Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library created to facilitate the development of [reinforcement knowing](http://47.99.119.17313000) algorithms. It aimed to standardize how environments are defined in [AI](http://www.letts.org) research study, making released research study more easily reproducible [24] [144] while supplying users with a simple interface for interacting with these environments. In 2022, brand-new developments of Gym have been moved to the library Gymnasium. [145] [146]
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<br>Gym Retro<br>
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<br>[Released](https://jobsportal.harleysltd.com) in 2018, Gym Retro is a [platform](https://octomo.co.uk) for support knowing (RL) research on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on optimizing representatives to resolve single jobs. Gym Retro provides the ability to generalize between video games with similar concepts but different looks.<br>
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<br>RoboSumo<br>
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<br>Released in 2017, RoboSumo is a [virtual](https://git.hitchhiker-linux.org) world where humanoid metalearning robot representatives at first lack understanding of how to even walk, however are provided the goals of [finding](http://grainfather.co.uk) out to move and to push the opposing agent out of the ring. [148] Through this adversarial learning procedure, the representatives discover how to adapt to altering conditions. When a representative is then gotten rid of from this virtual environment and placed in a new [virtual](https://thefreedommovement.ca) environment with high winds, the representative braces to remain upright, recommending it had discovered how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives could produce an intelligence "arms race" that could increase an agent's ability to work 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 used in the competitive [five-on-five video](https://tocgitlab.laiye.com) game Dota 2, that discover to play against human players at a high ability level totally through trial-and-error algorithms. Before becoming a group of 5, the first public presentation occurred at The [International](https://kanjob.de) 2017, the yearly best champion competition for the video game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had found out by playing against itself for 2 weeks of real time, which the learning software application was an action in the instructions of creating software that can deal with intricate jobs like a cosmetic surgeon. [152] [153] The system utilizes a kind of reinforcement knowing, as the bots find out gradually by playing against themselves numerous times a day for months, and [gratisafhalen.be](https://gratisafhalen.be/author/rebbeca9609/) are rewarded for actions such as killing an opponent and taking map objectives. [154] [155] [156]
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<br>By June 2018, [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1076849) the ability of the [bots expanded](https://teengigs.fun) to play together as a complete team of 5, and they had the [ability](https://eliteyachtsclub.com) to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against [professional](https://git.whistledev.com) players, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last [public appearance](https://mtglobalsolutionsinc.com) came later that month, where they played in 42,729 overall games in a [four-day](https://kaymack.careers) 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 difficulties of [AI](http://lethbridgegirlsrockcamp.com) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated using deep reinforcement learning (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 uses machine finding out to train a Shadow Hand, a [human-like robot](http://221.239.90.673000) hand, [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:SamualGuillen) to control physical things. [167] It finds out completely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI took on the things orientation problem by utilizing domain randomization, a simulation technique which exposes the student to a variety of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having movement tracking cameras, likewise has RGB cameras to enable the robotic to control an arbitrary things by seeing it. In 2018, OpenAI revealed that the system had the ability to manipulate a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI showed that Dactyl might resolve a Rubik's Cube. The robot was able to [resolve](https://www.keyfirst.co.uk) the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to design. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of producing gradually harder environments. ADR differs from manual domain randomization by not needing a human to specify 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 new [AI](http://123.207.52.103:3000) models established by OpenAI" to let [designers contact](http://tools.refinecolor.com) it for "any English language [AI](https://healthcarejob.cz) task". [170] [171]
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<br>Text generation<br>
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<br>The business has actually popularized generative pretrained transformers (GPT). [172]
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<br>OpenAI's initial GPT model ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language design was written by Alec Radford and his coworkers, and released in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative model of language could obtain world understanding and procedure long-range dependences by pre-training 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 a not being watched transformer language model and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative variations initially released to the general public. The full version of GPT-2 was not right away released due to issue about [prospective](https://wolvesbaneuo.com) abuse, including applications for composing phony news. [174] Some specialists expressed uncertainty that GPT-2 postured a significant hazard.<br>
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to identify "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned of "the innovation to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the complete variation of the GPT-2 language model. [177] Several websites host interactive presentations of different instances of GPT-2 and other [transformer models](https://music.afrisolentertainment.com). [178] [179] [180]
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<br>GPT-2's authors argue without supervision language designs to be [general-purpose](https://okk-shop.com) students, shown by GPT-2 attaining advanced precision and perplexity on 7 of 8 [zero-shot tasks](https://freelancejobsbd.com) (i.e. the design 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 somewhat 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](https://www.dpfremovalnottingham.com) pair encoding. This permits representing any string of characters by [encoding](http://park1.wakwak.com) 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 an unsupervised transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete version of GPT-3 contained 175 billion specifications, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million criteria were also trained). [186]
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<br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the function of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing in between English and Romanian, [wavedream.wiki](https://wavedream.wiki/index.php/User:Fausto73W963) and between English and German. [184]
