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<br>Announced in 2016, Gym is an open-source Python library developed to assist in the advancement of support knowing algorithms. It aimed to standardize how environments are defined in [AI](https://kohentv.flixsterz.com) research study, making released research study more easily reproducible [24] [144] while offering users with an easy user interface for engaging with these environments. In 2022, new advancements of Gym have actually been 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 support knowing (RL) research study on computer game [147] using RL algorithms and research study generalization. Prior RL research study focused mainly on enhancing representatives to resolve single jobs. Gym Retro provides the ability to generalize in between games with similar principles however different looks.<br> |
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<br>RoboSumo<br> |
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<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot [agents initially](https://igita.ir) do not have understanding of how to even stroll, however are provided the objectives of learning to move and to push the opposing representative out of the ring. [148] Through this adversarial [knowing](http://101.42.248.1083000) procedure, the agents find out how to adjust to altering conditions. When a [representative](http://47.105.162.154) is then gotten rid of from this virtual environment and put in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had actually learned how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents might develop an intelligence "arms race" that could increase a representative'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 five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that learn to play against human players at a high skill level entirely through trial-and-error algorithms. Before becoming a group of 5, the first public presentation took place at The International 2017, the yearly best [championship competition](https://www.primerorecruitment.co.uk) for the video game, where Dendi, a professional Ukrainian gamer, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:JeffryArreguin6) lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually found out by playing against itself for two weeks of actual time, which the knowing software application was a step in the instructions of creating software application that can deal with complicated jobs like a surgeon. [152] [153] The system utilizes a kind of support knowing, [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:YvonneBlubaugh) as the bots discover with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an opponent and taking map objectives. [154] [155] [156] |
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<br>By June 2018, the ability of the bots broadened to play together as a complete group of 5, and they had the ability to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 [exhibition matches](https://aubameyangclub.com) against expert gamers, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world [champions](https://kittelartscollege.com) of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public look came later on that month, where they played in 42,729 overall video games in a four-day open online competition, winning 99.4% of those games. [165] |
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<br>OpenAI 5's mechanisms in Dota 2's bot player reveals the challenges of [AI](https://executiverecruitmentltd.co.uk) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated making use of deep reinforcement knowing (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 learning to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It learns entirely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation problem by using domain randomization, a simulation technique which exposes the learner to a variety of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking cams, also has RGB video cameras to allow the robotic to control an approximate item by seeing it. In 2018, OpenAI showed 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 could resolve a Rubik's Cube. The robot had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to [perturbations](https://huconnect.org) by using Automatic Domain Randomization (ADR), a simulation method of creating gradually more hard environments. ADR differs from manual domain randomization by not needing a human to specify randomization varieties. [169] |
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<br>API<br> |
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<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://i-medconsults.com) designs developed by OpenAI" to let developers call on it for "any English language [AI](https://apk.tw) task". [170] [171] |
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<br>Text generation<br> |
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<br>The business has actually promoted generative 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 composed by Alec Radford and his colleagues, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world knowledge 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 without supervision transformer [language](https://cheapshared.com) model and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative variations at first released to the general public. The complete variation of GPT-2 was not instantly launched due to issue about possible misuse, consisting of applications for composing phony news. [174] Some professionals revealed uncertainty that GPT-2 positioned a substantial risk.<br> |
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<br>In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to identify "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned of "the innovation to completely 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 launched the total version of the GPT-2 language design. [177] Several sites host interactive demonstrations 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 designs](http://8.136.197.2303000) to be general-purpose students, shown by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot tasks (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 slightly 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both individual characters and multiple-character tokens. [181] |
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<br>GPT-3<br> |
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<br>First [explained](https://git.starve.space) in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a without supervision transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full version of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 designs with as few as 125 million criteria were also trained). [186] |
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<br>OpenAI specified that GPT-3 prospered at certain "meta-learning" tasks 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](http://193.123.80.2023000) in between English and Romanian, and between English and German. [184] |
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<br>GPT-3 significantly improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of [language designs](https://gitea.egyweb.se) might be approaching or encountering the essential ability [constraints](https://job.duttainnovations.com) of predictive language designs. [187] Pre-training GPT-3 required 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 design was not instantly launched 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 free private beta that started in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was certified specifically to [Microsoft](https://social.updum.com). [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 furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://casajienilor.ro) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can produce working code in over a lots shows languages, many successfully in Python. [192] |
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<br>Several issues with problems, design flaws and security vulnerabilities were mentioned. [195] [196] |
