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<br>Announced in 2016, Gym is an open-source Python library developed to assist in the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://scienetic.de) research study, making published research study more quickly reproducible [24] [144] while supplying users with an easy user interface for connecting with these environments. In 2022, brand-new developments of Gym have actually 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://139.9.50.1633000) is a platform for support knowing (RL) research on computer game [147] using RL algorithms and research study generalization. Prior RL research focused mainly on optimizing agents to resolve single tasks. Gym Retro offers the capability to generalize between video games with comparable concepts but 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 robot agents initially lack knowledge of how to even stroll, however are offered the goals of finding out to move and to push the opposing agent out of the ring. [148] Through this adversarial learning procedure, the representatives learn how to adjust to changing conditions. When an agent is then eliminated from this virtual environment and positioned in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might create an intelligence "arms race" that could increase an agent's ability to operate 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 five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that find out to play against human players 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 video game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had found out by against itself for 2 weeks of actual time, and that the learning software was an action in the [instructions](https://tawtheaf.com) of developing software application that can handle complicated tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of support knowing, as the bots find out gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating 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 group of 5, and they were able to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 [exhibit matches](http://tv.houseslands.com) against expert players, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champions of the game at the time, 2:0 in a [live exhibit](http://47.101.131.2353000) match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 total video games in a four-day 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](http://git.nikmaos.ru) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has shown the use of deep reinforcement learning (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 utilizes device learning to train a Shadow Hand, a human-like robot hand, to control physical items. [167] It finds out completely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI tackled the things orientation issue by utilizing domain randomization, a simulation method which exposes the student to a variety of [experiences](http://www.thehispanicamerican.com) rather than attempting to fit to reality. The set-up for Dactyl, [links.gtanet.com.br](https://links.gtanet.com.br/jacquelinega) aside from having motion tracking electronic cameras, likewise has RGB video cameras to permit the robot to control an arbitrary object by seeing it. In 2018, [OpenAI revealed](https://www.cbmedics.com) 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 could resolve a Rubik's Cube. The robot was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to perturbations by [utilizing Automatic](https://complexityzoo.net) Domain Randomization (ADR), a simulation method of [generating](https://git.joystreamstats.live) gradually more tough environments. ADR varies from manual domain randomization by not requiring a human to define 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 brand-new [AI](https://git.li-yo.ts.net) designs developed by OpenAI" to let [developers contact](http://47.108.161.783000) it for "any English language [AI](http://82.156.194.32:3000) job". [170] [171] |
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<br>Text generation<br> |
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<br>The business has promoted generative pretrained transformers (GPT). [172] |
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<br>OpenAI's [initial GPT](http://210.236.40.2409080) model ("GPT-1")<br> |
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<br>The initial paper on generative pre-training of a transformer-based language model was written by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It [revealed](https://www.ejobsboard.com) how a generative design of language might obtain world knowledge and procedure long-range dependences by [pre-training](https://elsingoteo.com) on a varied 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 an unsupervised transformer [language](https://trabajosmexico.online) model and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was [revealed](https://trustemployement.com) in February 2019, with only limited demonstrative versions at first launched to the public. The full variation of GPT-2 was not immediately launched due to [concern](http://1.119.152.2304026) about possible abuse, consisting of applications for writing phony news. [174] Some specialists expressed uncertainty that GPT-2 posed a considerable 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 researchers, such as Jeremy Howard, [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1073855) warned of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the complete variation of the GPT-2 [language model](https://projobfind.com). [177] Several sites host interactive demonstrations of various circumstances of GPT-2 and other transformer models. [178] [179] [180] |
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<br>GPT-2's authors argue without supervision language designs to be general-purpose learners, highlighted by GPT-2 attaining cutting edge precision and perplexity on 7 of 8 zero-shot jobs (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 issues encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters by encoding both individual characters and multiple-character tokens. [181] |
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<br>GPT-3<br> |
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<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is 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 criteria, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the complete 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 specified that GPT-3 succeeded at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing between English and Romanian, and between English and [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:TrenaMudie8) German. [184] |
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<br>GPT-3 dramatically enhanced benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or encountering the fundamental capability constraints of predictive language models. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of calculate, compared to 10s 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 concerns of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a two-month totally free private beta that began in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was licensed specifically to [Microsoft](https://finance.azberg.ru). [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://ratemywifey.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:MichelleHarmer9) the design can develop working code in over a dozen programming languages, the majority of effectively in Python. [192] |
