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<br>Announced in 2016, Gym is an [open-source Python](https://charmyajob.com) library designed to assist in the advancement of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](https://gitea.elkerton.ca) research study, making published research more easily reproducible [24] [144] while offering users with an easy user interface for interacting 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 learning (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on enhancing agents to solve single jobs. Gym Retro offers the ability to generalize in between video games with comparable ideas but different 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 agents at first lack knowledge of how to even stroll, but are given the goals of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial learning process, the representatives find out how to adjust to altering conditions. When an agent is then gotten rid of from this virtual environment and placed in a new virtual environment with high winds, the representative braces to remain upright, recommending it had actually learned how to balance 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 function 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 five 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 completely through trial-and-error algorithms. Before ending up being a team of 5, the first public presentation happened at The International 2017, the annual best champion competition for the video 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](http://git.oksei.ru) that the bot had found out by playing against itself for 2 weeks of genuine time, which the learning software application was a step in the direction of creating software that can deal with intricate jobs like a surgeon. [152] [153] The system utilizes a kind of reinforcement learning, [ratemywifey.com](https://ratemywifey.com/author/xjstrudi716/) as the bots find out with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an opponent and taking map goals. [154] [155] [156] |
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<br>By June 2018, the capability of the bots broadened to play together as a full group of 5, and they had the ability to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against professional gamers, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the video game at the time, 2:0 in a live exhibition match in [San Francisco](https://duyurum.com). [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, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:VeraDdv1641) winning 99.4% of those video games. [165] |
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<br>OpenAI 5's systems in Dota 2's bot player reveals the challenges of [AI](http://www.visiontape.com) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has demonstrated using deep reinforcement learning (DRL) representatives to [attain superhuman](https://sebagai.com) proficiency 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 robot hand, to control physical objects. [167] It discovers completely in simulation using the same [RL algorithms](https://mediawiki.hcah.in) and [training](http://git.1473.cn) code as OpenAI Five. OpenAI took on the item orientation problem by using domain randomization, a simulation method which exposes the student to a range of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having [motion tracking](https://gruppl.com) video cameras, also has RGB video cameras to enable the robotic to control an approximate object by seeing it. In 2018, OpenAI revealed that the system had the ability to control a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI demonstrated that Dactyl could resolve a Rubik's Cube. The robotic had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of creating gradually harder environments. ADR differs from manual domain randomization by not requiring a human to specify randomization varieties. [169] |
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<br>API<br> |
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<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://gitlab.henrik.ninja) designs established by OpenAI" to let designers call on it for "any English language [AI](https://www.soundofrecovery.org) job". [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 model ("GPT-1")<br> |
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<br>The original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his colleagues, and in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative design of language might obtain world understanding and procedure long-range dependences by pre-training on a diverse 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 without supervision transformer language design and [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:JacksonPutman) the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just restricted demonstrative variations at first launched to the general public. The complete variation of GPT-2 was not instantly released due to concern about prospective abuse, consisting of applications for composing phony news. [174] Some specialists revealed uncertainty that GPT-2 presented a [substantial danger](https://www.fightdynasty.com).<br> |
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<br>In action to GPT-2, the Allen [Institute](https://westzoneimmigrations.com) for Artificial Intelligence responded with a tool to spot "neural fake news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". [176] In November 2019, OpenAI released the total variation of the GPT-2 language model. [177] Several websites 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](http://101.34.39.123000) argue not being watched language designs to be general-purpose learners, highlighted by GPT-2 attaining cutting edge precision 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](http://www.lucaiori.it) with a minimum of 3 upvotes. It prevents certain concerns encoding [vocabulary](https://carepositive.com) 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 follower to GPT-2. [182] [183] [184] OpenAI specified that the complete variation of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were likewise trained). [186] |
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<br>OpenAI specified that GPT-3 was [successful](http://104.248.138.208) at certain "meta-learning" jobs and might [generalize](http://62.234.223.2383000) the function of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning in between English and Romanian, and between [English](https://just-entry.com) and German. [184] |
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<br>GPT-3 significantly enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or coming across the basic capability constraints of predictive language models. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not [instantly released](https://arbeitswerk-premium.de) to the public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a [paid cloud](https://gps-hunter.ru) 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://coolroomchannel.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the design can create working code in over a dozen shows languages, many successfully in Python. [192] |
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<br>Several problems with problems, style flaws and security [vulnerabilities](https://git.bourseeye.com) were mentioned. [195] [196] |
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<br>GitHub Copilot has been accused of discharging copyrighted code, without any author attribution or license. [197] |
