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 <br>Announced in 2016, Gym is an open-source Python library developed to assist in the advancement of support learning algorithms. It aimed to standardize how environments are specified in [AI](https://www.smfsimple.com) research, making released research more easily reproducible [24] [144] while offering users with an easy interface for engaging with these environments. In 2022, new developments of Gym have been transferred to the library Gymnasium. [145] [146]
 <br>Gym Retro<br>
 <br>Released in 2018, Gym Retro is a platform for support learning (RL) research on computer game [147] using RL algorithms and research study generalization. Prior RL research focused mainly on optimizing representatives to solve single tasks. Gym Retro gives the capability to generalize in between video games with comparable concepts but various appearances.<br>
 <br>RoboSumo<br>
 <br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives at first lack understanding of how to even stroll, but are provided the objectives of finding out 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 changing conditions. When a representative is then removed from this virtual environment and put in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had discovered how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives could develop an intelligence "arms race" that could increase a [representative's ability](https://gitea.shoulin.net) to function even outside the context of the [competition](http://sujongsa.net). [148]
 <br>OpenAI 5<br>
 <br>OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that discover to play against human gamers at a high skill level totally through experimental algorithms. Before ending up being a team of 5, the very first public demonstration took place at The [International](http://copyvance.com) 2017, the yearly best championship tournament for the video game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for two weeks of actual time, and  [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:DianaRosenthal) that the learning software was a step in the instructions of developing software application that can handle intricate tasks like a surgeon. [152] [153] The system uses a type of [reinforcement](http://66.112.209.23000) knowing, as the bots find out over time by playing against themselves hundreds of times a day for months, and are rewarded for  [yewiki.org](https://www.yewiki.org/User:EdwinaMcintire3) actions such as eliminating an enemy and taking map goals. [154] [155] [156]
 <br>By June 2018, the ability of the bots expanded to play together as a full team of 5, and they had the ability to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against professional players, but wound up losing both [video games](https://www.lightchen.info). [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champions of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last [public appearance](https://woodsrunners.com) came later on that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those video games. [165]
 <br>OpenAI 5's systems in Dota 2's bot player reveals the obstacles of [AI](http://git.mutouyun.com:3005) [systems](http://118.190.145.2173000) in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated using deep reinforcement knowing (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166]
 <br>Dactyl<br>
 <br>[Developed](http://git.wangtiansoft.com) in 2018, Dactyl utilizes machine finding out to train a Shadow Hand, a human-like robotic hand, to control physical items. [167] It discovers totally in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the object orientation issue by using domain randomization, a simulation approach which exposes the student to a variety of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having motion tracking cams, also has RGB video cameras to permit the robotic to control an approximate item by seeing it. In 2018, OpenAI showed that the system was able to control a cube and an octagonal prism. [168]
 <br>In 2019, OpenAI demonstrated that Dactyl could fix a Rubik's Cube. The robot had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by improving the [toughness](http://code.snapstream.com) of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of generating gradually harder environments. ADR differs from manual domain randomization by not requiring a human to define randomization varieties. [169]
 <br>API<br>
 <br>In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](http://1688dome.com) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](http://47.103.29.129:3000) job". [170] [171]
 <br>Text generation<br>
 <br>The business has actually popularized generative pretrained transformers (GPT). [172]
 <br>OpenAI's initial GPT model ("GPT-1")<br>
 <br>The original paper on [generative](http://8.134.237.707999) pre-training of a transformer-based language model was written by Alec Radford and his coworkers,  [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2672496) 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 process long-range dependencies by pre-training on a varied corpus with long stretches of adjoining text.<br>
 <br>GPT-2<br>
