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<br>Announced in 2016, Gym is an open-source Python library designed to assist in the advancement of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://openedu.com) research, making published research study more quickly reproducible [24] [144] while supplying users with a simple interface for connecting with these environments. In 2022, new advancements of Gym have actually been [relocated](http://162.14.117.2343000) to the [library Gymnasium](https://municipalitybank.com). [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 study on video games [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing agents to fix single jobs. Gym Retro gives the capability to generalize in between 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 robotic representatives initially lack knowledge of how to even stroll, but are offered the objectives of discovering to move and to press the [opposing representative](https://www.gotonaukri.com) out of the ring. [148] Through this adversarial knowing process, the agents find out how to adjust to changing conditions. When an agent is then eliminated from this virtual environment and put in a brand-new virtual environment with high winds, the representative braces to remain upright, recommending it had actually learned how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could develop an intelligence "arms race" that could [increase](https://wiki.sublab.net) an agent's ability to function 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 team of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that discover to play against human players at a high skill level [totally](https://empleos.contatech.org) through experimental algorithms. Before ending up being a team of 5, the very first public presentation took place at The International 2017, the yearly best championship tournament for the video game, where Dendi, an expert 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 actually learned by playing against itself for 2 weeks of actual time, which the learning software was an action in the instructions of producing software application that can manage complicated tasks like a surgeon. [152] [153] The system uses a type of support knowing, as the bots find out over time by playing against themselves hundreds of times a day for months, and are rewarded for actions 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 expanded to play together as a full team of 5, and [wiki-tb-service.com](http://wiki-tb-service.com/index.php?title=Benutzer:Dwight6450) they were able to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert gamers, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champs of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last [public appearance](http://1.92.128.2003000) came later that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those video games. [165] |
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<br>OpenAI 5's mechanisms in Dota 2's bot gamer shows the obstacles of [AI](https://acrohani-ta.com) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has actually demonstrated making use 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, Dactyl utilizes machine discovering to train a Shadow Hand, a human-like robotic hand, to control [physical objects](http://gkpjobs.com). [167] It learns entirely in simulation utilizing the exact same RL algorithms and [training code](https://cello.cnu.ac.kr) as OpenAI Five. OpenAI tackled the things orientation issue by utilizing domain randomization, a simulation approach which exposes the student to a range of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking video cameras, also has RGB cams to enable the robot to control an approximate object by seeing it. In 2018, OpenAI showed that the system was able to [control](https://anychinajob.com) 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 resolve the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to model. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation method of [creating](http://git.picaiba.com) progressively more hard environments. ADR differs 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 which it said was "for accessing new [AI](http://modiyil.com) designs developed by OpenAI" to let developers get in touch with it for "any English language [AI](http://git.agdatatec.com) task". [170] [171] |
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<br>Text generation<br> |
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<br>The business has actually 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 design was written by Alec Radford and his associates, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world knowledge and procedure long-range dependences 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 an unsupervised transformer language design and the follower to OpenAI's initial GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative variations initially released to the general public. The complete [variation](http://udyogservices.com) of GPT-2 was not immediately launched due to concern about prospective abuse, [including applications](https://customerscomm.com) for writing phony news. [174] Some specialists revealed uncertainty that GPT-2 presented a substantial risk.<br> |
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<br>In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "neural fake 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 released the complete version of the GPT-2 [language](https://bewerbermaschine.de) design. [177] Several websites host interactive demonstrations of various circumstances of GPT-2 and other [transformer designs](https://www.blatech.co.uk). [178] [179] [180] |
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<br>GPT-2's authors argue unsupervised language models to be general-purpose learners, shown by GPT-2 attaining cutting edge precision 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 somewhat 40 [gigabytes](https://git.antonshubin.com) of text from URLs shared in [Reddit submissions](http://codaip.co.kr) with at least 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by using byte pair encoding. This allows representing any string of [characters](https://visualchemy.gallery) by encoding both [specific characters](http://fridayad.in) 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 an unsupervised transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete version of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as few as 125 million criteria were likewise trained). [186] |
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<br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" jobs and could generalize the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and [pipewiki.org](https://pipewiki.org/wiki/index.php/User:AllenHankins0) cross-linguistic transfer learning in between English and Romanian, and in between English and German. [184] |
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<br>GPT-3 considerably improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or experiencing the basic capability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately launched to the general public for issues of possible abuse, although OpenAI planned to allow gain access to through a paid cloud API after a two-month free [personal](https://medhealthprofessionals.com) 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://116.205.229.196:3000) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the model can create working code in over a dozen programming languages, many successfully in Python. [192] |
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<br>Several concerns with glitches, style defects and security vulnerabilities were mentioned. [195] [196] |