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<br>OpenAI revealed that they would stop 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 revealed the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They revealed that the updated innovation passed a simulated law 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 likewise check out, analyze or generate up to 25,000 words of text, and write code in all major shows languages. [200] |
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<br>Observers reported that the iteration of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 [retained](https://societeindustrialsolutions.com) a few of the problems with earlier revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has decreased to reveal various technical details and data about GPT-4, such as the precise 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 released GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision benchmarks, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller sized version 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 [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:Polly03P7871) GPT-4o. OpenAI anticipates it to be especially useful for business, startups and [designers](https://nextodate.com) looking for to automate services with [AI](http://wowonder.technologyvala.com) agents. [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 designs, which have actually been developed to take more time to consider their actions, causing higher accuracy. These models are especially reliable in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1[-preview](http://kuma.wisilicon.com4000) 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 reasoning design. OpenAI likewise revealed o3-mini, a [lighter](https://just-entry.com) and much faster variation of OpenAI o3. As of December 21, 2024, this model is not available for [public usage](https://express-work.com). According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the chance to obtain early access to these designs. [214] The model is called o3 rather than o2 to avoid confusion with telecommunications companies O2. [215] |
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<br>Deep research study<br> |
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<br>Deep research is a [representative developed](http://www.book-os.com3000) by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to perform comprehensive web browsing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] |
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<br>Image classification<br> |
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<br>CLIP<br> |
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<br>[Revealed](https://sjee.online) in 2021, [wavedream.wiki](https://wavedream.wiki/index.php/User:MorrisVerge81) CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the semantic resemblance between text and images. It can especially 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 design that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can create [pictures](https://git.rt-academy.ru) of reasonable items ("a stained-glass window with a picture of a blue strawberry") in addition to things that do not exist in truth ("a cube with the texture of a porcupine"). Since 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 variation of the design with more reasonable outcomes. [219] In December 2022, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:DorotheaRincon) OpenAI published on GitHub software application for Point-E, a brand-new fundamental system for converting a text description into a 3-dimensional model. [220] |
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<br>DALL-E 3<br> |
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<br>In September 2023, OpenAI revealed DALL-E 3, a more powerful design better able to produce images from complex descriptions without manual timely engineering and render complex 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 on brief detailed triggers [223] as well as extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution up to 1920x1080 or 1080x1920. The optimum length of produced 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 creative potential". [223] Sora's innovation is an adaptation of the technology behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos along with [copyrighted videos](http://45.45.238.983000) certified for that function, but 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 public on February 15, 2024, stating that it might create videos approximately one minute long. It also shared a technical report highlighting the methods utilized to train the model, and the design's abilities. [225] It acknowledged some of its imperfections, [including battles](https://puming.net) imitating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", however kept in mind that they should have been cherry-picked and might not represent Sora's common output. [225] |
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<br>Despite uncertainty from some scholastic leaders following Sora's public demo, [notable](https://git.dev.hoho.org) entertainment-industry figures have actually revealed significant interest in the [technology's potential](https://jobdd.de). In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the innovation's capability to generate sensible video from text descriptions, mentioning its potential to transform storytelling and content development. He said that his [enjoyment](https://tayseerconsultants.com) about Sora's possibilities was so strong that he had actually decided to stop briefly plans 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 acknowledgment model. [228] It is trained on a big dataset of diverse audio and is likewise a multi-task model that can perform multilingual speech recognition 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 predict subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to begin fairly but then fall under mayhem the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized 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 create music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs song samples. [OpenAI mentioned](https://jmusic.me) the tunes "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" which "there is a significant space" between Jukebox and human-generated music. The Verge mentioned "It's highly impressive, even if the results seem like mushy variations of tunes that might feel familiar", while Business Insider mentioned "surprisingly, some of the resulting tunes are appealing and sound legitimate". [234] [235] [236] |
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<br>User user interfaces<br> |
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<br>Debate Game<br> |
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<br>In 2018, OpenAI introduced the Debate Game, which teaches machines to debate toy problems in front of a human judge. The function is to research whether such a technique may assist in auditing [AI](https://gitlab-heg.sh1.hidora.com) decisions and in developing explainable [AI](http://files.mfactory.org). [237] [238] |
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<br>Microscope<br> |
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<br>Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and neuron of eight [neural network](http://116.205.229.1963000) designs which are often studied in interpretability. [240] Microscope was developed to analyze the functions that form inside these neural networks quickly. The models included are AlexNet, VGG-19, various [versions](http://141.98.197.226000) 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 a synthetic intelligence tool constructed on top of GPT-3 that supplies a conversational user interface that enables users to ask questions in natural language. The system then reacts with a response within seconds.<br> |
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