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<br>Announced in 2016, Gym is an open-source Python library created to help with the advancement of support learning algorithms. It aimed to standardize how environments are specified in [AI](http://charge-gateway.com) research, making [released](https://git.starve.space) research study more easily reproducible [24] [144] while [supplying](https://www.blatech.co.uk) users with a simple user interface for interacting with these [environments](https://projectblueberryserver.com). 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 knowing (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research study focused mainly on enhancing agents to fix single jobs. Gym Retro gives the ability to generalize between video games with similar ideas but various looks.<br> |
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<br>RoboSumo<br> |
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<br>[Released](http://47.93.16.2223000) in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially do not have knowledge of how to even stroll, but are offered the objectives of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the representatives learn how to adjust to altering conditions. When a representative is then gotten rid of from this [virtual environment](https://www.imf1fan.com) and positioned in a brand-new virtual [environment](http://isarch.co.kr) with high winds, the agent braces to remain upright, recommending it had actually 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 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 five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:JulianeDaddario) that learn to play against human gamers at a high ability level completely through experimental algorithms. Before ending up being a group of 5, the very first public demonstration took place at The International 2017, the yearly premiere champion tournament for the game, where Dendi, an [expert Ukrainian](https://online-learning-initiative.org) player, lost against a bot in a live individually matchup. [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 direction of creating software application that can handle complex jobs like a cosmetic surgeon. [152] [153] The system utilizes a type of support knowing, as the bots learn in 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 goals. [154] [155] [156] |
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<br>By June 2018, the ability of the bots expanded to play together as a complete group of 5, and they were able to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The [International](https://smaphofilm.com) 2018, OpenAI Five played in two exhibition matches against expert gamers, but wound up losing both 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' last [public appearance](http://stackhub.co.kr) came later on 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 mechanisms in Dota 2's bot gamer reveals the difficulties of [AI](https://www.paradigmrecruitment.ca) systems in [multiplayer online](https://wiki.rrtn.org) fight arena (MOBA) games and how OpenAI Five has demonstrated the use of deep support learning (DRL) agents to attain superhuman competence in Dota 2 matches. [166] |
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<br>Dactyl<br> |
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<br>Developed in 2018, Dactyl uses [device discovering](https://code.52abp.com) to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It discovers totally in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI tackled the object orientation problem by utilizing domain randomization, a simulation method which exposes the learner to a [variety](https://somkenjobs.com) of [experiences](https://www.ajirazetu.tz) rather than trying to fit to truth. The set-up for Dactyl, aside from having movement tracking cameras, also has RGB cameras to allow the robot to manipulate an [approximate](http://223.68.171.1508004) things by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI demonstrated that Dactyl could [resolve](https://www.tvcommercialad.com) a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube present complicated physics that is harder to design. OpenAI did this by improving the toughness of Dactyl to [perturbations](http://moyora.today) by utilizing Automatic Domain Randomization (ADR), a simulation approach of generating gradually harder 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 announced a multi-purpose API which it said was "for accessing new [AI](https://git.rt-academy.ru) designs established by OpenAI" to let developers contact it for "any English language [AI](http://sujongsa.net) job". [170] [171] |
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<br>Text generation<br> |
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<br>The company has promoted generative pretrained transformers (GPT). [172] |
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<br>OpenAI's original GPT model ("GPT-1")<br> |
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<br>The initial paper on of a transformer-based language design was composed by Alec Radford and his associates, and released in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative design of language might obtain world understanding and procedure long-range dependencies by pre-training on a diverse 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 an unsupervised transformer language model and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative variations at first released to the general public. The complete variation of GPT-2 was not instantly launched due to concern about prospective misuse, including applications for writing fake news. [174] Some experts revealed uncertainty that GPT-2 presented a considerable risk.<br> |
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<br>In action to GPT-2, the Allen Institute for Artificial Intelligence [responded](http://git.medtap.cn) with a tool to detect "neural phony news". [175] Other researchers, such as Jeremy Howard, warned of "the technology to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the total version of the GPT-2 language model. [177] Several sites host interactive presentations of various instances of GPT-2 and other transformer models. [178] [179] [180] |
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<br>GPT-2's authors argue not being watched language models to be general-purpose learners, highlighted by GPT-2 attaining cutting edge 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](http://120.36.2.2179095) on, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This allows 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 in May 2020, Generative Pre-trained [a] [Transformer](https://cariere.depozitulmax.ro) 3 (GPT-3) is a not being watched transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI stated that the complete 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 designs with as few as 125 million criteria were likewise trained). [186] |
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<br>OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper offered 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 significantly improved benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or experiencing the essential capability constraints 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 full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 [trained design](https://quickdatescript.com) 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 free personal beta that started in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was certified exclusively 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 furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.yqfqzmy.monster) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the design can develop working code in over a dozen programs languages, the majority of successfully in Python. [192] |
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<br>Several concerns with problems, style flaws and security vulnerabilities were mentioned. [195] [196] |
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<br>GitHub Copilot has been implicated of giving off copyrighted code, without any author attribution or license. [197] |
