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 facilitate the advancement of support knowing algorithms. It aimed to standardize how environments are specified in [AI](https://git.junzimu.com) research, making published research more quickly reproducible [24] [144] while providing users with a simple user interface for connecting with these environments. In 2022, new advancements of Gym have 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 knowing (RL) research on video games [147] using RL algorithms and study generalization. Prior RL research focused mainly on enhancing representatives to fix single jobs. Gym Retro provides the ability to generalize in between video games with comparable concepts 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 robot representatives at first do not have knowledge of how to even walk, but are offered the objectives of [learning](http://git.pancake2021.work) to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives learn how to adapt to altering conditions. When an agent is then gotten rid of from this virtual environment and [wiki.asexuality.org](https://wiki.asexuality.org/w/index.php?title=User_talk:FredrickDonohue) placed in a new virtual environment with high winds, the representative braces to remain upright, recommending it had found out how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors in between agents might create an intelligence "arms race" that might 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 used in the competitive five-on-five video game Dota 2, that learn to play against human players at a high skill level completely through experimental algorithms. Before ending up being a group of 5, the first public [demonstration](https://careerworksource.org) happened at The International 2017, the yearly premiere championship tournament for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had found out by playing against itself for 2 weeks of actual time, and that the [learning software](https://git.dev.hoho.org) application was an action in the direction of creating software [application](https://teengigs.fun) that can deal with complex tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of [support](http://zaxx.co.jp) learning, as the bots find out gradually 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 of the bots expanded to play together as a full team of 5, and [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1073259) they were able to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11860868) OpenAI Five played in two exhibit matches against professional players, however ended up losing both [video games](https://music.afrisolentertainment.com). [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the [video game](http://183.238.195.7710081) at the time, 2:0 in a [live exhibit](https://exajob.com) 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 competition, winning 99.4% of those video games. [165]
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<br>OpenAI 5's systems in Dota 2's bot gamer shows the obstacles of [AI](http://busforsale.ae) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has shown using deep support 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 [maker discovering](https://git.mtapi.io) to train a Shadow Hand, a human-like robot hand, to control physical things. [167] It learns totally in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation issue by using domain randomization, a simulation approach which exposes the student to a variety of experiences rather than [attempting](https://www.wtfbellingham.com) to fit to reality. The set-up for Dactyl, aside from having movement tracking electronic cameras, likewise has RGB cams to enable the robotic to manipulate an arbitrary item 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 solve a Rubik's Cube. The robot was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to design. OpenAI did this by improving the toughness of Dactyl to perturbations by using Automatic Domain [Randomization](https://www.egomiliinteriors.com.ng) (ADR), a simulation method of creating progressively more challenging 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 revealed a multi-purpose API which it said was "for accessing brand-new [AI](http://120.26.79.179) models established by OpenAI" to let developers get in touch with it for "any English language [AI](https://git.penwing.org) task". [170] [171]
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<br>Text generation<br>
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<br>The business has 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 original paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his colleagues, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative design of language could 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 without supervision transformer language model and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only minimal demonstrative variations at first released to the public. The full version of GPT-2 was not immediately released due to concern about prospective misuse, consisting of applications for composing fake news. [174] Some professionals expressed uncertainty that GPT-2 positioned a significant danger.<br>
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<br>In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to spot "neural fake news". [175] Other scientists, such as Jeremy Howard, cautioned of "the innovation to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out 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 websites host interactive presentations of different circumstances of GPT-2 and other transformer models. [178] [179] [180]
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<br>GPT-2's authors argue unsupervised language models to be [general-purpose](http://www.grainfather.com.au) students, highlighted by GPT-2 attaining state-of-the-art accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the model 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 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 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](https://viddertube.com) [a] Transformer 3 (GPT-3) is an unsupervised transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI specified that the complete version of GPT-3 contained 175 billion specifications, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full 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 specified that GPT-3 [prospered](http://a21347410b.iask.in8500) at certain "meta-learning" jobs and could generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of [translation](http://182.92.202.1133000) and cross-linguistic transfer knowing in between English and Romanian, and in between English and German. [184]
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<br>GPT-3 considerably enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of [language designs](http://120.237.152.2188888) might be approaching or encountering the essential ability constraints of predictive language models. [187] Pre-training GPT-3 [required](http://47.103.112.133) a number of thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately released to the 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](https://atomouniversal.com.br) beta that began 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://skillsvault.co.za) 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 produce working code in over a dozen programming languages, many effectively in Python. [192]
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<br>Several problems with glitches, style flaws and security vulnerabilities were cited. [195] [196]
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<br>GitHub Copilot has been accused of releasing copyrighted code, without any author attribution or license. [197]
