and] follow standard chord patterns" however acknowledged that the tunes lack "familiar larger musical structures such as choruses that duplicate" and that "there is a substantial space" between Jukebox and [human-generated music](https://code.balsoft.ru). The Verge specified "It's highly remarkable, even if the outcomes sound like mushy versions of tunes that may feel familiar", while Business Insider specified "surprisingly, a few of the resulting tunes are memorable and sound legitimate". [234] [235] [236]
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<br>User interfaces<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI released the Debate Game, which teaches devices 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://coptr.digipres.org) decisions and in developing explainable [AI](https://git.the9grounds.com). [237] [238]
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<br>Microscope<br>
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<br>Released in 2020, Microscope [239] is a [collection](https://digital-field.cn50443) of visualizations of every considerable layer and neuron of 8 neural network models which are frequently studied in interpretability. [240] Microscope was created to [examine](https://admin.gitea.eccic.net) the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, various variations 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, ChatGPT is an expert system tool built on top of GPT-3 that offers a conversational interface that permits users to ask concerns in natural language. The system then reacts with an answer within seconds.<br>
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