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 learning algorithms. It aimed to standardize how environments are defined in [AI](http://8.137.12.29:3000) research study, making published research study more [easily reproducible](http://forum.ffmc59.fr) [24] [144] while offering users with a simple user interface for communicating 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 reinforcement learning (RL) research on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on optimizing representatives to fix single jobs. Gym Retro offers the capability to generalize between games with comparable principles however 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 agents initially do not have understanding of how to even walk, but are given the goals of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing process, the representatives discover how to adapt to changing conditions. When a representative is then eliminated from this virtual environment and placed in a brand-new virtual environment with high winds, the agent braces to remain upright, [recommending](https://almanyaisbulma.com.tr) it had actually discovered how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could develop an intelligence "arms race" that might [increase](https://spm.social) an agent's ability 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 group of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that discover to play against human players at a high [ability level](https://gitea.fcliu.net) completely through trial-and-error algorithms. Before becoming a team of 5, the very first public presentation happened at The International 2017, the yearly best championship tournament for the game, where Dendi, an expert Ukrainian player, lost against a bot in a [live one-on-one](http://47.104.6.70) matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had learned by playing against itself for [pipewiki.org](https://pipewiki.org/wiki/index.php/User:CyrilVanguilder) 2 weeks of actual time, and that the knowing software was an action in the direction of producing software application that can handle complicated jobs like a cosmetic surgeon. [152] [153] The system utilizes a kind of reinforcement learning, as the bots learn over time by playing against themselves times a day for months, and are rewarded for [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) actions such as [killing](http://110.41.19.14130000) an enemy and taking map objectives. [154] [155] [156]
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<br>By June 2018, the capability of the bots expanded to play together as a complete team of 5, and they were able to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against expert players, but wound up losing both [video games](https://animployment.com). [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public appearance came later that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those video games. [165]
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<br>OpenAI 5's mechanisms in Dota 2's bot gamer reveals the difficulties of [AI](http://www.thekaca.org) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has shown the usage of deep support knowing (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl utilizes maker learning to train a Shadow Hand, a human-like robotic hand, to control physical objects. [167] It finds out completely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation problem by utilizing domain randomization, a simulation technique which exposes the student to a range of experiences rather than trying to fit to truth. The set-up for Dactyl, aside from having motion tracking video cameras, likewise has RGB cameras to enable the robotic to manipulate an approximate object by seeing it. In 2018, OpenAI revealed that the system was able to manipulate 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 complicated physics that is harder to design. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of creating progressively harder [environments](http://git.irunthink.com). 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 revealed a multi-purpose API which it said was "for accessing brand-new [AI](http://140.143.208.127:3000) models established by OpenAI" to let [developers](https://gitea.ecommercetools.com.br) get in touch with it for "any English language [AI](https://gitlab.ineum.ru) job". [170] [171]
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<br>Text generation<br>
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<br>The company has popularized 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](https://lms.jolt.io) on generative pre-training of a transformer-based language design was written by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world knowledge and process 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](http://unired.zz.com.ve) 2 ("GPT-2") is a without supervision transformer language model and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only restricted demonstrative [variations](https://in-box.co.za) at first launched to the general public. The full version of GPT-2 was not right away launched due to concern about potential misuse, consisting of [applications](https://sportworkplace.com) for composing phony news. [174] Some experts revealed uncertainty that GPT-2 presented a substantial hazard.<br>
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<br>In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to identify "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned of "the innovation 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 released the total version of the GPT-2 language design. [177] Several websites host interactive demonstrations 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 designs to be general-purpose learners, illustrated by GPT-2 attaining state-of-the-art accuracy 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 somewhat 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 in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full variation of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as few 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 could [generalize](https://iinnsource.com) the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer knowing in between English and Romanian, and in between English and German. [184]
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<br>GPT-3 considerably improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or experiencing the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately released to the public for issues of possible abuse, although OpenAI planned to [enable gain](https://saathiyo.com) 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 certified solely 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 on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://wiki.sublab.net) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the design can develop working code in over a dozen programming languages, most successfully in Python. [192]
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<br>Several concerns with problems, style flaws and [security](http://wecomy.co.kr) vulnerabilities were pointed out. [195] [196]
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<br>GitHub Copilot has actually been implicated of producing copyrighted code, with no author attribution or license. [197]
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<br>OpenAI announced that they would discontinue assistance 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), capable of accepting text or image inputs. [199] They announced that the upgraded innovation passed a simulated law [school bar](https://jobz1.live) exam 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 also check out, examine or produce as much as 25,000 words of text, and write code in all significant programs languages. [200]
