Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library designed to help with the advancement of support learning algorithms. It aimed to standardize how environments are specified in [AI](https://barbersconnection.com) research, making published research more easily reproducible [24] [144] while offering users with an easy interface for connecting with these environments. In 2022, brand-new advancements of Gym have actually been moved to the library Gymnasium. [145] [146]
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<br>Gym Retro<br>
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<br>Released in 2018, Gym Retro is a platform for reinforcement learning (RL) research study on computer game [147] utilizing RL algorithms and [study generalization](https://coding.activcount.info). Prior [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2684771) RL research study focused mainly on enhancing agents to fix single tasks. Gym Retro provides the ability to generalize between video games with similar principles but different appearances.<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 representatives at first do not have understanding of how to even walk, however are provided the goals of finding out to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the representatives discover how to adjust to changing conditions. When an agent is then [eliminated](https://asromafansclub.com) from this virtual environment and positioned in a brand-new virtual environment with high winds, the agent braces to remain upright, recommending it had actually discovered how to balance in a generalized way. [148] [149] OpenAI's Igor [Mordatch](http://47.120.57.2263000) argued that competitors between representatives could 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 group of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that find out to play against human gamers at a high ability level entirely through trial-and-error algorithms. Before becoming a team of 5, the very first public demonstration took place at The International 2017, the yearly best championship competition for the video game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for two weeks of real time, and that the learning software application was a step in the instructions of creating software that can deal with complicated tasks like a surgeon. [152] [153] The system utilizes a kind of reinforcement learning, as the bots find out gradually by playing against themselves [numerous](https://git.magesoft.tech) 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 capability of the bots broadened to play together as a complete team of 5, and they were able to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The [International](http://git.hnits360.com) 2018, OpenAI Five played in 2 exhibit matches against professional players, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world [champions](https://heatwave.app) of the [video game](http://120.77.205.309998) at the time, [it-viking.ch](http://it-viking.ch/index.php/User:ElmoVaude846) 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public appearance came later that month, where they played in 42,729 overall video games in a four-day 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 player reveals the difficulties of [AI](https://svn.youshengyun.com:3000) systems in multiplayer online fight arena (MOBA) [video games](http://git.365zuoye.com) and how OpenAI Five has actually shown making use of deep reinforcement learning (DRL) representatives 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 finding out to train a Shadow Hand, a human-like robot hand, to control physical items. [167] It discovers completely in [simulation](https://git.morenonet.com) using the same RL algorithms and [training](https://legatobooks.com) code as OpenAI Five. OpenAI dealt with the item orientation problem by utilizing domain randomization, a [simulation method](https://spillbean.in.net) which exposes the [student](http://lesstagiaires.com) to a range of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having motion tracking cameras, likewise has RGB cameras to permit the robot to manipulate an arbitrary item by seeing it. In 2018, OpenAI showed that the system had the ability to control a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI showed that Dactyl could resolve a Rubik's Cube. The robotic was able to resolve the puzzle 60% of the time. Objects like the [Rubik's Cube](https://satyoptimum.com) introduce complex physics that is harder to model. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of generating gradually harder environments. ADR varies from manual domain randomization by not requiring a human to define randomization ranges. [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.bakicicepte.com) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](https://projobfind.com) 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 original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his coworkers, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world understanding and procedure long-range dependencies 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 an unsupervised transformer language model and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative variations initially launched to the general public. The full version of GPT-2 was not immediately launched due to concern about potential misuse, consisting of [applications](http://media.nudigi.id) for [composing phony](https://www.mk-yun.cn) news. [174] Some specialists revealed uncertainty that GPT-2 posed a substantial hazard.<br>
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<br>In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to spot "neural phony news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to totally 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 variation of the GPT-2 language model. [177] Several sites host interactive presentations of various instances of GPT-2 and other [transformer models](https://www.bakicicepte.com). [178] [179] [180]
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<br>GPT-2's [authors argue](https://paksarkarijob.com) without supervision language designs to be general-purpose students, highlighted by GPT-2 attaining cutting edge precision and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not more 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 using 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](https://git.uzavr.ru) 3 (GPT-3) is a without supervision transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete version of GPT-3 contained 175 billion criteria, [184] two orders of [magnitude bigger](http://115.29.48.483000) than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as few as 125 million criteria were also trained). [186]
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<br>OpenAI stated that GPT-3 prospered at certain "meta-learning" jobs and could generalize the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning in between English and Romanian, and in between English and German. [184]
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<br>GPT-3 dramatically enhanced [benchmark](https://www.hammerloop.com) results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or encountering the basic capability constraints of predictive language designs. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately launched to the general public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month free [personal](http://tv.houseslands.com) beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was certified specifically to [Microsoft](https://code.webpro.ltd). [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](http://git.estoneinfo.com) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://wiki.contextgarden.net) 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 create working code in over a lots shows languages, many [efficiently](https://www.onlywam.tv) in Python. [192]
