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 facilitate the advancement of reinforcement learning [algorithms](https://www.oradebusiness.eu). It aimed to standardize how environments are defined in [AI](http://gitlab.gavelinfo.com) research, making [released](http://124.16.139.223000) research study more quickly reproducible [24] [144] while providing users with an easy user interface for interacting with these environments. In 2022, new developments of Gym have actually been moved to the library Gymnasium. [145] [146]
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<br>Gym Retro<br>
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<br>Released in 2018, [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:RichieFirkins) Gym Retro is a [platform](https://git.ipmake.me) for reinforcement knowing (RL) research on computer game [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing agents to resolve single jobs. Gym Retro gives the capability to generalize in between video games with similar concepts 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 robot representatives initially do not have knowledge of how to even walk, but are provided the objectives of learning to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing process, the representatives learn how to adjust to altering conditions. When a representative is then gotten rid of from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, recommending it had actually found out how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives could develop an intelligence "arms race" that could increase an agent's capability to function even outside the context of the [competitors](https://git.arachno.de). [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 find out to play against human players at a high skill level entirely through experimental algorithms. Before becoming a team of 5, the very first public demonstration happened at The International 2017, the annual best championship tournament for the video game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for 2 weeks of actual time, and that the learning software application was a step in the instructions of developing software application that can handle complex jobs like a surgeon. [152] [153] The system utilizes a form of reinforcement knowing, as the bots find out over time by playing against themselves hundreds of times a day for months, and are rewarded for [actions](http://www.hcmis.cn) such as eliminating an opponent and taking map objectives. [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 ability to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against professional players, however wound up losing both [video games](http://qiriwe.com). [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champions of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public appearance came later on that month, where they played in 42,729 overall games in a four-day open online competition, winning 99.4% of those video games. [165]
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<br>OpenAI 5's mechanisms in Dota 2's bot player reveals the challenges of [AI](https://centraldasbiblias.com.br) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated making use of deep reinforcement knowing (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl utilizes machine finding out to train a Shadow Hand, a human-like robotic hand, to control physical items. [167] It learns totally in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation issue by using domain randomization, a simulation method which [exposes](https://mulkinflux.com) the student to a variety of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having [motion tracking](https://library.kemu.ac.ke) cams, likewise has RGB video cameras to enable the robotic to control an [approximate](https://gitea.nongnghiepso.com) things by seeing it. In 2018, OpenAI showed that the system was able to control a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI showed that Dactyl could solve a Rubik's Cube. The robot was able to resolve the puzzle 60% of the time. Objects like the [Rubik's Cube](https://gemma.mysocialuniverse.com) present complicated physics that is harder to model. OpenAI did this by improving the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of producing gradually more tough environments. ADR differs from manual domain randomization by not needing 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 brand-new [AI](https://pakfindjob.com) designs established by OpenAI" to let developers contact it for "any English language [AI](https://dvine.tv) job". [170] [171]
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<br>Text generation<br>
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<br>The company has promoted generative pretrained transformers (GPT). [172]
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<br>OpenAI's original GPT design ("GPT-1")<br>
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<br>The initial 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 revealed 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 adjoining 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 transformer language design and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only restricted demonstrative variations initially released to the general public. The full variation of GPT-2 was not immediately launched due to concern about prospective misuse, including applications for composing phony news. [174] Some professionals revealed uncertainty that GPT-2 posed a substantial threat.<br>
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to detect "neural fake news". [175] Other scientists, such as Jeremy Howard, cautioned of "the technology to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be impossible to filter". [176] In November 2019, OpenAI released the total variation of the GPT-2 language design. [177] Several websites host interactive demonstrations of different circumstances of GPT-2 and other transformer models. [178] [179] [180]
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<br>GPT-2's authors argue without supervision language designs to be general-purpose 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](https://gitlab.amepos.in) examples).<br>
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<br>The corpus it was [trained](https://git.kitgxrl.gay) on, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by utilizing byte [pair encoding](https://www.pkjobs.store). This permits representing any string of characters by encoding both individual characters and multiple-character tokens. [181]
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<br>GPT-3<br>
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<br>First explained in May 2020, [Generative Pre-trained](https://git.arachno.de) [a] Transformer 3 (GPT-3) is a not being watched transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI stated that the complete [variation](https://gitea-working.testrail-staging.com) of GPT-3 contained 175 billion parameters, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 designs with as couple of as 125 million criteria were also trained). [186]
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<br>OpenAI stated that GPT-3 prospered at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer [knowing](https://www.eadvisor.it) in between English and Romanian, and between English and German. [184]
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<br>GPT-3 dramatically improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or experiencing the [basic ability](https://crownmatch.com) constraints of predictive language models. [187] Pre-training GPT-3 [required](https://www.medicalvideos.com) a number of thousand petaflop/s-days [b] of calculate, [compared](https://youtoosocialnetwork.com) to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately launched to the public for issues of possible abuse, although OpenAI prepared 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 licensed solely 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 furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://www.haimimedia.cn:3001) powering the [code autocompletion](http://ratel.ng) [tool GitHub](https://xn--939a42kg7dvqi7uo.com) Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can develop working code in over a dozen shows languages, a lot of efficiently in Python. [192]