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<br>[GitHub Copilot](http://www.colegio-sanandres.cl) has actually been accused of producing copyrighted code, without any author attribution or license. [197] |
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<br>OpenAI revealed that they would cease 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 or image inputs. [199] They announced that the updated innovation passed a simulated law school bar test 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 could likewise read, analyze or produce approximately 25,000 words of text, and compose code in all major programming languages. [200] |
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<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based model, [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:UnaProsser9137) with the caveat that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has [decreased](http://hjl.me) to expose different technical details and data 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 generate text, images and audio. [204] GPT-4o attained advanced results in voice, multilingual, and vision benchmarks, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI launched GPT-4o mini, [wiki.lafabriquedelalogistique.fr](https://wiki.lafabriquedelalogistique.fr/Utilisateur:LashayAlderson9) a smaller sized 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 especially useful for business, startups and designers looking for to automate services with [AI](https://www.p3r.app) 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 been created to take more time to think about their responses, causing higher precision. These models are particularly efficient in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1[-preview](https://fcschalke04fansclub.com) was replaced by o1. [211] |
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<br>o3<br> |
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<br>On December 20, 2024, OpenAI revealed o3, the successor of the o1 reasoning model. OpenAI likewise revealed o3-mini, a lighter and faster variation of OpenAI o3. Since 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, safety and security researchers had the chance to obtain early access to these models. [214] The design is called o3 rather than o2 to prevent confusion with telecommunications companies O2. [215] |
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<br>Deep research study<br> |
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<br>Deep research study is a representative developed by OpenAI, unveiled on February 2, 2025. It [leverages](http://124.222.181.1503000) the capabilities of OpenAI's o3 model to perform substantial web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) [benchmark](https://bio.rogstecnologia.com.br). [120] |
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<br>Image classification<br> |
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<br>CLIP<br> |
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<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the semantic similarity between text and images. It can significantly be utilized for [pipewiki.org](https://pipewiki.org/wiki/index.php/User:GeraldDonnithorn) 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](http://webheaydemo.co.uk). [218] DALL-E uses a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and [generate](http://wiki.pokemonspeedruns.com) corresponding images. It can create [pictures](http://120.79.94.1223000) of realistic items ("a stained-glass window with a picture of a blue strawberry") along with items 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 updated variation of the model with more sensible results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new basic system for converting 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 revealed DALL-E 3, a more effective model much better able to create images from intricate descriptions without manual timely engineering and render intricate details like hands and text. [221] It was [released](https://git.electrosoft.hr) 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 produce videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of produced videos is unidentified.<br> |
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<br>Sora's advancement team called it after the Japanese word for "sky", to represent its "endless creative capacity". [223] Sora's technology is an adaptation of the innovation behind the DALL · E 3 [text-to-image model](https://git.jzcscw.cn). [225] OpenAI trained the system using publicly-available videos along with copyrighted videos certified for that function, but did not expose the number or the precise sources of the videos. [223] |
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<br>OpenAI showed some [Sora-created high-definition](https://git.mhurliman.net) videos to the public on February 15, 2024, specifying that it might generate videos up to one minute long. It likewise shared a technical report highlighting the approaches used to train the design, and the design's capabilities. [225] It [acknowledged](https://www.e-vinil.ro) a few of its shortcomings, consisting of struggles imitating intricate 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](https://myclassictv.com) and might not represent Sora's common output. [225] |
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<br>Despite uncertainty from some scholastic leaders following Sora's public demo, significant entertainment-industry figures have revealed significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to create realistic video from text descriptions, citing its potential to change storytelling and content development. He said that his enjoyment about Sora's possibilities was so strong that he had decided to stop briefly plans 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 acknowledgment model. [228] It is trained on a big dataset of diverse audio and is also a [multi-task](https://git.manu.moe) design that can perform multilingual speech recognition along with 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 net trained to anticipate subsequent musical notes in MIDI music files. It can create tunes with 10 instruments in 15 styles. According to The Verge, a tune generated by MuseNet tends to begin fairly however then fall under chaos the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for the internet psychological thriller Ben Drowned to 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 genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI stated the songs "reveal regional musical coherence [and] follow standard chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" and that "there is a substantial space" in between Jukebox and human-generated music. The Verge mentioned "It's highly impressive, even if the outcomes sound like mushy versions of tunes that may feel familiar", while Business Insider stated "remarkably, a few of the resulting songs are memorable 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, [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:ShanelBergman33) OpenAI launched the Debate Game, which [teaches makers](http://www.shopmento.net) to debate toy problems in front of a human judge. The purpose is to research study whether such a method may help in auditing [AI](https://www.netrecruit.al) decisions and in establishing explainable [AI](https://neejobs.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 nerve cell of 8 neural [network designs](https://video.lamsonsaovang.com) which are typically studied in interpretability. [240] Microscope was developed to analyze the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, different versions of Inception, and [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:MichaelCrocker0) 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 expert system tool developed on top of GPT-3 that supplies a conversational user interface that allows users to ask concerns in natural language. The system then reacts with a response within seconds.<br> |
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