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<br>GPT-3 significantly enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language models might be [approaching](http://112.124.19.388080) or coming across the fundamental 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 model. [184] Like its predecessor, [174] the GPT-3 trained design was not right away released to the public for concerns of possible abuse, although OpenAI planned to allow gain access to through a paid cloud API after a two-month complimentary personal beta that started in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was certified specifically 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 been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://orcz.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the design can develop working code in over a dozen programming languages, a lot of [efficiently](http://www.zhihutech.com) in Python. [192]
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<br>Several issues with glitches, style defects and security vulnerabilities were cited. [195] [196]
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<br>GitHub Copilot has actually been implicated of discharging copyrighted code, without any author attribution or license. [197]
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<br>OpenAI revealed 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 announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the updated innovation passed a simulated law school bar examination with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, evaluate or produce as much as 25,000 words of text, and compose code in all [major programs](https://vezonne.com) 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 version, with the caution that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually declined to expose different technical details and statistics about GPT-4, such as the accurate size of the design. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained state-of-the-art outcomes in voice, multilingual, and vision criteria, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) benchmark 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 anticipates it to be particularly helpful for enterprises, start-ups and designers looking for to automate services with [AI](http://wp10476777.server-he.de) 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 been created to take more time to think of their reactions, resulting in higher accuracy. These models are especially efficient in science, coding, and reasoning 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 successor of the o1 reasoning model. OpenAI also revealed o3-mini, a lighter and quicker version of OpenAI o3. As of December 21, 2024, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) this model 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 opportunity to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecommunications services supplier O2. [215]
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<br>Deep research<br>
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<br>Deep research is a representative established by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform extensive web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and [Python tools](http://124.221.255.92) allowed, 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 evaluate the semantic similarity in between text and images. It can significantly 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 design that [produces](https://noxxxx.com) images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of an unfortunate capybara") and create corresponding images. It can produce pictures of sensible items ("a stained-glass window with an image of a blue strawberry") as well as objects 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 announced DALL-E 2, an upgraded version of the design with more reasonable results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new fundamental system for transforming a text description into a 3-dimensional model. [220]
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<br>DALL-E 3<br>
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<br>In September 2023, OpenAI announced DALL-E 3, a more powerful model much better able to produce images from intricate descriptions without manual timely engineering and render complicated details like hands and text. [221] It was released 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 produce videos based on short detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of produced videos is unidentified.<br>
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<br>Sora's advancement group called it after the Japanese word for "sky", to signify its "endless imaginative capacity". [223] Sora's technology is an adjustment 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 licensed for that function, however did not expose the number or the specific sources of the videos. [223]
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<br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it could generate videos up to one minute long. It also shared a technical report highlighting the approaches utilized to train the design, and the model's abilities. [225] It acknowledged some of its imperfections, including struggles mimicing intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but noted that they need to have been cherry-picked and may not represent Sora's common output. [225]
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<br>Despite uncertainty from some academic leaders following Sora's public demonstration, significant entertainment-industry figures have actually shown considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's ability to [generate realistic](http://39.101.134.269800) video from text descriptions, citing its prospective to reinvent storytelling and material development. He said that his enjoyment about Sora's possibilities was so strong that he had chosen 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 model. [228] It is trained on a large dataset of varied audio and is also a multi-task model that can carry out multilingual speech recognition 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 predict subsequent musical notes in MIDI music files. It can produce songs with 10 instruments in 15 styles. According to The Verge, a tune generated by MuseNet tends to start fairly however then fall into turmoil the longer it plays. [230] [231] In pop culture, preliminary applications 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 generate music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs tune samples. OpenAI stated the tunes "reveal local musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" which "there is a considerable space" between Jukebox and human-generated music. The Verge stated "It's technically excellent, even if the outcomes sound like mushy versions of songs that may feel familiar", while Business Insider mentioned "remarkably, a few 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 makers to debate toy problems in front of a human judge. The function is to research study whether such a method may help in auditing [AI](http://test-www.writebug.com:3000) choices and in developing explainable [AI](http://124.223.100.38:3000). [237] [238]
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<br>Microscope<br>
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<br>Released in 2020, Microscope [239] is a [collection](http://www.thynkjobs.com) of visualizations of every substantial layer and neuron of 8 neural network [designs](https://www.wow-z.com) which are typically studied in interpretability. [240] [Microscope](http://ccrr.ru) was produced to evaluate the features that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, various variations of Inception, and various variations of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, ChatGPT is an [artificial intelligence](https://netgork.com) tool developed on top of GPT-3 that supplies a conversational interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.<br>
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