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<br>Announced in 2016, Gym is an open-source Python library created to facilitate the development of support knowing algorithms. It aimed to standardize how environments are specified in [AI](http://42.192.95.179) research, making published research study more quickly reproducible [24] [144] while offering users with an easy interface for communicating 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 is a platform for reinforcement learning (RL) research on video games [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing agents to fix single jobs. Gym Retro gives the capability to generalize in between games with similar principles however 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 robotic agents at first do not have understanding of how to even walk, however are offered the goals of finding out to move and to push the opposing representative out of the ring. [148] Through this adversarial learning procedure, the [representatives learn](https://jobdd.de) how to adapt to [changing conditions](https://doum.cn). When an agent is then removed from this virtual environment and put in a brand-new virtual environment with high winds, the agent braces to remain upright, recommending it had actually discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives might produce an intelligence "arms race" that might increase an agent's ability to operate even outside the context of the competition. [148] |
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<br>OpenAI 5<br> |
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<br>OpenAI Five is a team of 5 OpenAI-curated bots used 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 team of 5, the first public demonstration [occurred](https://surmodels.com) at The International 2017, the yearly best champion competition for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one 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 an action in the instructions of developing software application that can handle complicated tasks like a cosmetic surgeon. [152] [153] The system [utilizes](https://thaisfriendly.com) a kind of support knowing, as the bots find out with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an enemy and taking map goals. [154] [155] [156] |
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<br>By June 2018, the ability of the bots expanded to play together as a complete team of 5, and they had the ability to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The [International](https://lidoo.com.br) 2018, OpenAI Five played in two exhibition matches against professional gamers, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public appearance came later that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those video games. [165] |
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<br>OpenAI 5's systems in Dota 2's bot gamer shows the difficulties of [AI](http://www.xn--v42bq2sqta01ewty.com) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has actually shown using [deep support](https://forum.alwehdaclub.sa) learning (DRL) agents to attain superhuman proficiency in Dota 2 [matches](https://git.mae.wtf). [166] |
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<br>Dactyl<br> |
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<br>Developed in 2018, [gratisafhalen.be](https://gratisafhalen.be/author/sherrierome/) Dactyl uses machine learning to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It finds out totally in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation problem by using domain randomization, a simulation approach which exposes the learner to a [variety](https://git.qoto.org) of experiences instead of attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking video cameras, also has RGB video cameras to allow the robot to manipulate an approximate item by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI demonstrated that Dactyl could solve a Rubik's Cube. The robot had the ability 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 of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of creating gradually more tough 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 announced a multi-purpose API which it said was "for accessing new [AI](http://www.grainfather.co.nz) designs developed by OpenAI" to let developers get in touch with it for "any English language [AI](http://cgi3.bekkoame.ne.jp) task". [170] [171] |
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<br>Text generation<br> |
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<br>The business has [popularized generative](https://crossborderdating.com) pretrained transformers (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 model was written by Alec Radford and his coworkers, and released in [preprint](https://jobdd.de) on OpenAI's website on June 11, 2018. [173] It showed how a generative model of language might obtain world understanding and process long-range dependencies 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 without [supervision transformer](https://git.camus.cat) language design and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just restricted demonstrative variations at first released to the public. The full variation of GPT-2 was not right away launched due to issue about possible abuse, consisting of applications for composing fake news. [174] Some professionals revealed uncertainty that GPT-2 presented a considerable risk.<br> |
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence [reacted](http://szfinest.com6060) with a tool to find "neural fake news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be difficult to filter". [176] In November 2019, OpenAI released the total variation of the GPT-2 language model. [177] Several sites host interactive presentations of different circumstances of GPT-2 and other transformer models. [178] [179] [180] |
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<br>GPT-2's authors argue unsupervised language models to be general-purpose learners, illustrated by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot jobs (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 a little 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters by encoding both private characters and multiple-character tokens. [181] |
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<br>GPT-3<br> |
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<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language design and the [follower](https://spotlessmusic.com) to GPT-2. [182] [183] [184] OpenAI specified that the full variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as couple of as 125 million criteria were likewise trained). [186] |
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<br>OpenAI stated that GPT-3 succeeded at certain "meta-learning" jobs and could generalize the function of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning in between [English](https://dreamtube.congero.club) and Romanian, and between [English](http://seelin.in) 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 designs could be approaching or encountering the [basic ability](https://jobs.web4y.online) constraints of [predictive language](http://fcgit.scitech.co.kr) models. [187] Pre-training GPT-3 required a number of thousand [yewiki.org](https://www.yewiki.org/User:WilfredoEldersha) 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 right away released to the public for [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:LeonardoAckman1) concerns of possible abuse, although OpenAI prepared to enable 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. [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 actually additionally been [trained](https://freelancejobsbd.com) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://idemnaposao.rs) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the design can produce working code in over a lots programming languages, most effectively in Python. [192] |