 <br>Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language design and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative variations at first launched to the general public. The full variation of GPT-2 was not instantly launched due to concern about potential abuse, including applications for [composing phony](http://social.redemaxxi.com.br) news. [174] Some experts expressed [uncertainty](https://gogolive.biz) that GPT-2 presented a significant hazard.<br>
 <br>In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to detect "neural phony news". [175] Other researchers, such as Jeremy Howard, cautioned of "the technology to completely 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 complete version of the GPT-2 language design. [177] Several websites host interactive presentations of different circumstances of GPT-2 and other transformer models. [178] [179] [180]
 <br>GPT-2's authors argue not being watched language models to be general-purpose learners, [highlighted](https://www.drawlfest.com) by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not additional trained on any [task-specific input-output](https://whotube.great-site.net) examples).<br>
 <br>The corpus it was trained on, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain concerns encoding [vocabulary](https://www.beyoncetube.com) with word tokens by using byte pair encoding. This allows representing any string of characters by encoding both private characters and multiple-character tokens. [181]
 <br>GPT-3<br>
 <br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being watched transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion criteria, [184] two orders of magnitude larger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 designs with as couple of as 125 million parameters were likewise trained). [186]
 <br>OpenAI mentioned 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 provided examples of translation and cross-linguistic transfer knowing between English and Romanian, and between English and German. [184]
 <br>GPT-3 drastically enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models might be approaching or experiencing the essential capability constraints of predictive language models. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not right away launched to the public for issues of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month complimentary [private](https://gitlab.buaanlsde.cn) beta that began in June 2020. [170] [189]
 <br>On September 23, 2020, GPT-3 was certified solely to Microsoft. [190] [191]
 <br>Codex<br>
 <br>Announced in mid-2021, Codex is a descendant of GPT-3 that has additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.songyuchao.cn) powering the [code autocompletion](https://www.mepcobill.site) tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can produce working code in over a dozen shows languages, most efficiently in Python. [192]
 <br>Several issues with glitches, style defects and security vulnerabilities were cited. [195] [196]
 <br>GitHub Copilot has actually been accused of emitting copyrighted code, without any author attribution or license. [197]
 <br>OpenAI announced that they would stop [support](http://148.66.10.103000) for Codex API on March 23, 2023. [198]
 <br>GPT-4<br>
 <br>On March 14, 2023, [OpenAI revealed](https://gitlab.henrik.ninja) 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 test with a score around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also check out, analyze or generate up to 25,000 words of text, and [compose code](https://git.pm-gbr.de) in all significant shows languages. [200]
 <br>Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained some of the issues with earlier revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose numerous technical details and statistics about GPT-4, such as the exact size of the model. [203]
 <br>GPT-4o<br>
 <br>On May 13, 2024, OpenAI announced and released GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained state-of-the-art lead to voice, multilingual, and vision standards, setting brand-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]
 <br>On July 18, 2024, OpenAI released 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](https://gitea.alexandermohan.com) to $5 and $15 respectively for GPT-4o. OpenAI expects it to be especially helpful for enterprises, start-ups and designers looking for to automate services with [AI](http://git.365zuoye.com) representatives. [208]
 <br>o1<br>
 <br>On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been designed to take more time to think of their responses, causing greater accuracy. These models are particularly efficient in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was changed by o1. [211]
 <br>o3<br>
 <br>On December 20, 2024, [OpenAI revealed](http://116.63.157.38418) o3, the [successor](https://www.bongmedia.tv) of the o1 thinking design. OpenAI likewise revealed o3-mini, a lighter and [faster variation](https://kohentv.flixsterz.com) of OpenAI o3. As of December 21, 2024, this model is not available for public use. According to OpenAI, they are checking o3 and  [disgaeawiki.info](https://disgaeawiki.info/index.php/User:ClayGertrude97) o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the opportunity to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecoms providers O2. [215]
 <br>Deep research<br>
