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<br>Announced in 2016, Gym is an open-source Python library designed to facilitate the advancement of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://remnantstreet.com) research, making published research more quickly reproducible [24] [144] while providing users with a simple interface for interacting with these environments. In 2022, 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 study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on optimizing representatives to resolve single tasks. Gym Retro offers the ability to generalize in between video games with comparable concepts however different appearances.<br> |
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<br>RoboSumo<br> |
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<br>Released in 2017, RoboSumo is a [virtual](https://www.huntsrecruitment.com) world where humanoid metalearning robotic representatives at first do not have understanding of how to even walk, however are offered the objectives of discovering to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the [representatives](https://play.hewah.com) find out how to adjust to changing conditions. When a representative is then gotten rid of from this virtual environment and placed in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could create an intelligence "arms race" that could increase an agent's ability to function 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 5 [OpenAI-curated bots](https://abilliontestimoniesandmore.org) utilized in the competitive five-on-five computer game Dota 2, that find out to play against human players at a high skill level completely through trial-and-error algorithms. Before becoming a team of 5, the very first public demonstration happened at The International 2017, the annual best championship competition for the video game, where Dendi, an expert 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 learned by playing against itself for two weeks of real time, which the learning software was an action in the direction of creating software that can handle complex jobs like a cosmetic surgeon. [152] [153] The system utilizes a form of reinforcement knowing, as the bots find out gradually by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating 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 team of 5, and they were able to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against expert players, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public look came later on that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those games. [165] |
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<br>OpenAI 5['s mechanisms](http://football.aobtravel.se) in Dota 2's bot player reveals the challenges of [AI](https://git.yuhong.com.cn) systems in multiplayer online battle arena (MOBA) [video games](https://hotjobsng.com) and [genbecle.com](https://www.genbecle.com/index.php?title=Utilisateur:MyronNowell73) how OpenAI Five has demonstrated the usage of [deep reinforcement](http://git.vimer.top3000) 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 utilizes device learning to train a Shadow Hand, a human-like robotic hand, to control physical objects. [167] It discovers totally in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI took on the things orientation problem by utilizing domain randomization, a simulation method which exposes the student to a range of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having motion tracking electronic cameras, likewise has RGB cameras to enable the robotic to manipulate an arbitrary things by seeing it. In 2018, OpenAI revealed that the system had the ability to control a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI showed that Dactyl might solve a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to model. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of producing progressively harder environments. ADR differs from manual [domain randomization](http://xn--ok0b74gbuofpaf7p.com) 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 brand-new [AI](https://gitea.mrc-europe.com) models developed by OpenAI" to let developers call on it for "any English language [AI](https://git.xxb.lttc.cn) job". [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](https://se.mathematik.uni-marburg.de) GPT design ("GPT-1")<br> |
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<br>The original paper on generative pre-training of a transformer-based language model was composed by Alec Radford and [forum.pinoo.com.tr](http://forum.pinoo.com.tr/profile.php?id=1322189) his coworkers, and published in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world [knowledge](https://source.brutex.net) and process long-range dependences 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 not being watched transformer language model and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative variations initially launched to the general public. The full variation of GPT-2 was not right away launched due to issue about potential misuse, including applications for writing [phony news](https://work.melcogames.com). [174] Some [experts expressed](https://git.yuhong.com.cn) uncertainty that GPT-2 posed 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 fake news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the complete version of the GPT-2 language model. [177] Several websites host interactive presentations of various circumstances of GPT-2 and other transformer designs. [178] [179] [180] |
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<br>GPT-2's authors argue not being watched language models to be general-purpose students, highlighted by GPT-2 attaining advanced accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further trained on any task-specific input-output examples).<br> |
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<br>The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain issues encoding vocabulary with word tokens by using 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 model and [gratisafhalen.be](https://gratisafhalen.be/author/olivershoem/) the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full version of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were likewise trained). [186] |
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<br>OpenAI mentioned 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 gave examples of translation and cross-linguistic transfer knowing between English and Romanian, and in between English and German. [184] |
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<br>GPT-3 drastically enhanced outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models could be [approaching](http://114.132.245.2038001) or coming across the fundamental ability constraints of predictive language models. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not right away released to the public for concerns of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month totally free personal beta that began in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was [certified](https://granthers.com) specifically to [Microsoft](http://git.jaxc.cn). [190] [191] |
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<br>Codex<br> |
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<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://git.magic-beans.cn:3000) [powering](https://www.bakicicepte.com) the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was [launched](http://gitlab.qu-in.com) in personal beta. [194] According to OpenAI, the model can produce working code in over a lots shows languages, a lot of successfully in Python. [192] |