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<br>Several problems with glitches, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:FelishaJoy30) design flaws and security vulnerabilities were [mentioned](https://www.nc-healthcare.co.uk). [195] [196] |
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<br>GitHub Copilot has actually been accused of giving off copyrighted code, without any author attribution or license. [197] |
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<br>OpenAI revealed that they would terminate assistance for [Codex API](https://www.askmeclassifieds.com) 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 upgraded 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 read, evaluate or produce approximately 25,000 words of text, and compose code in all significant programs languages. [200] |
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<br>Observers reported that the version 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 problems with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has decreased to reveal numerous technical details and data about GPT-4, such as the precise size of the design. [203] |
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<br>GPT-4o<br> |
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<br>On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained modern outcomes in voice, multilingual, and vision standards, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, [OpenAI released](http://gogs.black-art.cn) GPT-4o mini, a smaller sized version 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 helpful for enterprises, startups and designers looking for [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1074946) to automate services with [AI](https://meta.mactan.com.br) 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 models, which have actually been designed to take more time to think of their reactions, causing greater precision. These designs are especially reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was replaced by o1. [211] |
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<br>o3<br> |
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<br>On December 20, 2024, OpenAI unveiled o3, the follower of the o1 thinking model. OpenAI likewise unveiled o3-mini, a lighter and quicker version of OpenAI o3. Since December 21, 2024, 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 opportunity to obtain early access to these designs. [214] The model is called o3 rather than o2 to avoid confusion with telecommunications companies O2. [215] |
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<br>Deep research study<br> |
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<br>Deep research is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 model to carry out substantial web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools enabled, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120] |
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<br>Image classification<br> |
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<br>CLIP<br> |
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<br>[Revealed](https://git.thunraz.se) 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 significantly be utilized for image classification. [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 images from textual descriptions. [218] DALL-E uses a 12[-billion-parameter](https://wheeoo.com) version of GPT-3 to interpret natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and produce corresponding images. It can produce images of [practical objects](http://47.121.132.113000) ("a stained-glass window with an image of a blue strawberry") in addition to things that do not exist in truth ("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 announced DALL-E 2, an updated version of the design with more reasonable outcomes. [219] In December 2022, [ratemywifey.com](https://ratemywifey.com/author/hugocruse67/) OpenAI released on GitHub software for Point-E, a brand-new simple system for converting a [text description](https://www.bridgewaystaffing.com) 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 effective design better able to produce images from intricate descriptions without manual [prompt engineering](https://4kwavemedia.com) and render complex details like hands and text. [221] It was launched 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 design that can create videos based upon short detailed prompts [223] along with extend existing videos forwards or backwards in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The maximal 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 "endless imaginative 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 as well as [copyrighted](https://git.bugi.si) videos certified for that purpose, but did not expose 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 public on February 15, 2024, specifying that it could produce videos up to one minute long. It also shared a technical report highlighting the techniques used to train the model, and the design's capabilities. [225] It acknowledged a few of its imperfections, including struggles replicating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but kept in mind that they should have been cherry-picked and may not [represent Sora's](https://www.bjs-personal.hu) 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 revealed significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to produce reasonable video from text descriptions, mentioning its prospective to change storytelling and material creation. He said that his excitement about [Sora's possibilities](https://jobs.theelitejob.com) was so strong that he had actually decided to stop briefly plans for broadening his Atlanta-based motion [picture](https://frce.de) 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 model that can carry out multilingual speech recognition as well as 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, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:VeronaIronside) MuseNet is a deep neural net trained to [anticipate subsequent](https://gitlab.damage.run) musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a tune created by MuseNet tends to start fairly however then fall into turmoil the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized as early as 2020 for the [web mental](https://gitlab.informicus.ru) 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 category, artist, and a bit of lyrics and outputs song samples. OpenAI stated the tunes "reveal regional musical coherence [and] follow traditional chord patterns" however acknowledged that the songs do not have "familiar larger musical structures such as choruses that repeat" which "there is a considerable gap" in between Jukebox and human-generated music. The [Verge stated](https://www.cdlcruzdasalmas.com.br) "It's technically excellent, even if the outcomes seem like mushy variations of tunes that may feel familiar", while Business Insider mentioned "remarkably, a few of the resulting songs are memorable and sound legitimate". [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 released](http://47.120.16.1378889) the Debate Game, which teaches devices to dispute toy issues in front of a human judge. The purpose is to research whether such an approach may help in auditing [AI](https://git.electrosoft.hr) choices and in developing explainable [AI](http://43.143.46.76:3000). [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 frequently studied in interpretability. [240] Microscope was produced to examine the features that form inside these neural networks easily. The designs included are AlexNet, VGG-19, various variations of Inception, and different versions of CLIP Resnet. [241] |
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<br>ChatGPT<br> |
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<br>Launched in November 2022, ChatGPT is an artificial intelligence tool constructed on top of GPT-3 that provides a conversational user interface that enables users to ask concerns in natural language. The system then reacts with an answer within seconds.<br> |
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