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<br>GitHub Copilot has been accused of producing copyrighted code, with no author attribution or license. [197] |
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<br>OpenAI announced 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 announced the release of Generative Pre-trained Transformer 4 (GPT-4), capable of 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 might likewise check out, examine or generate up to 25,000 words of text, and compose code in all major programming languages. [200] |
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<br>[Observers](https://socialeconomy4ces-wiki.auth.gr) reported that the model of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to expose numerous technical details and data about GPT-4, such as the precise size of the design. [203] |
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<br>GPT-4o<br> |
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<br>On May 13, 2024, [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:QYKElton1324495) OpenAI announced and released GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained modern outcomes in voice, multilingual, and vision standards, setting brand-new records in audio speech recognition and [translation](http://www.iilii.co.kr). [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 launched GPT-4o mini, a smaller sized 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 particularly useful for enterprises, start-ups and designers seeking to automate services with [AI](https://one2train.net) agents. [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 models, which have actually been created to take more time to think of their actions, causing greater precision. These designs are particularly effective in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was replaced by o1. [211] |
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<br>o3<br> |
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<br>On December 20, 2024, OpenAI unveiled o3, the successor of the o1 reasoning model. OpenAI likewise revealed o3-mini, a lighter and faster version of OpenAI o3. As of December 21, 2024, this model is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the opportunity to obtain early access to these designs. [214] The design is called o3 instead of o2 to avoid confusion with telecommunications companies O2. [215] |
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<br>Deep research<br> |
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<br>Deep research is an [agent developed](https://git.aionnect.com) by OpenAI, revealed on February 2, 2025. It [leverages](http://team.pocketuniversity.cn) the capabilities of OpenAI's o3 design to carry out substantial web surfing, information analysis, and synthesis, delivering detailed reports within a [timeframe](https://lepostecanada.com) of 5 to 30 minutes. [216] With browsing and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] |
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<br>Image category<br> |
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<br>CLIP<br> |
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<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to analyze the semantic resemblance in between text and images. It can notably be used 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 develops images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can produce images of reasonable objects ("a stained-glass window with an image of a blue strawberry") along with 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](https://video.invirtua.com) DALL-E 2, an updated variation of the model with more sensible results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new basic system for converting a [text description](http://gitlab.y-droid.com) into a 3[-dimensional design](http://git.daiss.work). [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 intricate descriptions without manual prompt engineering and render complicated details like hands and text. [221] It was launched to the general public as a [ChatGPT](https://gitea.oio.cat) 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 generate videos based upon short detailed triggers [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 optimum length of generated videos is unknown.<br> |
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<br>Sora's development team called it after the Japanese word for "sky", to represent its "limitless imaginative capacity". [223] is an adjustment of the innovation behind the DALL · E 3 [text-to-image model](http://47.110.52.1323000). [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos certified for that function, but did not reveal 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, mentioning that it might [generate videos](http://bluemobile010.com) as much as one minute long. It likewise shared a technical report highlighting the [methods](https://git.buzhishi.com14433) used to train the model, and the model's capabilities. [225] It acknowledged some of its shortcomings, consisting of battles simulating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", but noted that they should 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 have actually shown considerable interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's ability to create [reasonable video](http://47.109.30.1948888) from text descriptions, mentioning its prospective to transform storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to stop briefly prepare for expanding 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 recognition model. [228] It is trained on a big dataset of diverse audio and is also a multi-task model that can carry out multilingual speech acknowledgment as well as speech translation and language recognition. [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 generate tunes with 10 instruments in 15 designs. According to The Verge, a tune generated by MuseNet tends to [start fairly](http://8.140.244.22410880) but then fall into turmoil the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for the web psychological 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 stated the songs "show regional musical coherence [and] follow conventional chord patterns" but acknowledged that the songs lack "familiar larger musical structures such as choruses that repeat" which "there is a substantial gap" between Jukebox and human-generated music. The Verge stated "It's technically excellent, even if the results sound like mushy versions of tunes that might feel familiar", while Business Insider mentioned "remarkably, some of the resulting songs are catchy and sound legitimate". [234] [235] [236] |
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<br>Interface<br> |
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<br>Debate Game<br> |
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<br>In 2018, OpenAI introduced the Debate Game, which teaches makers to dispute toy issues in front of a human judge. The purpose is to research whether such an approach might assist in auditing [AI](https://starfc.co.kr) choices and in developing explainable [AI](http://git.sinoecare.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 [considerable layer](http://www.cl1024.online) and nerve cell of eight neural network models which are typically studied in interpretability. [240] Microscope was created to analyze the functions that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, different 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 a synthetic intelligence tool constructed on top of GPT-3 that provides a [conversational](https://employmentabroad.com) user [interface](https://git.nagaev.pro) that enables users to ask questions in natural language. The system then responds with a response within seconds.<br> |
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