 <br>Deep research is an [agent established](http://24insite.com) by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out comprehensive web browsing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120]
 <br>Image category<br>
 <br>CLIP<br>
 <br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to analyze the [semantic similarity](https://equijob.de) in between text and images. It can especially be used for image category. [217]
 <br>Text-to-image<br>
 <br>DALL-E<br>
 <br>Revealed in 2021, DALL-E is a Transformer model that creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can develop pictures of sensible items ("a stained-glass window with a picture of a blue strawberry") in addition to items that do not exist in truth ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.<br>
 <br>DALL-E 2<br>
 <br>In April 2022, OpenAI announced DALL-E 2, an updated version of the model with more sensible results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a [brand-new](http://1.15.187.67) basic system for transforming a text description into a 3-dimensional design. [220]
 <br>DALL-E 3<br>
 <br>In September 2023, OpenAI announced DALL-E 3, a more effective design much better able to generate images from complex descriptions without manual prompt engineering and render complicated details like hands and text. [221] It was released to the general public as a ChatGPT Plus function in October. [222]
 <br>Text-to-video<br>
 <br>Sora<br>
 <br>Sora is a text-to-video model that can create videos based on brief detailed prompts [223] as well as extend existing videos forwards or [backwards](http://git.tbd.yanzuoguang.com) in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of generated videos is unknown.<br>
 <br>Sora's advancement team named it after the Japanese word for "sky", to signify its "unlimited creative capacity". [223] Sora's technology is an adaptation of the technology behind the [DALL ·](https://code.cypod.me) E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos certified for that purpose, but did not expose the number or the exact sources of the videos. [223]
 <br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it could generate videos as much as one minute long. It likewise shared a technical report highlighting the methods used to train the design,  [genbecle.com](https://www.genbecle.com/index.php?title=Utilisateur:AnnaBoxer61535) and the model's capabilities. [225] It acknowledged a few of its shortcomings, consisting of battles simulating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "remarkable", however kept in mind that they must have been cherry-picked and might not represent Sora's common output. [225]
 <br>Despite uncertainty from some academic leaders following Sora's public demo, significant entertainment-industry figures have revealed substantial interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to generate sensible video from text descriptions, citing its prospective to transform storytelling and material creation. He said that his excitement about [Sora's possibilities](https://git.j.co.ua) was so strong that he had decided to pause plans for expanding his Atlanta-based film studio. [227]
 <br>Speech-to-text<br>
 <br>Whisper<br>
 <br>Released in 2022, Whisper is a general-purpose speech recognition model. [228] It is trained on a large dataset of diverse audio and is also a multi-task design that can perform multilingual speech acknowledgment along with speech translation and language identification. [229]
 <br>Music generation<br>
 <br>MuseNet<br>
 <br> in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a tune produced by MuseNet tends to start fairly however then fall under turmoil the longer it plays. [230] [231] In pop culture, preliminary applications 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]
 <br>Jukebox<br>
 <br>Released in 2020, Jukebox is an open-sourced algorithm to produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and  [oeclub.org](https://oeclub.org/index.php/User:RegenaBarlee3) a snippet of lyrics and outputs tune samples. OpenAI mentioned the tunes "show regional musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes lack "familiar larger musical structures such as choruses that repeat" which "there is a considerable gap" in between Jukebox and human-generated music. The Verge mentioned "It's highly impressive, even if the outcomes sound like mushy variations of tunes that may feel familiar", while Business Insider mentioned "remarkably, a few of the resulting tunes are catchy and sound genuine". [234] [235] [236]
 <br>Interface<br>
 <br>Debate Game<br>
 <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 may help in auditing [AI](http://43.137.50.31) decisions and in developing explainable [AI](https://apps365.jobs). [237] [238]
 <br>Microscope<br>
 <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 developed to analyze the features that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, various variations of Inception, and various versions of CLIP Resnet. [241]
 <br>ChatGPT<br>
 <br>[Launched](http://zeus.thrace-lan.info3000) in November 2022, [ChatGPT](https://udyogseba.com) is an expert system tool developed on top of GPT-3 that offers a conversational interface that permits users to ask concerns in natural language. The system then responds with an answer within seconds.<br>