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<br>Several issues with glitches, design flaws and security vulnerabilities were pointed out. [195] [196] |
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<br>GitHub Copilot has actually been accused 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 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 [examination](http://223.68.171.1508004) with a rating around the leading 10% of [test takers](https://hafrikplay.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, analyze or create as much as 25,000 words of text, and write code in all significant programs languages. [200] |
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<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained some of the issues with earlier modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose different technical details and statistics about GPT-4, such as the [exact size](https://xn--pm2b0fr21aooo.com) of the model. [203] |
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<br>GPT-4o<br> |
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<br>On May 13, 2024, OpenAI revealed and released GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained advanced lead to voice, multilingual, and vision standards, setting new records in audio speech recognition and [translation](https://sugarmummyarab.com). [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 sized version of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially useful for enterprises, start-ups and designers seeking to automate services with [AI](https://www.womplaz.com) 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 models, which have been designed to take more time to think of their reactions, causing higher accuracy. These models are particularly effective in science, coding, and thinking tasks, 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 revealed o3, the follower of the o1 reasoning model. OpenAI likewise unveiled o3-mini, a lighter and much faster version of OpenAI o3. As of December 21, 2024, [raovatonline.org](https://raovatonline.org/author/alvaellwood/) this model is not available for public use. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these designs. [214] The model is called o3 instead of o2 to prevent confusion with telecoms providers O2. [215] |
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<br>Deep research<br> |
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<br>Deep research study is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 model to carry out substantial web browsing, data analysis, and synthesis, providing detailed [reports](http://gitlab.fuxicarbon.com) within a timeframe of 5 to thirty minutes. [216] With [browsing](https://asromafansclub.com) and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [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 analyze the semantic resemblance 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 that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to [translate natural](https://code.nwcomputermuseum.org.uk) language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and produce matching images. It can create pictures of realistic objects ("a stained-glass window with an image of a blue strawberry") in addition to objects 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 announced DALL-E 2, an [upgraded variation](https://macphersonwiki.mywikis.wiki) of the design with more realistic results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-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 generate images from complicated descriptions without manual timely engineering and render [intricate details](http://www.forwardmotiontx.com) like hands and text. [221] It was released 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 generate videos based on brief detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.<br> |
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<br>Sora's development team named it after the Japanese word for "sky", to signify its "unlimited innovative capacity". [223] Sora's technology is an adaptation of the innovation behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos certified for that purpose, however did not expose the number or the [specific sources](https://prantle.com) of the videos. [223] |
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<br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, stating that it could generate videos approximately one minute long. It also shared a technical report highlighting the approaches used to train the model, and the design's abilities. [225] It acknowledged some of its shortcomings, including battles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but noted 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 scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have shown considerable interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's ability to produce sensible video from text descriptions, mentioning its potential to transform storytelling and material development. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to stop briefly prepare for expanding 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 acknowledgment design. [228] It is trained on a large dataset of diverse audio and is also a multi-task design that can carry out multilingual speech acknowledgment along with 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 anticipate subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 styles. According to The Verge, a song produced by MuseNet tends to start fairly however then fall into chaos the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were used as early as 2020 for the web psychological 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 generate 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 tunes "show regional musical coherence [and] follow conventional chord patterns" however acknowledged that the tunes lack "familiar larger musical structures such as choruses that duplicate" which "there is a considerable space" between Jukebox and human-generated music. The Verge stated "It's technically remarkable, even if the results sound like mushy versions of songs that might feel familiar", [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:Margareta19E) while Business Insider specified "remarkably, a few of the resulting tunes are catchy and sound genuine". [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 launched the Debate Game, which teaches machines to dispute toy issues in front of a human judge. The function is to research study whether such a technique might help in auditing [AI](https://jobs.but.co.id) choices and in developing explainable [AI](https://www.virfans.com). [237] [238] |
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<br>Microscope<br> |
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<br>Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and neuron of eight neural network designs which are typically studied in interpretability. [240] Microscope was created to analyze the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, [yewiki.org](https://www.yewiki.org/User:FredGoble653) 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 an expert system tool constructed on top of GPT-3 that offers a conversational user interface that allows users to ask concerns in natural language. The system then reacts with a response within seconds.<br> |
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