Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library created to assist in the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://moztube.com) research, making published research more quickly reproducible [24] [144] while [providing](https://gt.clarifylife.net) users with an easy user interface for interacting with these environments. In 2022, brand-new developments of Gym have actually been transferred 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 learning (RL) research study on computer game [147] using RL algorithms and research study generalization. Prior RL research study focused mainly on [enhancing agents](http://www.vmeste-so-vsemi.ru) to solve single jobs. Gym Retro gives the capability to generalize between video games with similar concepts but various 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 robotic representatives initially do not have knowledge of how to even walk, however are provided the [objectives](http://59.56.92.3413000) of discovering to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing process, the agents learn how to adjust to [altering conditions](https://www.istorya.net). When a representative is then removed from this virtual environment and positioned in a brand-new virtual environment with high winds, the [representative braces](https://gt.clarifylife.net) to remain upright, suggesting it had found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between agents could create an "arms race" that could increase an agent's capability to operate 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 team of 5 OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that discover to play against human players at a high skill level completely through trial-and-error algorithms. Before becoming a group of 5, the very first public presentation occurred at The International 2017, the annual premiere champion competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live one-on-one 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, and that the knowing software was a step in the [direction](https://kewesocial.site) of creating software application that can handle complex jobs like a cosmetic surgeon. [152] [153] The system utilizes a kind of reinforcement knowing, as the bots find out gradually by playing against themselves numerous times a day for months, and 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 broadened to play together as a full team of 5, and they were able to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert players, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champions of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public appearance came later on that month, where they played in 42,729 total video games in a [four-day](http://116.205.229.1963000) open online competition, 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 obstacles of [AI](http://gitlab.fuxicarbon.com) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has shown making use of deep support knowing (DRL) representatives to [attain superhuman](https://geniusactionblueprint.com) skills in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl uses device finding out to train a Shadow Hand, a human-like robot hand, to manipulate physical objects. [167] It discovers completely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation issue by utilizing domain randomization, a [simulation technique](http://13.209.39.13932421) which exposes the student to a variety of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having [motion tracking](http://109.195.52.923000) video cameras, likewise has RGB video cameras to enable the robot to [manipulate](https://gitea.daysofourlives.cn11443) an arbitrary things 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 might fix a Rubik's Cube. The robotic had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce [intricate physics](https://scode.unisza.edu.my) that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of producing progressively harder environments. ADR differs from manual domain randomization by not needing a human to define 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 brand-new [AI](https://www.jobplanner.eu) designs developed by OpenAI" to let designers call on it for "any English language [AI](http://106.15.235.242) job". [170] [171]
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<br>Text generation<br>
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<br>The company has actually promoted generative pretrained transformers (GPT). [172]
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<br>OpenAI's initial 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 colleagues, and [released](http://47.102.102.152) in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative design of language might obtain world understanding and process long-range dependences 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 successor to OpenAI's original [GPT design](https://codeh.genyon.cn) ("GPT-1"). GPT-2 was revealed in February 2019, [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:DessieLundstrom) with just minimal demonstrative variations at first launched to the public. The full version of GPT-2 was not right away launched due to concern about prospective misuse, consisting of applications for composing fake news. [174] Some experts expressed uncertainty that GPT-2 presented a substantial threat.<br>
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to detect "neural fake news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI released the total version of the GPT-2 language design. [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 without [supervision language](https://uniondaocoop.com) models to be general-purpose students, shown by GPT-2 attaining state-of-the-art accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not additional 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 a minimum of 3 upvotes. It prevents certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both specific 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 a without supervision transformer [language](http://47.113.115.2393000) model and the successor to GPT-2. [182] [183] [184] OpenAI stated 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 complete version of GPT-2 (although GPT-3 [designs](https://barokafunerals.co.za) with as few as 125 million [parameters](http://1024kt.com3000) were also trained). [186]
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<br>OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" jobs and could generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning between English and Romanian, and in between English and German. [184]
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<br>GPT-3 dramatically improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or encountering the basic 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 complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly launched to the public for concerns of possible abuse, although OpenAI prepared to enable gain access to through a paid cloud API after a two-month complimentary personal beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed 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 in addition been [trained](http://8.217.113.413000) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.guidancetaxdebt.com) 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 produce working code in over a lots programming languages, most efficiently in Python. [192]
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<br>Several problems with glitches, style defects and security [vulnerabilities](http://git.zthymaoyi.com) were cited. [195] [196]
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<br>GitHub Copilot has been implicated of producing copyrighted code, without any author attribution or license. [197]