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<br>Several problems with problems, style flaws and security vulnerabilities were mentioned. [195] [196]
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<br>GitHub Copilot has been accused of emitting copyrighted code, with no author attribution or license. [197]
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<br>OpenAI revealed that they would cease 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 revealed the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the updated innovation passed a simulated law school bar examination with a score around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, analyze or create up to 25,000 words of text, and compose code in all major shows languages. [200]
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<br>Observers reported that the iteration of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the problems with earlier revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal numerous technical details and stats 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 released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision benchmarks, setting 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, a smaller variation of GPT-4o replacing 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 expects it to be especially beneficial for enterprises, startups and designers looking for to automate services with [AI](https://www.ajirazetu.tz) 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 designs, which have been developed to take more time to think of their actions, resulting in higher precision. These designs are particularly [effective](https://afacericrestine.ro) in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Staff member. [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 reasoning design. OpenAI also unveiled o3-mini, a lighter and faster version of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are evaluating 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 [companies](https://git.gilgoldman.com) O2. [215]
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<br>Deep research study<br>
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<br>Deep research study is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform comprehensive web browsing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching 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](https://kigalilife.co.rw) in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to evaluate the semantic resemblance between text and images. It can notably be utilized 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, [it-viking.ch](http://it-viking.ch/index.php/User:TaylahM410959) DALL-E is a Transformer design that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to interpret natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can produce pictures of sensible things ("a stained-glass window with an image of a blue strawberry") as well as things 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 announced DALL-E 2, an updated version of the design with more realistic results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a new rudimentary system for transforming 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 powerful design much better able to generate images from complicated descriptions without manual prompt engineering and render complicated details like hands and text. [221] It was launched to the public as a [ChatGPT](https://inspirationlift.com) Plus feature in October. [222]
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<br>Text-to-video<br>
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<br>Sora<br>
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<br>Sora is a text-to-video model that can generate videos based upon short detailed triggers [223] in addition to [extend existing](https://dubaijobzone.com) videos forwards or backwards in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of produced videos is unidentified.<br>
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<br>[Sora's advancement](http://cgi3.bekkoame.ne.jp) team named it after the Japanese word for "sky", to symbolize its "limitless creative potential". [223] Sora's technology is an adaptation of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos as well as licensed for that purpose, but did not reveal the number or the specific sources of the videos. [223]
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<br>OpenAI showed some [Sora-created high-definition](http://www.jobteck.co.in) videos to the public on February 15, 2024, mentioning that it might create videos up to one minute long. It also shared a technical report highlighting the techniques used to train the model, and the design's capabilities. [225] It acknowledged a few of its shortcomings, consisting of battles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) but noted that they need to have been cherry-picked and may not [represent Sora's](https://www.telewolves.com) common output. [225]
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<br>Despite uncertainty from some academic leaders following Sora's public demo, noteworthy entertainment-industry figures have actually revealed substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's capability to produce sensible video from text descriptions, citing its prospective to revolutionize storytelling and material creation. He said that his [excitement](https://www.complete-jobs.com) about [Sora's possibilities](https://git.parat.swiss) was so strong that he had actually chosen 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 in 2022, Whisper is a general-purpose speech [acknowledgment](http://gitlab.lvxingqiche.com) design. [228] It is trained on a big dataset of diverse audio and is also a multi-task design that can carry out multilingual speech [recognition](http://www.zjzhcn.com) 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 forecast subsequent musical notes in MIDI music files. It can generate 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 utilized as early as 2020 for [oeclub.org](https://oeclub.org/index.php/User:MauricioRdz) the internet mental 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, Jukebox is an open-sourced algorithm to produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI specified the songs "reveal local musical coherence [and] follow traditional chord patterns" but acknowledged that the songs lack "familiar bigger musical structures such as choruses that duplicate" and that "there is a substantial gap" in between Jukebox and human-generated music. The Verge specified "It's technologically excellent, even if the results seem like mushy variations of tunes that may feel familiar", while Business Insider stated "remarkably, a few of the resulting songs are memorable and sound legitimate". [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, [OpenAI introduced](https://www.hirecybers.com) the Debate Game, which teaches devices to discuss toy issues in front of a human judge. The function is to research study whether such an approach may assist in auditing [AI](https://cagit.cacode.net) decisions and in developing explainable [AI](https://workforceselection.eu). [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 neuron of eight neural network designs which are frequently studied in interpretability. [240] Microscope was developed to analyze the [functions](https://git.penwing.org) that form inside these neural networks easily. The designs consisted of are AlexNet, VGG-19, different versions of Inception, and different variations 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 built on top of GPT-3 that provides a conversational interface that allows users to ask questions in natural language. The system then reacts with a response within seconds.<br>
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