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](http://47.109.30.194:8888) research study, making published research study more easily reproducible [24] [144] while offering users with a simple interface for engaging with these environments. In 2022, new advancements of Gym have actually been transferred to the [library Gymnasium](https://git.didi.la). [145] [146]
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<br>Gym Retro<br>
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<br>Released in 2018, [Gym Retro](http://git.indep.gob.mx) is a platform for [reinforcement learning](https://scholarpool.com) (RL) research on computer game [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on optimizing agents to resolve single tasks. Gym Retro offers the capability to generalize in 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 representatives at first lack understanding of how to even stroll, however are [offered](https://git.cavemanon.xyz) the objectives of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial learning procedure, the representatives learn how to adapt to changing conditions. When a representative is then removed from this virtual environment and placed in a new virtual environment with high winds, the representative braces to remain upright, recommending it had actually discovered how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might develop an intelligence "arms race" that might increase an agent's capability 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 team of 5 OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that discover to play against human gamers at a high skill level entirely through experimental algorithms. Before becoming a team of 5, the first public presentation took place at The International 2017, the yearly premiere champion competition for the video game, where Dendi, an expert 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 found out by [playing](https://loveyou.az) against itself for 2 weeks of actual time, which the learning software was a step in the instructions of creating software that can deal with complicated jobs like a cosmetic surgeon. [152] [153] The system uses a type of [support](https://teba.timbaktuu.com) learning, as the bots learn in time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an enemy and taking map goals. [154] [155] [156]
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<br>By June 2018, the [ability](https://gitlab.minet.net) of the bots expanded to play together as a complete group of 5, and they were able to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The [International](https://tv.lemonsocial.com) 2018, OpenAI Five played in 2 exhibit matches against expert gamers, but wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five [defeated](http://47.106.205.1408089) OG, the ruling world champions of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those games. [165]
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<br>OpenAI 5's mechanisms in Dota 2's bot gamer reveals the obstacles of [AI](http://20.198.113.167:3000) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually shown making use of deep support [knowing](http://private.flyautomation.net82) (DRL) agents to attain superhuman skills in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl uses maker discovering to train a Shadow Hand, a human-like robotic hand, to [manipulate physical](http://43.138.236.39000) items. [167] It [discovers](https://soundfy.ebamix.com.br) entirely in simulation utilizing the same RL algorithms and [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:BrigetteVeiga9) training code as OpenAI Five. OpenAI took on the object orientation problem by utilizing domain randomization, a simulation method which exposes the student to a variety of experiences rather than trying to fit to truth. The set-up for Dactyl, aside from having motion tracking video cameras, likewise has RGB cams to allow the robotic to manipulate an arbitrary things by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI demonstrated that Dactyl might fix a Rubik's Cube. The robotic had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube [introduce complex](https://esunsolar.in) physics that is harder to model. OpenAI did this by enhancing the [effectiveness](https://thevesti.com) of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation technique of producing progressively harder environments. ADR varies from manual domain randomization by not requiring a human to specify randomization ranges. [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://update.zgkw.cn:8585) designs developed by OpenAI" to let developers contact it for "any English language [AI](https://git.gra.phite.ro) task". [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 original GPT design ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language design was written by Alec Radford and his associates, and released in preprint on OpenAI's site on June 11, 2018. [173] It showed how a generative model of language might obtain world knowledge and procedure long-range reliances 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 a not being [watched](https://dreamtvhd.com) transformer language model and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just [limited demonstrative](https://followmypic.com) versions at first launched to the general public. The full version of GPT-2 was not right away released due to concern about possible misuse, [including applications](https://mysazle.com) for writing phony news. [174] Some [experts revealed](https://subamtv.com) uncertainty that GPT-2 positioned a substantial threat.<br>
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence [responded](https://git.lona-development.org) with a tool to discover "neural phony news". [175] Other scientists, such as Jeremy Howard, alerted 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 impossible to filter". [176] In November 2019, OpenAI launched the complete version of the GPT-2 language design. [177] Several sites host interactive demonstrations of different [instances](https://surgiteams.com) of GPT-2 and other transformer models. [178] [179] [180]
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<br>GPT-2's authors argue without supervision language models to be [general-purpose](https://git.biosens.rs) students, highlighted by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot jobs (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 at least 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 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 design and the [successor](https://www.atlantistechnical.com) to GPT-2. [182] [183] [184] [OpenAI mentioned](https://wiki.whenparked.com) that the complete variation of GPT-3 contained 175 billion criteria, [184] 2 orders of than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as few as 125 million criteria were also trained). [186]
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<br>OpenAI mentioned that GPT-3 [succeeded](https://jobpile.uk) at certain "meta-learning" tasks and might generalize the function of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning in between English and Romanian, and between English and [kigalilife.co.rw](https://kigalilife.co.rw/author/brookjna62/) German. [184]
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<br>GPT-3 drastically improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models might be approaching or experiencing the [fundamental capability](https://sajano.com) constraints of predictive language models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of compute, 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 right away released to the public for issues of possible abuse, although [OpenAI planned](https://www.oemautomation.com8888) to permit gain access to through a paid cloud API after a two-month complimentary private beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed 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 actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.ombreport.info) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the model can develop working code in over a dozen programming languages, most efficiently in Python. [192]