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<br>Several concerns with problems, design flaws and security vulnerabilities were cited. [195] [196] |
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<br>GitHub Copilot has actually been accused of emitting copyrighted code, with no author attribution or [garagesale.es](https://www.garagesale.es/author/eloisepreec/) license. [197] |
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<br>OpenAI revealed that they would terminate support for Codex API on March 23, 2023. [198] |
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<br>GPT-4<br> |
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<br>On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in [accepting text](http://110.42.231.1713000) or image inputs. [199] They revealed that the updated technology passed a simulated law school bar examination with a score around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could likewise check out, analyze or produce up to 25,000 words of text, and write code in all significant programming languages. [200] |
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<br>Observers reported that the iteration 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 revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has actually declined to expose different technical details and statistics about GPT-4, such as the exact 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 generate text, images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision benchmarks, setting new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the [Massive Multitask](https://jobsportal.harleysltd.com) Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized version of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT interface. Its [API costs](https://thedatingpage.com) $0.15 per million input tokens and $0.60 per million output tokens, [compared](https://54.165.237.249) to $5 and $15 respectively for GPT-4o. OpenAI expects it to be especially useful for enterprises, startups and designers seeking to automate services with [AI](http://mtmnetwork.co.kr) 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 developed to take more time to think about their reactions, leading to higher accuracy. These designs are especially effective in science, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11860868) coding, and thinking jobs, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1[-preview](https://trabajosmexico.online) 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 design. OpenAI likewise revealed o3-mini, [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:WCTSteve75017) a lighter and faster variation of OpenAI o3. As of December 21, 2024, this model is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the chance to obtain early access to these [designs](https://openedu.com). [214] The design is called o3 rather than o2 to prevent confusion with telecommunications [providers](https://asicwiki.org) O2. [215] |
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<br>Deep research<br> |
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<br>Deep research study is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to carry out comprehensive web surfing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools allowed, it reached an [accuracy](https://bakery.muf-fin.tech) of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [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 similarity between text and images. It can notably be used 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 creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to analyze natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and create matching images. It can create images of realistic objects ("a stained-glass window with a picture 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 variation of the model with more practical results. [219] In December 2022, OpenAI published on GitHub software application 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 effective design better able to generate images from complicated descriptions without manual timely engineering and render intricate details like hands and text. [221] It was launched to the general public as a [ChatGPT](https://palsyworld.com) Plus feature in October. [222] |
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<br>Text-to-video<br> |
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<br>Sora<br> |
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<br>Sora is a text-to-video model that can produce videos based upon short detailed triggers [223] in addition to extend existing videos forwards or backwards in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of produced videos is unidentified.<br> |
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<br>Sora's development group called it after the Japanese word for "sky", to represent its "endless imaginative potential". [223] Sora's innovation 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 accredited for that function, however did not reveal the number or the specific 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, [mentioning](https://candidates.giftabled.org) that it might generate videos up to one minute long. It also shared a technical report highlighting the approaches used to train the model, and the design's capabilities. [225] It acknowledged some of its drawbacks, [consisting](http://git.jcode.net) of [battles simulating](https://sondezar.com) complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", 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, notable entertainment-industry figures have actually revealed significant interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to produce sensible video from text descriptions, mentioning its prospective to revolutionize storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had chosen to pause prepare for expanding 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 model. [228] It is trained on a big dataset of diverse audio and is also a multi-task model that can carry out multilingual speech [acknowledgment](https://oros-git.regione.puglia.it) in addition to 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 in 2019, MuseNet is a [deep neural](https://git.cocorolife.tw) net trained to forecast 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 but then fall into mayhem the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized 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 produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI mentioned the songs "reveal local musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes lack "familiar larger musical structures such as choruses that duplicate" and that "there is a considerable gap" between Jukebox and human-generated music. The Verge stated "It's technologically excellent, even if the results sound like mushy versions of tunes that might feel familiar", while Business Insider specified "surprisingly, 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 launched the Debate Game, which teaches devices to debate toy issues in front of a human judge. The purpose is to research whether such an approach may help in auditing [AI](http://135.181.29.174:3001) choices and in [establishing explainable](https://pakfindjob.com) [AI](https://amore.is). [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 substantial layer and neuron of 8 neural network designs which are frequently studied in interpretability. [240] Microscope was produced to analyze the features that form inside these neural networks quickly. The models 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 built on top of GPT-3 that provides 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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