Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library [designed](http://mooel.co.kr) to assist in the development of reinforcement learning algorithms. It aimed to standardize how [environments](https://elit.press) are specified in [AI](https://gmstaffingsolutions.com) research, making released research study more easily reproducible [24] [144] while supplying users with a basic user interface for interacting with these environments. In 2022, new advancements of Gym have been 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](http://47.93.56.668080) for reinforcement knowing (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on optimizing representatives to resolve single jobs. Gym Retro offers the capability to generalize between games with comparable 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 robotic representatives initially lack understanding of how to even walk, however are provided the goals of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the agents learn how to adjust to altering conditions. When an agent is then removed from this virtual environment and put in a brand-new virtual environment with high winds, the representative braces to remain upright, suggesting it had learned how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between agents could develop an [intelligence](http://119.23.214.10930032) "arms race" that could increase a representative's ability to work 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 5 OpenAI-curated bots utilized in the [competitive five-on-five](https://www.scikey.ai) video game Dota 2, that find out to play against human players at a high ability level completely through trial-and-error algorithms. Before ending up being a group of 5, the very first public demonstration took place at The International 2017, the annual premiere championship competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live one-on-one match. [150] [151] After the match, [wiki.rolandradio.net](https://wiki.rolandradio.net/index.php?title=User:RudyRenteria459) 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 was an action in the instructions of producing software application that can manage complicated tasks like a cosmetic surgeon. [152] [153] The system uses a type of support knowing, as the bots learn in time by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156]
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<br>By June 2018, the capability of the bots broadened to play together as a full group of 5, and they had the ability to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against professional players, but ended up losing both video games. [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](https://axionrecruiting.com). [163] [164] The bots' last public look came later that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games. [165]
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<br>OpenAI 5's mechanisms in Dota 2's bot player reveals the obstacles of [AI](https://youtoosocialnetwork.com) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has actually shown making use of deep support [learning](https://www.jobassembly.com) (DRL) agents to attain superhuman skills in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>[Developed](http://211.117.60.153000) in 2018, Dactyl uses device discovering to train a Shadow Hand, a human-like robotic hand, to control physical objects. [167] It finds out completely in simulation using the very same RL algorithms and [training](https://dreamtube.congero.club) code as OpenAI Five. OpenAI tackled the object orientation issue by utilizing domain randomization, a simulation method which exposes the student to a variety of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having motion tracking cameras, likewise has RGB electronic cameras to permit the robotic to control an approximate 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 showed that Dactyl might fix a Rubik's Cube. The robotic was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of creating progressively harder environments. [ADR varies](https://gmstaffingsolutions.com) from manual domain randomization by not requiring a human to specify randomization varieties. [169]
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<br>API<br>
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<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://dev.gajim.org) models developed by OpenAI" to let designers contact it for "any English language [AI](http://124.71.134.146:3000) job". [170] [171]
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<br>Text generation<br>
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<br>The business has actually promoted generative pretrained transformers (GPT). [172]
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<br>OpenAI's original GPT model ("GPT-1")<br>
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<br>The original paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It showed how a generative design of language could obtain world knowledge and procedure long-range dependences by pre-training on a varied corpus with long stretches of contiguous 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 design and the [follower](https://wiki.atlantia.sca.org) to [OpenAI's original](https://www.egomiliinteriors.com.ng) GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative versions initially released to the public. The complete version of GPT-2 was not immediately released due to issue about potential misuse, including applications for composing phony news. [174] Some experts expressed uncertainty that GPT-2 presented a substantial risk.<br>
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<br>In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural fake news". [175] Other researchers, such as Jeremy Howard, alerted of "the innovation to absolutely 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 complete variation of the GPT-2 language model. [177] Several websites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180]
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<br>GPT-2's authors argue [unsupervised language](https://www.pakgovtnaukri.pk) models to be general-purpose learners, shown by GPT-2 attaining cutting edge precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further trained on any [task-specific input-output](https://xn--939a42kg7dvqi7uo.com) examples).<br>
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<br>The corpus it was trained on, called WebText, contains somewhat 40 gigabytes of text from [URLs shared](https://gitea.umrbotech.com) in Reddit submissions with a minimum of 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This allows 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](http://82.157.11.2243000) [a] Transformer 3 (GPT-3) is a without supervision transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full variation of GPT-3 contained 175 billion criteria, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 designs with as few as 125 million specifications were likewise trained). [186]
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<br>OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" tasks and might [generalize](http://cjma.kr) the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184]
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<br>GPT-3 drastically improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or encountering the essential capability constraints of predictive language models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly launched to the general public for concerns of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a [two-month totally](https://aladin.social) free personal beta that started in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was certified specifically 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 additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://labz.biz) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was [launched](http://1688dome.com) in private beta. [194] According to OpenAI, the model can develop working code in over a lots programming languages, most efficiently in Python. [192]