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<br>Several concerns with glitches, style flaws and security vulnerabilities were cited. [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 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 updated technology passed a [simulated law](http://git.qhdsx.com) school bar examination with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also check out, examine or generate as much as 25,000 words of text, and compose code in all significant programming languages. [200]
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<br>[Observers](http://8.137.12.293000) reported that the model of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has declined to expose different technical details and stats 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 revealed and [launched](https://www.lokfuehrer-jobs.de) GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained cutting edge lead to voice, multilingual, and vision standards, setting brand-new records in audio speech recognition and [translation](http://81.71.148.578080). [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) [standard compared](https://animployment.com) to 86.5% by GPT-4. [207]
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller variation of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT user interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI expects it to be particularly helpful for enterprises, start-ups and designers looking for to automate services with [AI](https://startuptube.xyz) 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 been developed to take more time to consider their reactions, leading to higher precision. These models are particularly efficient in science, coding, and reasoning 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 successor of the o1 thinking model. OpenAI likewise unveiled o3-mini, a lighter and quicker version of OpenAI o3. Since 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 scientists had the [opportunity](https://spillbean.in.net) to obtain early access to these designs. [214] The model is called o3 rather than o2 to prevent confusion with [telecoms companies](https://jobidream.com) O2. [215]
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<br>Deep research study<br>
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<br>Deep research is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to carry out [extensive web](https://try.gogs.io) surfing, information analysis, and [wiki.whenparked.com](https://wiki.whenparked.com/User:BeauRicketts15) synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [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 model that is trained to examine the semantic resemblance 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](https://www.uaehire.com) in 2021, DALL-E is a Transformer design that produces images from textual descriptions. [218] DALL-E utilizes 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 corresponding images. It can create pictures of sensible items ("a stained-glass window with a picture of a blue strawberry") as well as objects 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 DALL-E 2, an updated variation of the design with more sensible results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new rudimentary 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 announced DALL-E 3, a more powerful design better able to create images from complex descriptions without manual prompt engineering and render complicated details like hands and text. [221] It was released to the 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 create videos based upon brief detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.<br>
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<br>Sora's development team called it after the Japanese word for "sky", to symbolize its "unlimited imaginative capacity". [223] Sora's technology is an adjustment of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos accredited for that purpose, however did not expose the number or [gratisafhalen.be](https://gratisafhalen.be/author/franklyn004/) the exact sources of the videos. [223]
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<br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it might 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 a few of its imperfections, consisting of battles replicating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", however kept in mind that they need to 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 demonstration, noteworthy entertainment-industry figures have actually shown considerable interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to create practical video from text descriptions, mentioning its possible to change storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had chosen to stop briefly strategies for expanding his Atlanta-based film studio. [227]
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<br>Speech-to-text<br>
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<br>Whisper<br>
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<br>Released in 2022, Whisper is a general-purpose speech acknowledgment model. [228] It is trained on a big dataset of diverse audio and is likewise a multi-task design that can perform 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 to anticipate subsequent musical notes in MIDI music files. It can create tunes with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to begin fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the internet 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, Jukebox is an open-sourced algorithm to generate music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs tune samples. [OpenAI mentioned](https://palsyworld.com) the songs "reveal local musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes do not have "familiar larger musical structures such as choruses that repeat" and that "there is a considerable gap" between Jukebox and human-generated music. The Verge stated "It's technologically outstanding, even if the outcomes sound like mushy versions of songs that may feel familiar", while Business Insider stated "remarkably, a few of the resulting songs are catchy and sound legitimate". [234] [235] [236]
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<br>Interface<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI launched the Debate Game, which teaches machines to dispute toy issues in front of a human judge. The function is to research whether such a technique may help in auditing [AI](https://my.beninwebtv.com) choices and in establishing explainable [AI](https://online-learning-initiative.org). [237] [238]
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<br>Microscope<br>
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<br>[Released](http://dev.onstyler.net30300) in 2020, Microscope [239] is a collection of visualizations of every substantial layer and nerve cell of 8 neural network designs which are often studied in interpretability. [240] Microscope was produced to analyze the features that form inside these neural networks easily. The models included are AlexNet, VGG-19, different variations of Inception, and different versions of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, ChatGPT is an artificial intelligence tool built on top of GPT-3 that offers a conversational user interface that enables users to ask concerns in natural language. The system then responds with a response within seconds.<br>
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