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<br>Announced in 2016, Gym is an open-source Python library designed to help with the development of support knowing algorithms. It aimed to standardize how environments are specified in [AI](https://dimans.mx) research, making published research more easily reproducible [24] [144] while offering users with an easy user interface for engaging with these environments. In 2022, new advancements of Gym have actually been transferred 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://sdongha.com) is a platform for [reinforcement knowing](https://www.footballclubfans.com) (RL) research on video games [147] using RL algorithms and research study generalization. Prior RL research focused mainly on optimizing representatives to resolve single jobs. Gym Retro gives the ability to generalize in between video games with comparable ideas however different looks.<br> |
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<br>RoboSumo<br> |
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<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives at first do not have knowledge of how to even walk, but are given the goals of finding out to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing process, the agents discover how to adapt to changing conditions. When a representative is then eliminated from this virtual environment and placed in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had actually found out how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives could develop 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 group of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that learn to play against human gamers at a high [skill level](https://git.aaronmanning.net) entirely through experimental algorithms. Before ending up being a group of 5, the first public demonstration took place at The [International](https://ixoye.do) 2017, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) the annual best championship competition for the game, where Dendi, an expert Ukrainian player, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for two weeks of real time, and that the learning software was a step in the direction of developing software application that can handle complex jobs like a cosmetic surgeon. [152] [153] The system uses a type of reinforcement knowing, as the [bots learn](http://git.zonaweb.com.br3000) gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156] |
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<br>By June 2018, the ability of the bots expanded to play together as a full group of 5, and they had the ability to defeat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against expert gamers, however wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated 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' final public appearance 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 mechanisms in Dota 2's bot gamer shows the obstacles of [AI](http://wecomy.co.kr) systems in multiplayer online [battle arena](http://private.flyautomation.net82) (MOBA) games and how OpenAI Five has actually shown making use of deep support knowing (DRL) agents to attain superhuman [proficiency](http://8.137.85.1813000) in Dota 2 matches. [166] |
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<br>Dactyl<br> |
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<br>Developed in 2018, Dactyl utilizes machine finding out to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It learns totally in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI took on the things orientation issue by using domain randomization, a simulation technique which exposes the learner to a range of experiences instead of attempting to fit to reality. The set-up for Dactyl, aside from having motion tracking cams, likewise has RGB video cameras to permit the robotic to control an approximate object by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI demonstrated that Dactyl might solve a [Rubik's Cube](http://47.97.159.1443000). The robotic was able to solve 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 [effectiveness](https://jobsportal.harleysltd.com) of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of producing gradually more tough environments. ADR varies from manual domain randomization by not needing a human to define 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 brand-new [AI](http://compass-framework.com:3000) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](http://git.setech.ltd:8300) task". [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 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 coworkers, and released in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative design of language might obtain world knowledge and procedure long-range reliances by pre-training on a [varied corpus](http://119.130.113.2453000) 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 follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative versions initially released to the public. The full version of GPT-2 was not immediately launched due to issue about potential abuse, consisting of applications for writing fake news. [174] Some experts revealed uncertainty that GPT-2 posed a .<br> |
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<br>In action to GPT-2, the Allen Institute for [Artificial Intelligence](https://www.runsimon.com) [responded](https://jandlfabricating.com) with a tool to discover "neural phony news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation to totally 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 variation of the GPT-2 language design. [177] Several sites host interactive demonstrations of various instances of GPT-2 and other transformer designs. [178] [179] [180] |
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<br>GPT-2's authors argue [unsupervised language](http://49.232.207.1133000) designs to be general-purpose students, shown by GPT-2 attaining advanced precision and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not [additional trained](https://www.telewolves.com) 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 prevents certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This permits 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 design and the follower to GPT-2. [182] [183] [184] OpenAI stated that the complete version of GPT-3 contained 175 billion specifications, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as few as 125 million specifications were also trained). [186] |
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<br>OpenAI stated that GPT-3 prospered 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 learning between English and Romanian, and between English and German. [184] |
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<br>GPT-3 considerably improved [benchmark outcomes](https://afrocinema.org) over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or experiencing the essential ability constraints of predictive language models. [187] Pre-training GPT-3 required a number of thousand [larsaluarna.se](http://www.larsaluarna.se/index.php/User:TraceySimmonds) petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately launched to the public for issues of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month complimentary personal beta that began in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was [certified exclusively](http://wrs.spdns.eu) 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 additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://101.200.241.6:3000) 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 develop working code in over a dozen programming languages, most successfully in Python. [192] |
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<br>Several issues with problems, style defects and security vulnerabilities were cited. [195] [196] |
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<br>GitHub Copilot has actually been accused of giving off copyrighted code, without any [author attribution](https://git.noisolation.com) or license. [197] |
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<br>OpenAI announced that they would discontinue 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](https://gajaphil.com) Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar examination with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise check out, evaluate or create up to 25,000 words of text, and compose code in all significant programs languages. [200] |