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<br>Several concerns with glitches, design defects and security vulnerabilities were pointed out. [195] [196]
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<br>GitHub Copilot has actually been implicated of releasing copyrighted code, without any author attribution or license. [197]
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<br>OpenAI announced that they would cease 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 revealed 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 school bar examination with a rating around the top 10% of [test takers](https://gogs.rg.net). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also check out, analyze or produce as much as 25,000 words of text, and compose code in all major programming languages. [200]
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<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 [retained](https://www.themart.co.kr) some of the issues with earlier revisions. [201] GPT-4 is also efficient in taking images as input on [ChatGPT](http://haiji.qnoddns.org.cn3000). [202] OpenAI has [declined](http://39.100.93.1872585) to reveal various 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 revealed and released GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained state-of-the-art outcomes 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 GPT-4o mini, a smaller variation of GPT-4o changing 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 especially beneficial for enterprises, start-ups and designers looking for to automate services with [AI](https://dubai.risqueteam.com) 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 believe about their responses, causing higher precision. These designs are especially effective in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was [changed](https://www.pickmemo.com) by o1. [211]
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<br>o3<br>
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<br>On December 20, 2024, OpenAI revealed o3, [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:FerminBrannon00) the successor of the o1 reasoning model. OpenAI likewise unveiled o3-mini, a lighter and much faster variation of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the opportunity to obtain early access to these models. [214] The model is called o3 rather than o2 to avoid confusion with telecommunications providers O2. [215]
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<br>Deep research<br>
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<br>Deep research study is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform comprehensive web surfing, information analysis, and [wiki.whenparked.com](https://wiki.whenparked.com/User:AishaCrampton4) synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools enabled, it reached a precision 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 examine the semantic similarity in between text and images. It can notably be utilized for image classification. [217]
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<br>Text-to-image<br>
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<br>DALL-E<br>
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<br>Revealed in 2021, 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 translate natural language inputs (such as "a green leather purse formed like a pentagon" or "an isometric view of a sad capybara") and [produce](https://trulymet.com) corresponding images. It can create images of practical objects ("a stained-glass window with an image of a blue strawberry") as well as things that do not exist in reality ("a cube with the texture of a porcupine"). 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 model with more sensible results. [219] In December 2022, [OpenAI released](https://git.mista.ru) on [GitHub software](https://www.myjobsghana.com) for Point-E, a new basic 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 effective model better able to generate images from complex descriptions without manual timely 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 design that can create videos based upon short detailed triggers [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 optimum length of generated videos is unknown.<br>
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<br>Sora's development group named it after the Japanese word for "sky", to symbolize its "unlimited imaginative potential". [223] Sora's technology is an adaptation of the [innovation](https://oeclub.org) behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos for that purpose, however did not expose the number or the specific 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, mentioning that it could create videos approximately 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 a few of its imperfections, including battles replicating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", but noted that they must have been cherry-picked and may not [represent Sora's](https://empleos.contatech.org) typical output. [225]
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<br>Despite uncertainty from some academic leaders following Sora's public demonstration, significant entertainment-industry figures have shown substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's capability to produce practical video from text descriptions, citing its potential to reinvent storytelling and material creation. He said that his enjoyment about Sora's possibilities was so strong that he had decided to stop briefly prepare 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 acknowledgment model. [228] It is trained on a big dataset of diverse audio and is also a multi-task design that can perform 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 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 tune generated by MuseNet tends to start fairly however then fall under chaos the longer it plays. [230] [231] In popular culture, [preliminary applications](http://git.r.tender.pro) of this tool were utilized as early as 2020 for the web mental thriller Ben Drowned to produce music for the titular character. [232] [233]
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<br>Jukebox<br>
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<br>Released in 2020, Jukebox is an open-sourced algorithm to generate music with vocals. After [training](https://git.marcopacs.com) on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs song samples. OpenAI stated the songs "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" and that "there is a substantial space" in between Jukebox and [disgaeawiki.info](https://disgaeawiki.info/index.php/User:MorrisSherrill8) human-generated music. The Verge specified "It's technologically outstanding, even if the results seem like mushy versions of tunes that may feel familiar", while Business Insider [mentioned](http://106.39.38.2421300) "surprisingly, some of the resulting songs are memorable and sound legitimate". [234] [235] [236]
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<br>User interfaces<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI released the Debate Game, which teaches makers to dispute toy issues in front of a human judge. The function is to research whether such a technique might assist in auditing [AI](https://www.suntool.top) choices and in developing explainable [AI](https://suprabullion.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 substantial layer and [wavedream.wiki](https://wavedream.wiki/index.php/User:CharaLamontagne) nerve cell of eight neural network designs which are typically studied in interpretability. [240] Microscope was produced to evaluate the functions that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, various variations of Inception, and various 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 constructed on top of GPT-3 that provides a [conversational](https://alldogssportspark.com) user interface that allows users to ask concerns in natural language. The system then reacts with a response within seconds.<br>
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