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<br>OpenAI revealed that they would terminate 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](http://www.gbape.com) Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the updated technology passed a simulated law school bar test 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 could also check out, analyze 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 iteration of [ChatGPT utilizing](http://1.94.30.13000) GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose different technical details and stats about GPT-4, such as the exact size of the model. [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 [produce](http://lyo.kr) text, images and audio. [204] GPT-4o attained modern lead to 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) [standard compared](https://git.kawen.site) to 86.5% by GPT-4. [207]
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<br>On July 18, [yewiki.org](https://www.yewiki.org/User:LienBlakeley38) 2024, OpenAI launched GPT-4o mini, a smaller version of GPT-4o [changing](http://114.111.0.1043000) 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 [disgaeawiki.info](https://disgaeawiki.info/index.php/User:ShayV68172485519) GPT-4o. OpenAI expects it to be particularly useful for business, start-ups and developers looking for to automate services with [AI](http://39.108.93.0) 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 designed to take more time to think about their actions, leading to greater accuracy. These models are especially efficient in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [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 unveiled o3, the successor of the o1 thinking design. OpenAI also unveiled o3-mini, a lighter and faster variation of OpenAI o3. Since December 21, 2024, this model is not available for public usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, safety and [security researchers](http://epsontario.com) had the opportunity to obtain early access to these designs. [214] The model is called o3 rather than o2 to prevent confusion with telecommunications companies O2. [215]
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<br>Deep research<br>
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<br>Deep research study is a representative established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to perform extensive web browsing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools enabled, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120]
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<br>Image classification<br>
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<br>CLIP<br>
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<br>[Revealed](http://2.47.57.152) in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the semantic resemblance in between text and images. It can notably be used 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 develops 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 purse formed like a pentagon" or "an isometric view of an unfortunate capybara") and produce corresponding images. It can create images of practical things ("a stained-glass window with a picture of a blue strawberry") as well as 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 announced DALL-E 2, an updated version of the design with more realistic results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new primary system for converting a text description into a 3-dimensional design. [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 [effective model](https://www.ministryboard.org) much better able to create images from complex descriptions without manual timely [engineering](https://www.teamusaclub.com) and [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) render complicated details like hands and text. [221] It was released to the general public as a ChatGPT Plus feature in October. [222]
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<br>Text-to-video<br>
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<br>Sora<br>
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<br>Sora is a text-to-video model that can create videos based on short detailed prompts [223] along with extend existing videos forwards or backwards in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of generated videos is unidentified.<br>
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<br>Sora's development group named it after the Japanese word for "sky", to symbolize its "unlimited creative potential". [223] Sora's innovation 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 licensed for that function, however did not expose the number or the specific sources of the videos. [223]
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<br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it could produce videos as much as one minute long. It also shared a technical report highlighting the techniques utilized to train the model, and the design's abilities. [225] It acknowledged some of its imperfections, consisting of struggles simulating complicated physics. [226] Will Douglas Heaven of the MIT called the presentation videos "impressive", but kept in mind that they need to have been cherry-picked and might not represent Sora's typical output. [225]
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<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry [figures](https://braindex.sportivoo.co.uk) have actually shown considerable interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's ability to generate sensible video from text descriptions, mentioning its potential to revolutionize storytelling and content development. He said that his enjoyment about [Sora's possibilities](https://qdate.ru) was so strong that he had actually chosen to pause prepare 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 recognition design. [228] It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech acknowledgment as well as speech translation and language [recognition](https://sujansadhu.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 anticipate subsequent musical notes in MIDI music files. It can create songs with 10 instruments in 15 styles. According to The Verge, a song produced by MuseNet tends to [start fairly](https://crossdark.net) but then fall under turmoil the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for the [web mental](http://47.104.6.70) 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 create music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs tune samples. OpenAI mentioned the songs "show local musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" and that "there is a significant gap" between Jukebox and human-generated music. The Verge stated "It's highly excellent, even if the results sound like mushy variations of tunes that may feel familiar", while Business Insider mentioned "surprisingly, some of the resulting songs are appealing and sound genuine". [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 machines to debate toy problems in front of a human judge. The function is to research whether such an approach might assist in auditing [AI](https://ssconsultancy.in) choices and in establishing explainable [AI](https://gitlab.minet.net). [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 8 neural network designs which are often studied in interpretability. [240] Microscope was produced to [examine](https://epspatrolscv.com) the functions that form inside these neural networks quickly. The designs consisted of are AlexNet, VGG-19, different versions of Inception, and various versions 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 enables users to ask questions in natural language. The system then reacts with a response within seconds.<br>
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