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<br>Several issues with problems, style defects and security vulnerabilities were pointed out. [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 revealed 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), [pipewiki.org](https://pipewiki.org/wiki/index.php/User:MurrayAuricht37) capable of accepting text or image inputs. [199] They announced that the upgraded technology 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 could likewise read, [evaluate](https://wino.org.pl) or create approximately 25,000 words of text, and write code in all significant programming languages. [200]
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<br>Observers reported that the model of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based model, with the [caution](http://images.gillion.com.cn) that GPT-4 retained some of the issues with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has [decreased](https://gitlab.t-salon.cc) to reveal different technical details and data about GPT-4, such as the precise size of the design. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained advanced results in voice, multilingual, and vision benchmarks, setting 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 released](https://in-box.co.za) GPT-4o mini, a smaller sized 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 particularly beneficial for enterprises, start-ups and developers looking for to [automate services](https://heartbeatdigital.cn) with [AI](https://tagreba.org) representatives. [208]
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<br>o1<br>
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<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have actually been created to take more time to think of their actions, resulting in greater precision. These designs are particularly efficient in science, coding, and thinking jobs, 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 model. OpenAI also revealed o3-mini, a lighter and quicker variation 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 design is called o3 instead of 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 developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out comprehensive web browsing, data analysis, and synthesis, delivering detailed [reports](https://www.xtrareal.tv) within a timeframe of 5 to thirty 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 category<br>
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<br>CLIP<br>
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<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to evaluate the semantic resemblance in between text and images. It can significantly 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 model](http://47.110.52.1323000) that develops images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to [interpret natural](http://harimuniform.co.kr) language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can produce pictures of realistic objects ("a stained-glass window with an image of a blue strawberry") in addition to things 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 upgraded version of the design with more sensible outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new simple system for converting a text description into a 3-dimensional model. [220]
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<br>DALL-E 3<br>
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<br>In September 2023, OpenAI revealed DALL-E 3, a more powerful design better able to produce images from intricate descriptions without manual timely engineering and render complex details like hands and text. [221] It was launched 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 model that can generate videos based upon brief [detailed prompts](https://git.caraus.tech) [223] in addition to extend existing videos forwards or backwards in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of created videos is unknown.<br>
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<br>Sora's advancement team named it after the Japanese word for "sky", to symbolize its "unlimited imaginative potential". [223] [Sora's innovation](https://gitlab.truckxi.com) is an adjustment of the [innovation](http://www.s-golflex.kr) behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos along with [copyrighted](http://124.223.100.383000) videos certified for [pipewiki.org](https://pipewiki.org/wiki/index.php/User:Darla0047511291) that function, however did not expose the number or the exact sources 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 could generate videos approximately 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 drawbacks, including struggles simulating complex physics. [226] Will Douglas Heaven of the MIT [Technology Review](https://ibs3457.com) called the presentation videos "impressive", but noted 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 scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have shown significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the [technology's capability](https://digital-field.cn50443) to produce reasonable video from text descriptions, citing its possible to reinvent storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to stop briefly strategies for broadening his Atlanta-based movie 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 model. [228] It is trained on a large dataset of varied audio and is likewise a multi-task design that can carry out [multilingual speech](https://rca.co.id) [acknowledgment](https://chat-oo.com) in addition to speech translation and language [recognition](http://thegrainfather.com). [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 produce tunes with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to begin fairly but then fall into mayhem the longer it plays. [230] [231] In popular culture, initial applications of this tool were used as early as 2020 for the internet psychological thriller Ben Drowned to create 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 generate music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs song samples. OpenAI specified the songs "reveal regional musical coherence [and] follow traditional chord patterns" however [acknowledged](https://www.joboont.in) that the songs do not have "familiar bigger musical structures such as choruses that duplicate" and that "there is a considerable gap" between Jukebox and human-generated music. The Verge stated "It's technically remarkable, even if the outcomes sound like mushy variations of songs that may feel familiar", while [Business Insider](https://git.marcopacs.com) stated "remarkably, a few of the resulting songs are appealing 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 released the Debate Game, which [teaches devices](http://47.107.92.41234) to dispute toy issues in front of a human judge. The function is to research whether such a technique might help in auditing [AI](https://one2train.net) choices and in [establishing explainable](http://www.xyais.com) [AI](https://cvmira.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 significant layer and neuron of eight neural network models which are typically studied in interpretability. [240] Microscope was developed to analyze the functions that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, different variations 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 offers a conversational interface that enables users to ask concerns in natural language. The system then responds with a response within seconds.<br>
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