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<br>Observers reported that the model of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has declined to reveal various technical details and [demo.qkseo.in](http://demo.qkseo.in/profile.php?id=1016708) statistics about GPT-4, such as the [accurate size](https://gitlab.chabokan.net) of the design. [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 create text, images and audio. [204] GPT-4o attained cutting edge outcomes in voice, multilingual, and vision standards, setting new records in audio speech acknowledgment 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 version of GPT-4o changing GPT-3.5 Turbo on the ChatGPT interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. [OpenAI expects](https://wegoemploi.com) it to be particularly useful for enterprises, start-ups and developers looking for to automate services with [AI](https://www.uaelaboursupply.ae) representatives. [208] |
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<br>o1<br> |
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<br>On September 12, 2024, [OpenAI released](http://fujino-mori.com) the o1-preview and o1-mini designs, which have been created to take more time to think of their actions, leading to higher accuracy. These models are especially reliable in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was [changed](https://optimiserenergy.com) by o1. [211] |
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<br>o3<br> |
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<br>On December 20, 2024, OpenAI unveiled o3, the successor of the o1 reasoning design. OpenAI likewise revealed o3-mini, a lighter and faster version of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are [testing](http://1.15.187.67) o3 and o3-mini. [212] [213] Until January 10, 2025, security and [security scientists](http://www.carnevalecommunity.it) had the chance to obtain early access to these designs. [214] The design is called o3 instead of o2 to avoid confusion with telecoms companies O2. [215] |
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<br>Deep research study<br> |
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<br>Deep research study is an agent established by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to [perform comprehensive](https://wiki.communitydata.science) web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With [browsing](http://repo.z1.mastarjeta.net) and Python tools enabled, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] |
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<br>Image classification<br> |
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<br>CLIP<br> |
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<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to examine the semantic similarity between text and images. It can especially 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 model that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to analyze natural [language inputs](https://git.tbaer.de) (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate matching images. It can create pictures of realistic items ("a stained-glass window with an image of a blue strawberry") as well as items that do not exist in truth ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.<br> |
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<br>DALL-E 2<br> |
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<br>In April 2022, OpenAI revealed DALL-E 2, an upgraded variation of the design with more sensible outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new fundamental system for converting a text description into a 3[-dimensional design](https://links.gtanet.com.br). [220] |
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<br>DALL-E 3<br> |
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<br>In September 2023, OpenAI revealed DALL-E 3, a more effective model much better able to produce images from [intricate descriptions](https://spiritustv.com) without manual timely engineering and [render intricate](http://coastalplainplants.org) details like hands and text. [221] It was launched to the 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 create videos based on brief detailed prompts [223] along with extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.<br> |
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<br>Sora's development team named it after the Japanese word for "sky", to represent its "endless innovative capacity". [223] Sora's innovation is an adjustment of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos accredited for that purpose, however did not reveal the number or the exact sources of the videos. [223] |
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<br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, stating that it might generate videos as much as one minute long. It likewise shared a technical report highlighting the techniques used to train the model, and the model's abilities. [225] It acknowledged a few of its shortcomings, consisting of struggles imitating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", however noted that they should have been cherry-picked and may not represent Sora's common output. [225] |
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<br>Despite uncertainty from some scholastic leaders following Sora's public demo, significant entertainment-industry figures have actually shown significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the innovation's ability to produce sensible video from text descriptions, mentioning its potential to revolutionize storytelling and content development. He said that his excitement 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 recognition design. [228] It is trained on a large dataset of diverse audio and is likewise a [multi-task](http://macrocc.com3000) model that can perform 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 [forecast subsequent](http://ufidahz.com.cn9015) musical notes in MIDI music files. It can create tunes 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, preliminary applications of this tool were utilized as early as 2020 for the internet 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 produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs song samples. OpenAI stated the songs "show local musical coherence [and] follow traditional chord patterns" however acknowledged that the songs lack "familiar bigger musical structures such as choruses that duplicate" and that "there is a significant space" in between Jukebox and human-generated music. The Verge stated "It's technically outstanding, even if the results seem like mushy variations of songs that might feel familiar", while Business Insider specified "remarkably, some of the resulting tunes are catchy 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 launched the Debate Game, which [teaches machines](https://git.fracturedcode.net) to debate toy problems in front of a human judge. The function is to research whether such a method may assist in auditing [AI](http://private.flyautomation.net:82) decisions and in [establishing explainable](https://owangee.com) [AI](https://www.sportfansunite.com). [237] [238] |
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<br>Microscope<br> |
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<br>[Released](http://39.105.128.46) in 2020, Microscope [239] is a collection of visualizations of every substantial layer and nerve cell of eight neural network models which are frequently studied in interpretability. [240] Microscope was produced to analyze the functions that form inside these neural networks easily. The designs included are AlexNet, VGG-19, different versions of Inception, and different variations of CLIP Resnet. [241] |
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<br>ChatGPT<br> |
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<br>Launched in November 2022, [ChatGPT](http://shiningon.top) is an expert system tool constructed on top of GPT-3 that supplies a conversational user interface that permits users to ask questions in natural language. The system then reacts with an answer within seconds.<br> |
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