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<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained some of the issues with earlier modifications. [201] GPT-4 is also [efficient](https://ruofei.vip) in taking images as input on ChatGPT. [202] OpenAI has actually declined to reveal various technical details and data 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 released GPT-4o, which can process and generate text, [wavedream.wiki](https://wavedream.wiki/index.php/User:TammieRaposo6) images and audio. [204] GPT-4o attained advanced outcomes in voice, multilingual, and vision standards, setting brand-new records in audio speech [acknowledgment](https://demanza.com) and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207]
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<br>On July 18, 2024, OpenAI released GPT-4o mini, 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 beneficial for enterprises, start-ups and developers seeking to automate services with [AI](http://easyoverseasnp.com) agents. [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 been developed to take more time to consider their actions, causing greater precision. These designs are particularly reliable in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was replaced by o1. [211]
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<br>o3<br>
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<br>On December 20, 2024, OpenAI unveiled o3, the follower of the o1 reasoning design. OpenAI also revealed o3-mini, a [lighter](https://git.tissue.works) and much faster version 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 models. [214] The model is called o3 rather than o2 to avoid confusion with telecoms companies O2. [215]
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<br>Deep research<br>
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<br>Deep research is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out comprehensive web browsing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty 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](http://git.7doc.com.cn) Pre-training) is a model that is trained to evaluate the semantic similarity in between text and images. It can significantly be utilized for image category. [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 version of GPT-3 to translate natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and generate matching images. It can create pictures of [realistic objects](http://gitlab.signalbip.fr) ("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"). 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 revealed](https://www.sealgram.com) DALL-E 2, an [upgraded variation](https://seconddialog.com) of the model with more realistic results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new primary system for transforming a text description into a 3[-dimensional](http://test.wefanbot.com3000) design. [220]
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<br>DALL-E 3<br>
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<br>In September 2023, [OpenAI revealed](https://git.tea-assets.com) DALL-E 3, a more powerful design much better able to generate images from complex descriptions without manual prompt engineering and render complex details like hands and text. [221] It was launched to the general public as a ChatGPT 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 generate videos based upon short detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of generated videos is unknown.<br>
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<br>Sora's advancement team called it after the Japanese word for "sky", to symbolize its "endless innovative potential". [223] [Sora's innovation](http://git.lovestrong.top) is an adjustment of the innovation behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system [utilizing](https://www.dadam21.co.kr) publicly-available videos as well as copyrighted videos certified for that function, [wiki.whenparked.com](https://wiki.whenparked.com/User:Wade37577327) but did not reveal the number or the [exact sources](http://103.254.32.77) of the videos. [223]
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<br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, stating that it might generate videos as much as one minute long. It likewise shared a technical report highlighting the [methods utilized](http://183.221.101.893000) to train the design, and the design's capabilities. [225] It acknowledged some of its shortcomings, consisting of struggles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", however kept in mind that they should have been cherry-picked and may not represent Sora's common output. [225]
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<br>Despite uncertainty from some scholastic leaders following Sora's public demo, noteworthy entertainment-industry figures have revealed significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's capability to generate practical video from text descriptions, mentioning its prospective to change storytelling and material creation. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to stop briefly strategies for broadening 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](https://m1bar.com) 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 recognition in addition to speech translation and language [identification](http://coastalplainplants.org). [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 songs with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to begin fairly but then fall under mayhem the longer it plays. [230] [231] In pop culture, initial applications of this tool were used as early as 2020 for the web psychological thriller Ben Drowned to [produce music](http://www.vokipedia.de) for the [titular character](http://121.199.172.2383000). [232] [233]
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<br>Jukebox<br>
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<br>Released in 2020, Jukebox is an open-sourced algorithm to generate music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and [wiki.asexuality.org](https://wiki.asexuality.org/w/index.php?title=User_talk:BrandonSilvis23) a [snippet](http://git.rabbittec.com) of lyrics and outputs tune samples. OpenAI stated the tunes "reveal local musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes lack "familiar larger musical structures such as choruses that repeat" and that "there is a substantial space" between Jukebox and human-generated music. The Verge mentioned "It's highly excellent, even if the results seem like mushy variations of songs that may feel familiar", while Business Insider mentioned "surprisingly, a few of the resulting tunes 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 introduced the Debate Game, which teaches devices to discuss toy problems in front of a human judge. The function is to research whether such an approach may assist in auditing [AI](https://in-box.co.za) decisions and in establishing explainable [AI](https://2ubii.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 eight neural network designs which are frequently studied in interpretability. [240] [Microscope](https://gallery.wideworldvideo.com) was produced to analyze the features that form inside these [neural networks](https://yourecruitplace.com.au) quickly. The models consisted of are AlexNet, VGG-19, different versions of Inception, and different [versions](https://gitlab.ujaen.es) of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, ChatGPT is a synthetic intelligence tool constructed on top of GPT-3 that supplies a conversational user interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.<br>
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