Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library developed to help with the development of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://salesupprocess.it) research, making released research more quickly reproducible [24] [144] while offering users with an easy interface for connecting with these environments. In 2022, new advancements of Gym have been relocated 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](http://101.132.163.1963000) (RL) research on video games [147] using RL algorithms and study generalization. Prior RL research study focused mainly on optimizing agents to fix single jobs. Gym Retro offers the [capability](https://careers.midware.in) to generalize in between video games with similar principles but various looks.<br>
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<br>RoboSumo<br>
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<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially do not have understanding of how to even walk, however are offered the objectives of discovering to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives find out how to adjust to changing conditions. When a representative is then removed from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives might develop an intelligence "arms race" that might increase an agent's capability to work 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 5 OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that learn to play against human players at a high ability level totally through trial-and-error algorithms. Before ending up being a group of 5, the very first public presentation happened at The International 2017, the annual best champion tournament for the game, where Dendi, a professional [Ukrainian](https://gitlab.appgdev.co.kr) gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg [Brockman](https://www.unotravel.co.kr) explained that the bot had actually found out by [playing](https://gitea.mierzala.com) against itself for two weeks of actual time, which the knowing software was a step in the direction of developing software that can manage intricate tasks like a [cosmetic surgeon](https://droomjobs.nl). [152] [153] The system uses a type of reinforcement knowing, as the bots discover with time by playing against themselves [hundreds](https://brotato.wiki.spellsandguns.com) of 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 ability of the bots broadened to play together as a complete team of 5, and they had the to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 [exhibit matches](https://wiki.vst.hs-furtwangen.de) against expert players, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world [champions](http://git.liuhung.com) of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public appearance came later that month, where they played in 42,729 overall video games in a [four-day](http://45.55.138.823000) open online competition, winning 99.4% of those video games. [165]
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<br>OpenAI 5['s systems](https://owow.chat) in Dota 2's bot player shows the challenges of [AI](https://braindex.sportivoo.co.uk) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has shown the usage of deep support learning (DRL) representatives to attain superhuman skills in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:GayKastner43699) Dactyl uses device learning to train a Shadow Hand, a human-like robot hand, to [manipulate](https://git.es-ukrtb.ru) physical objects. [167] It finds out totally in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI took on the item orientation problem by [utilizing](http://jobsgo.co.za) domain randomization, a simulation approach which exposes the student to a variety of experiences rather than [attempting](https://gitlab.truckxi.com) to fit to reality. The set-up for Dactyl, aside from having [movement tracking](https://pyra-handheld.com) video cameras, likewise has RGB video cameras to enable the robot to manipulate an approximate item by seeing it. In 2018, OpenAI revealed that the system had the ability to manipulate a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI showed that Dactyl could resolve a Rubik's Cube. The robotic had the ability to solve the puzzle 60% of the time. Objects like the Rubik's Cube present [complicated](https://happylife1004.co.kr) physics that is harder to design. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of producing progressively harder environments. ADR varies from manual domain randomization by not requiring a human to define randomization varieties. [169]
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<br>API<br>
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<br>In June 2020, OpenAI announced a [multi-purpose API](https://work-ofie.com) which it said was "for accessing brand-new [AI](https://git.gumoio.com) models established by OpenAI" to let [developers](https://sunriji.com) get in touch with it for "any English language [AI](http://dndplacement.com) 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 initial GPT design ("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 coworkers, and released in preprint on OpenAI's site on June 11, 2018. [173] It showed how a generative design of language might obtain world understanding 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](https://www.istorya.net) 2 ("GPT-2") is a without supervision transformer language design and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only restricted demonstrative versions initially launched to the general public. The complete variation of GPT-2 was not immediately launched due to issue about potential misuse, consisting of applications for [writing phony](https://cdltruckdrivingcareers.com) news. [174] Some experts revealed uncertainty that GPT-2 postured a considerable hazard.<br>
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<br>In response to GPT-2, the Allen Institute for [Artificial Intelligence](https://novashop6.com) reacted with a tool to find "neural phony news". [175] Other researchers, such as Jeremy Howard, warned of "the technology to completely 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 variation of the GPT-2 language model. [177] Several sites 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 without supervision language models to be general-purpose students, highlighted by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not additional trained on any task-specific input-output examples).<br>
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<br>The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit submissions with at least 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 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 model and the [follower](https://sapjobsindia.com) to GPT-2. [182] [183] [184] OpenAI mentioned that the full version of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full [variation](https://telecomgurus.in) of GPT-2 (although GPT-3 models with as couple of as 125 million criteria were likewise trained). [186]
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<br>OpenAI mentioned that GPT-3 prospered at certain "meta-learning" tasks and could generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning in between [English](http://154.9.255.1983000) and Romanian, and between English and 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](https://radicaltarot.com) or coming across the essential ability constraints of predictive language models. [187] Pre-training GPT-3 [required](https://zeustrahub.osloop.com) a number of thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not right away launched to the public for concerns of possible abuse, although [OpenAI planned](https://carepositive.com) to allow gain access to through a paid cloud API after a two-month complimentary private beta that started in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was certified exclusively to Microsoft. [190] [191]
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<br>Codex<br>
