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<br>Announced in 2016, Gym is an open-source Python library [developed](https://onthewaytohell.com) to assist in the development of support knowing algorithms. It aimed to [standardize](http://experienciacortazar.com.ar) how environments are specified in [AI](https://exajob.com) research study, making published research more quickly [reproducible](https://jobs.competelikepros.com) [24] [144] while supplying users with an easy user interface for engaging with these environments. In 2022, [brand-new advancements](https://feleempleo.es) 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 is a platform for support learning (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on enhancing agents to [solve single](https://nojoom.net) tasks. Gym Retro gives the ability to generalize between video games with similar ideas but various 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 walk, but are offered the objectives of learning to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the agents discover how to adjust to changing conditions. When an agent is then removed from this virtual environment and positioned in a brand-new virtual environment with high winds, the representative braces to remain upright, suggesting it had learned how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives might create an intelligence "arms race" that might increase a representative's capability to function even outside the context of the [competition](https://quikconnect.us). [148] |
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<br>OpenAI 5<br> |
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<br>OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that discover to play against human gamers at a high skill level completely through trial-and-error algorithms. Before becoming a group of 5, the first public demonstration took place at The International 2017, the annual best championship tournament for the video game, where Dendi, an [expert Ukrainian](https://git.gumoio.com) player, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually learned by playing against itself for 2 weeks of genuine time, and that the knowing software application was a step in the direction of [developing software](http://39.105.129.2293000) application that can deal with complicated tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of reinforcement knowing, as the bots find out with time by playing against themselves hundreds of times a day for months, and are rewarded for [actions](https://www.employment.bz) such as killing an opponent and taking map goals. [154] [155] [156] |
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<br>By June 2018, the [ability](http://221.229.103.5563010) of the bots broadened to play together as a complete group of 5, and they were able to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two [exhibition matches](https://www.rozgar.site) against expert players, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs of the game at the time, 2:0 in a live exhibition match in [San Francisco](https://vagas.grupooportunityrh.com.br). [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 competitors, winning 99.4% of those video games. [165] |
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<br>OpenAI 5's mechanisms in Dota 2's bot player reveals the difficulties of [AI](https://git.l1.media) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually 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 uses [machine finding](http://120.77.2.937000) out to train a Shadow Hand, a human-like robot hand, to manipulate physical items. [167] It finds out completely in [simulation utilizing](http://gitea.ucarmesin.de) the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the item orientation problem by using domain randomization, a simulation technique which exposes the student to a range of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having movement tracking electronic cameras, likewise has RGB cameras to allow the robotic to manipulate an approximate item 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 demonstrated that Dactyl could resolve a Rubik's Cube. The robotic was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by improving the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of creating gradually harder environments. ADR differs from manual domain randomization by not needing a human to [define randomization](https://git.profect.de) 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](http://personal-view.com) designs established by OpenAI" to let designers call on it for "any English language [AI](https://forum.tinycircuits.com) job". [170] [171] |
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<br>Text generation<br> |
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<br>The business has popularized generative pretrained [transformers](https://git.torrents-csv.com) (GPT). [172] |
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<br>OpenAI's original GPT design ("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 site on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world knowledge and process long-range dependencies 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 without supervision transformer language model and the successor to [OpenAI's initial](https://nexthub.live) GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just restricted demonstrative variations initially launched to the public. The full version of GPT-2 was not instantly released due to concern about potential abuse, consisting of applications for writing phony news. [174] Some experts expressed uncertainty that GPT-2 positioned a significant threat.<br> |
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<br>In action to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to discover "neural phony news". [175] Other researchers, such as Jeremy Howard, alerted of "the innovation to absolutely 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 released the total variation of the GPT-2 language design. [177] Several sites host interactive demonstrations of various circumstances of GPT-2 and other transformer designs. [178] [179] [180] |
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<br>GPT-2's authors argue unsupervised [language models](http://120.46.37.2433000) to be general-purpose students, highlighted by GPT-2 attaining cutting edge precision and perplexity on 7 of 8 [zero-shot jobs](http://www.asiapp.co.kr) (i.e. the design was not additional trained on any task-specific input-output examples).<br> |
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<br>The corpus it was trained on, called WebText, contains somewhat 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents certain problems encoding vocabulary with word tokens by using byte pair encoding. This allows representing any string of characters by [encoding](https://gitea.qianking.xyz3443) both specific 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 mentioned that the complete variation of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude larger 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 specified that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer knowing between English and Romanian, [raovatonline.org](https://raovatonline.org/author/yllhilton18/) and in between English and German. [184] |
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<br>GPT-3 considerably enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or experiencing the essential ability constraints of predictive language models. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately launched to the general public for concerns of possible abuse, although OpenAI planned to allow [gain access](https://www.ontheballpersonnel.com.au) to through a paid cloud API after a two-month totally free private beta that started in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was certified solely 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](http://git.guandanmaster.com) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.privateger.me) 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 create working code in over a lots programming languages, most successfully in Python. [192] |