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<br>OpenAI revealed that they would discontinue 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 revealed that the upgraded innovation passed a simulated law school bar exam with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, analyze or produce approximately 25,000 words of text, and compose 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 [caution](http://test-www.writebug.com3000) that GPT-4 retained a few of the problems with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to expose different technical details and stats about GPT-4, such as the accurate 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 generate text, images and audio. [204] GPT-4o attained advanced 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 launched GPT-4o mini, a smaller variation 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 [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:CatalinaHoffnung) $15 respectively for GPT-4o. OpenAI anticipates it to be particularly useful for enterprises, startups and developers seeking to automate services with [AI](https://municipalitybank.com) agents. [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 responses, [causing](http://mao2000.com3000) greater accuracy. These designs are particularly reliable in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was changed by o1. [211]
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<br>o3<br>
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<br>On December 20, 2024, OpenAI revealed o3, the follower of the o1 thinking model. OpenAI also unveiled o3-mini, a lighter and quicker version of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the opportunity to obtain early access to these models. [214] The model is called o3 rather than o2 to avoid confusion with telecommunications services supplier O2. [215]
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<br>Deep research<br>
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<br>Deep research is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to [perform comprehensive](https://comunidadebrasilbr.com) web surfing, data analysis, and synthesis, [delivering detailed](https://rhabits.io) reports within a timeframe of 5 to 30 minutes. [216] With browsing 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 in 2021, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:PaulineMcLaurin) CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the semantic similarity between text and images. It can especially 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](https://gitlab.lizhiyuedong.com) that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of a sad capybara") and create matching images. It can develop pictures of realistic items ("a stained-glass window with a picture of a blue strawberry") as well as [objects](https://talentocentroamerica.com) 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 updated version of the design with more practical outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new fundamental system for converting 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 much better able to [produce](http://47.108.161.783000) images from complicated descriptions without manual prompt engineering and render intricate 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 create videos based upon brief detailed prompts [223] in addition to extend existing videos forwards or in reverse in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.<br>
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<br>Sora's development team named it after the Japanese word for "sky", to represent its "endless imaginative potential". [223] Sora's technology is an adjustment of the innovation behind the DALL · E 3 text-to-image model. [225] [OpenAI trained](http://140.125.21.658418) the system utilizing publicly-available videos along with copyrighted videos [accredited](http://8.140.244.22410880) for that function, however did not reveal the number or the exact sources of the videos. [223]
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<br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it could produce videos as much as one minute long. It also shared a technical report highlighting the techniques used to train the model, and the model's capabilities. [225] It acknowledged some of its drawbacks, including battles simulating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", but kept in mind that they must have been cherry-picked and may not represent Sora's typical output. [225]
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<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, notable entertainment-industry figures have shown considerable interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's ability to [produce realistic](http://gpra.jpn.org) video from text descriptions, mentioning its potential to change storytelling and content creation. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to pause plans for [broadening](https://givebackabroad.org) 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 varied audio and is likewise a multi-task design that can carry out multilingual speech acknowledgment 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](http://221.238.85.747000) to anticipate subsequent musical notes in MIDI music files. It can produce songs with 10 instruments in 15 styles. According to The Verge, a tune produced by MuseNet tends to start fairly however then fall under turmoil the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were utilized as early as 2020 for the web psychological thriller Ben Drowned to produce music for the titular character. [232] [233]
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<br>Jukebox<br>
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<br>Released in 2020, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:Maurice1620) Jukebox is an open-sourced algorithm to generate music with vocals. After [training](https://www.scikey.ai) on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs song samples. OpenAI stated the songs "reveal local musical coherence [and] follow standard chord patterns" but acknowledged that the tunes lack "familiar larger musical structures such as choruses that repeat" and that "there is a substantial space" in between Jukebox and human-generated music. The Verge stated "It's highly excellent, even if the outcomes seem like mushy variations of songs that might feel familiar", while Business Insider mentioned "surprisingly, some of the resulting songs are appealing and sound genuine". [234] [235] [236]
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<br>User interfaces<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI released the Debate Game, which [teaches devices](https://recruitment.nohproblem.com) to discuss toy problems in front of a human judge. The function is to research study whether such an approach may assist in auditing [AI](https://www.diltexbrands.com) decisions and [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:CherylCastiglia) in establishing explainable [AI](https://skillsvault.co.za). [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 8 neural network designs which are frequently studied in interpretability. [240] Microscope was produced to evaluate the features that form inside these neural networks quickly. The designs included are AlexNet, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:TracieCoats00) VGG-19, different versions of Inception, and various 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 permits users to ask questions in natural language. The system then reacts with a response within seconds.<br>
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