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<br>OpenAI announced that they would stop support for [Codex API](https://www.egomiliinteriors.com.ng) on March 23, 2023. [198] |
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<br>GPT-4<br> |
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<br>On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or [disgaeawiki.info](https://disgaeawiki.info/index.php/User:TYKEarl029660062) image inputs. [199] They revealed that the updated innovation passed a simulated law school bar exam with a rating around the top 10% of [test takers](https://git.googoltech.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, analyze or generate as much as 25,000 words of text, and compose code in all major 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 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 decreased to reveal different technical details and stats about GPT-4, such as the exact size of the model. [203] |
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<br>GPT-4o<br> |
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<br>On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and produce text, [wiki.lafabriquedelalogistique.fr](https://wiki.lafabriquedelalogistique.fr/Discussion_utilisateur:BuddyDeshotel23) images and audio. [204] GPT-4o attained state-of-the-art lead to 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) standard compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller variation of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT user interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially useful for enterprises, start-ups and designers seeking to automate services with [AI](http://slfood.co.kr) representatives. [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 models, which have actually been created to take more time to consider their reactions, leading to greater precision. These models are especially reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [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 revealed o3, the follower of the o1 reasoning model. OpenAI likewise unveiled 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 checking 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 providers O2. [215] |
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<br>Deep research study<br> |
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<br>Deep research is an agent established by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to carry out extensive web surfing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [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 resemblance in between text and images. It can significantly be used for image [classification](https://gitlab.kicon.fri.uniza.sk). [217] |
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<br>Text-to-image<br> |
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<br>DALL-E<br> |
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<br>[Revealed](https://fototik.com) in 2021, DALL-E is a Transformer model that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to [interpret natural](https://wutdawut.com) [language inputs](https://121gamers.com) (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and generate matching images. It can produce pictures of practical items ("a stained-glass window with an image of a blue strawberry") along with [objects](http://jsuntec.cn3000) that do not exist in reality ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.<br> |
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<br>DALL-E 2<br> |
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<br>In April 2022, OpenAI revealed DALL-E 2, an upgraded version of the design with more reasonable outcomes. [219] In December 2022, OpenAI released on GitHub software [application](https://menfucks.com) for Point-E, a new simple system for transforming a text description into a 3[-dimensional design](https://www.yohaig.ng). [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 generate images from complicated descriptions without manual prompt engineering and render complicated details like hands and text. [221] It was released to the general public as a ChatGPT Plus function in October. [222] |
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<br>Text-to-video<br> |
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<br>Sora<br> |
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<br>Sora is a text-to-video design that can produce videos based on short detailed prompts [223] along with extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The optimum length of created videos is [unidentified](https://www.videomixplay.com).<br> |
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<br>Sora's advancement group named it after the Japanese word for "sky", to represent its "unlimited innovative potential". [223] Sora's innovation is an adjustment of the innovation behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using [publicly-available](https://kition.mhl.tuc.gr) videos along with copyrighted videos certified for that purpose, however did not reveal the number or the [precise sources](http://gitlab.rainh.top) 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, stating that it could create videos up to one minute long. It also shared a technical report highlighting the techniques utilized to train the design, and the model's abilities. [225] It acknowledged a few of its shortcomings, consisting of struggles replicating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", however kept in mind that they need to have been cherry-picked and may not represent Sora's normal output. [225] |
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<br>Despite uncertainty from some academic leaders following [Sora's public](https://gogs.koljastrohm-games.com) demo, significant entertainment-industry figures have actually revealed significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry [expressed](http://www.book-os.com3000) his awe at the innovation's ability to [produce reasonable](https://allcollars.com) video from text descriptions, mentioning its possible to revolutionize storytelling and material development. He said that his excitement about Sora's possibilities was so strong that he had decided to stop briefly strategies for broadening 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 design. [228] It is trained on a large dataset of diverse audio and is likewise a multi-task design that can perform multilingual speech recognition 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 net trained to predict subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 styles. According to The Verge, a song created 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 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 create music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs tune [samples](https://remoterecruit.com.au). OpenAI specified the songs "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that duplicate" and that "there is a substantial gap" between Jukebox and human-generated music. The Verge stated "It's highly remarkable, even if the outcomes sound like mushy versions of songs that might feel familiar", while Business Insider mentioned "surprisingly, some of the resulting songs are catchy 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 dispute toy issues in front of a human judge. The function is to research study whether such a technique may assist in auditing [AI](https://git.ddswd.de) decisions and in developing explainable [AI](https://www.pinnaclefiber.com.pk). [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 significant layer and nerve cell of eight neural [network models](https://jobs.360career.org) which are often studied in interpretability. [240] Microscope was produced to evaluate the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, various [variations](https://gitea.eggtech.net) of Inception, and various [variations](https://probando.tutvfree.com) 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 constructed on top of GPT-3 that provides a conversational user interface that permits users to ask questions in natural language. The system then reacts with a response within seconds.<br> |
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