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<br>Several concerns with glitches, style defects and security vulnerabilities were cited. [195] [196] |
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<br>GitHub Copilot has actually been accused of releasing copyrighted code, with no author attribution or license. [197] |
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<br>OpenAI revealed that they would stop support for Codex API on March 23, 2023. [198] |
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<br>GPT-4<br> |
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<br>On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in [accepting text](http://202.90.141.173000) or image inputs. [199] They announced that the updated innovation passed a simulated law school bar test with a score around the leading 10% of [test takers](http://hybrid-forum.ru). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, analyze or generate 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 using GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained some of the issues with earlier modifications. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal numerous technical [details](https://git.privateger.me) and stats about GPT-4, such as the accurate size 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 cutting edge outcomes in voice, multilingual, and vision benchmarks, setting new records in [audio speech](http://bryggeriklubben.se) recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language (MMLU) standard compared to 86.5% by GPT-4. [207] |
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<br>On July 18, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:MittieBusch3064) 2024, OpenAI released GPT-4o mini, a smaller variation of GPT-4o changing GPT-3.5 Turbo on the ChatGPT user interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially useful for enterprises, start-ups and designers looking for to automate services with [AI](https://ipmanage.sumedangkab.go.id) representatives. [208] |
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<br>o1<br> |
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<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have actually been created to take more time to think of their responses, resulting in greater precision. These models are particularly reliable 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 unveiled o3, the follower of the o1 thinking design. OpenAI likewise unveiled o3-mini, a lighter and faster version of OpenAI o3. Since December 21, 2024, this design is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the chance to obtain early access to these models. [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 established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to perform comprehensive web browsing, information 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](https://git.christophhagen.de) 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 examine the semantic resemblance between text and [wavedream.wiki](https://wavedream.wiki/index.php/User:MargieMakin668) images. It can significantly 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 version of GPT-3 to translate natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of a sad capybara") and generate matching images. It can develop images of realistic items ("a stained-glass window with a picture of a blue strawberry") in addition to 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 practical outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new simple 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 revealed DALL-E 3, a more powerful model much better able to produce images from complicated 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 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 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 up to 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.<br> |
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<br>Sora's development team named it after the Japanese word for "sky", to symbolize its "limitless creative potential". [223] Sora's technology is an [adjustment](http://sl860.com) of the technology behind the DALL · E 3 [text-to-image](https://newsfast.online) model. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos certified for that function, but did not reveal the number or the precise sources of the videos. [223] |
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<br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it could create videos up to one minute long. It likewise shared a technical report highlighting the methods utilized to train the model, and the model's abilities. [225] It acknowledged some of its imperfections, consisting of struggles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", however kept in mind that they must have been cherry-picked and might not represent Sora's typical output. [225] |
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<br>Despite uncertainty from some scholastic leaders following Sora's public demo, significant entertainment-industry figures have revealed considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the [technology's capability](https://forum.batman.gainedge.org) to [generate](https://gogs.dev.dazesoft.cn) sensible video from text descriptions, mentioning its potential to [revolutionize storytelling](http://180.76.133.25316300) and content creation. He said that his excitement about Sora's possibilities was so strong that he had actually chosen 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](https://publiccharters.org) on a large dataset of varied audio and is also a multi-task model that can perform multilingual [speech acknowledgment](http://mao2000.com3000) as well as 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](http://104.248.138.208) in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to [start fairly](https://gitlab.henrik.ninja) but then fall into turmoil the longer it plays. [230] [231] In [popular](http://colorroom.net) culture, initial applications of this tool were used as early as 2020 for the web mental thriller Ben Drowned to develop music for the titular character. [232] [233] |
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<br>Jukebox<br> |
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<br>Released in 2020, Jukebox is an open-sourced algorithm to create music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs song samples. OpenAI mentioned the songs "reveal local musical coherence [and] follow conventional chord patterns" however acknowledged that the songs do not have "familiar larger musical structures such as choruses that repeat" which "there is a considerable space" between Jukebox and human-generated music. The Verge specified "It's technologically remarkable, even if the outcomes sound like mushy versions of tunes that may feel familiar", while Business Insider specified "surprisingly, some of the resulting songs 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 introduced the Debate Game, which teaches makers to dispute toy problems in front of a human judge. The function is to research study whether such a method might assist in auditing [AI](http://macrocc.com:3000) choices and in developing explainable [AI](https://weldersfabricators.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 considerable layer and neuron of 8 neural network models which are typically studied in interpretability. [240] [Microscope](https://orka.org.rs) was created to [analyze](https://www.activeline.com.au) the features that form inside these [neural networks](https://prazskypantheon.cz) quickly. The models consisted of are AlexNet, VGG-19, various 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](https://git.wyling.cn) is an expert system tool built on top of GPT-3 that supplies 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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