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<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has actually additionally been [trained](https://aipod.app) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.kayserieticaretmerkezi.com) 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 create working code in over a lots shows languages, the majority of 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](https://southwestjobs.so) has actually been accused of releasing copyrighted code, with no author attribution or license. [197]
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<br>[OpenAI revealed](http://www.grainfather.com.au) that they would terminate support for Codex API on March 23, 2023. [198]
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<br>GPT-4<br>
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<br>On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the updated innovation passed a simulated law school bar exam with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, evaluate or create approximately 25,000 words of text, and compose code in all significant programming languages. [200]
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<br>[Observers](https://www.apkjobs.site) reported that the version of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caution that GPT-4 retained some of the issues with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal numerous technical details and statistics 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, images and audio. [204] GPT-4o attained cutting edge lead to voice, multilingual, and vision standards, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) benchmark compared to 86.5% by GPT-4. [207]
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<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller version 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 anticipates it to be especially helpful for enterprises, start-ups and designers looking for to automate services with [AI](http://47.113.115.239:3000) representatives. [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 actually been created to take more time to consider their actions, leading to greater precision. These models are especially efficient in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Team members. [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 successor of the o1 thinking model. OpenAI also unveiled o3-mini, a lighter and much faster version of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the chance to obtain early access to these models. [214] The design is called o3 instead of o2 to [prevent confusion](https://www.frigorista.org) with telecoms providers O2. [215]
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<br>Deep research<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 carry out comprehensive web surfing, information analysis, and synthesis, delivering detailed reports 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 classification<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 analyze the semantic similarity 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 model that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to interpret natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and generate matching images. It can produce pictures of sensible objects ("a stained-glass window with an image of a blue strawberry") in addition to things 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 upgraded version of the model with more sensible 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 announced DALL-E 3, a more powerful design much better able to produce images from complicated descriptions without manual timely engineering and render complicated details like hands and text. [221] It was released to the general public as a ChatGPT Plus function in October. [222]
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<br>Text-to-video<br>
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<br>Sora<br>
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<br>Sora is a text-to-video model that can create videos based on brief [detailed triggers](https://git.dev.hoho.org) [223] in addition to extend existing videos [forwards](http://gnu5.hisystem.com.ar) or backwards in time. [224] It can generate videos with resolution up to 1920x1080 or 1080x1920. The maximal length of created videos is unknown.<br>
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<br>Sora's development team called it after the Japanese word for "sky", to signify its "unlimited innovative potential". [223] Sora's technology is an adaptation of the innovation behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos certified for that function, but did not expose the number or the precise sources of the videos. [223]
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<br>OpenAI demonstrated some Sora-created high-definition videos to the public on February 15, 2024, specifying that it might [generate videos](https://cyltalentohumano.com) up to one minute long. It likewise shared a technical report highlighting the approaches utilized to train the design, and the design's abilities. [225] It acknowledged a few of its shortcomings, including battles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", but noted that they must have been cherry-picked and may not [represent Sora's](https://www.onlywam.tv) normal output. [225]
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<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, significant entertainment-industry figures have shown significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's ability to produce practical video from text descriptions, mentioning its possible to transform storytelling and content development. He said that his excitement about [Sora's possibilities](https://flowndeveloper.site) was so strong that he had chosen to pause prepare 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](https://hesdeadjim.org) is a general-purpose speech recognition model. [228] It is trained on a big dataset of diverse audio and is also a multi-task design that can carry out multilingual speech acknowledgment as well as 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](http://autogangnam.dothome.co.kr) 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 generated by MuseNet tends to start fairly but then fall under chaos the longer it plays. [230] [231] In [popular](http://101.43.151.1913000) culture, preliminary applications of this tool were utilized as early as 2020 for the web psychological thriller Ben Drowned to produce music for the titular character. [232] [233]
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<br>Jukebox<br>
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<br>Released in 2020, 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 bit of lyrics and outputs tune samples. OpenAI specified the tunes "reveal local musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" which "there is a substantial space" between Jukebox and human-generated music. The Verge specified "It's technologically remarkable, even if the outcomes sound like mushy versions of songs that may feel familiar", while Business Insider specified "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 launched the Debate Game, which teaches machines to dispute toy problems in front of a human judge. The purpose is to research study whether such a method might help in auditing [AI](http://secretour.xyz) choices and in developing explainable [AI](https://ruraltv.in). [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 often studied in interpretability. [240] Microscope was developed to analyze the functions that form inside these [neural networks](http://jobsgo.co.za) easily. The designs included are AlexNet, VGG-19, various 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 artificial intelligence tool developed on top of GPT-3 that offers a conversational interface that enables users to ask concerns in natural language. The system then reacts with a response within seconds.<br>
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