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 <br>Announced in 2016, Gym is an open-source Python library developed to assist in the development of support learning algorithms. It aimed to standardize how environments are specified in [AI](http://git.qhdsx.com) research study, making released research study more easily reproducible [24] [144] while supplying users with an easy interface for engaging with these environments. In 2022, brand-new advancements of Gym have been relocated to the library Gymnasium. [145] [146]
 <br>Gym Retro<br>
 <br>[Released](https://just-entry.com) in 2018, Gym Retro is a platform for [reinforcement knowing](http://47.76.141.283000) (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on enhancing representatives to resolve single tasks. Gym Retro offers the ability to generalize in between games with comparable principles however various looks.<br>
 <br>RoboSumo<br>
 <br>[Released](https://git.chocolatinie.fr) in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially do not have knowledge of how to even stroll, however are given the goals of [learning](https://quierochance.com) to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing process, the [agents discover](https://www.eruptz.com) how to adapt to altering conditions. When an agent is then removed from this virtual environment and positioned in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives might develop an intelligence "arms race" that might [increase](https://24cyber.ru) an agent's capability to function even outside the context of the competition. [148]
 <br>OpenAI 5<br>
 <br>OpenAI Five is a group of 5 OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that find out to play against human players at a high ability level entirely through trial-and-error algorithms. Before ending up being a team of 5, the first public presentation took place at The [International](http://www.my.vw.ru) 2017, the yearly best champion competition for the video game, where Dendi, a professional Ukrainian player, 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 two weeks of real time, which the learning software was a step in the direction of producing software that can deal with complex jobs like a cosmetic surgeon. [152] [153] The system utilizes a form of reinforcement learning, as the bots find out with time by playing against themselves hundreds of times a day for months,  [pediascape.science](https://pediascape.science/wiki/User:PansyCarlin0) and are rewarded for actions such as eliminating an enemy and taking map objectives. [154] [155] [156]
 <br>By June 2018, the ability of the bots broadened to play together as a complete group of 5, and they had the ability to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The [International](https://event.genie-go.com) 2018, OpenAI Five played in two exhibition matches against expert gamers, but ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public appearance came later on that month, where they played in 42,729 overall video games in a four-day open online competition, winning 99.4% of those video games. [165]
 <br>OpenAI 5's systems in Dota 2's bot gamer shows the difficulties of [AI](http://113.177.27.200:2033) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated making use of deep reinforcement knowing (DRL) agents to [attain superhuman](https://agalliances.com) proficiency in Dota 2 matches. [166]
 <br>Dactyl<br>
 <br>Developed in 2018, Dactyl utilizes machine learning to train a Shadow Hand, a human-like robot hand, to manipulate physical objects. [167] It learns completely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation problem by utilizing domain randomization, a simulation approach which exposes the student to a range of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having movement tracking electronic cameras, also has RGB electronic cameras to allow the robot to manipulate an approximate object by seeing it. In 2018, OpenAI revealed that the system had the ability to manipulate a cube and an [octagonal prism](https://kollega.by). [168]
 <br>In 2019, OpenAI showed that Dactyl could resolve a Rubik's Cube. The robot had the [ability](https://www.findinall.com) to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce intricate [physics](https://quicklancer.bylancer.com) that is harder to model. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating gradually harder environments. ADR varies from manual domain randomization by not requiring a human to define randomization ranges. [169]
 <br>API<br>
 <br>In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](http://git.rabbittec.com) models developed by OpenAI" to let designers call on it for "any English language [AI](http://bingbinghome.top:3001) job". [170] [171]
 <br>Text generation<br>
 <br>The company has promoted generative pretrained transformers (GPT). [172]
 <br>OpenAI's initial GPT model ("GPT-1")<br>
 <br>The initial paper on generative pre-training of a transformer-based language design was written by Alec Radford and his associates, and published in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative design of language might obtain world understanding and process long-range reliances by pre-training on a diverse corpus with long stretches of adjoining text.<br>
 <br>GPT-2<br>
 <br>Generative Pre-trained Transformer 2 ("GPT-2") is a without supervision transformer [language](http://43.139.182.871111) model and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative versions initially launched to the general public. The full variation of GPT-2 was not immediately launched due to concern about prospective abuse, including applications for writing fake news. [174] Some specialists expressed uncertainty that GPT-2 positioned a considerable danger.<br>
 <br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to find "neural phony 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 muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the complete version of the GPT-2 language design. [177] Several sites host [interactive](https://git.io8.dev) demonstrations of various instances of GPT-2 and other transformer models. [178] [179] [180]
 <br>GPT-2's authors argue without supervision language designs to be general-purpose learners, highlighted by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not further trained on any [task-specific input-output](https://git.guildofwriters.org) examples).<br>
 <br>The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit [submissions](https://demo.shoudyhosting.com) with at least 3 upvotes. It prevents certain problems encoding vocabulary with word tokens by using byte pair encoding. This permits representing any string of characters by encoding both [specific characters](https://inamoro.com.br) and [multiple-character tokens](http://47.122.66.12910300). [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 follower to GPT-2. [182] [183] [184] OpenAI stated that the complete [variation](http://82.223.37.137) of GPT-3 contained 175 billion criteria, [184] 2 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 parameters were likewise trained). [186]
 <br>OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" tasks and could generalize the function of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning in between English and Romanian, and in between English and German. [184]
 <br>GPT-3 significantly enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the essential ability constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of compute, [compared](http://39.108.86.523000) to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly launched to the general public for concerns of possible abuse, although OpenAI prepared to allow [gain access](https://901radio.com) to through a paid cloud API after a two-month complimentary private beta that started in June 2020. [170] [189]
 <br>On September 23, 2020, GPT-3 was licensed exclusively to Microsoft. [190] [191]
 <br>Codex<br>
 <br>Announced in mid-2021, Codex is a descendant of GPT-3 that has furthermore been  on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.referall.us) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the model can create working code in over a dozen programming languages, the [majority](http://81.68.246.1736680) of successfully in Python. [192]
 <br>Several concerns with problems, design defects and security vulnerabilities were cited. [195] [196]
 <br>GitHub Copilot has actually been accused of releasing copyrighted code, without any author [attribution](http://101.35.184.1553000) or license. [197]
 <br>OpenAI announced that they would cease support for Codex API on March 23, 2023. [198]
 <br>GPT-4<br>
 <br>On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar examination with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, examine or create approximately 25,000 words of text, and compose code in all significant shows languages. [200]
 <br>Observers reported that the iteration of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caution that GPT-4 [retained](http://git.superiot.net) some of the issues with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has [decreased](https://gitea.adminakademia.pl) to reveal various technical details and data about GPT-4, such as the accurate size of the design. [203]
 <br>GPT-4o<br>
 <br>On May 13, 2024, OpenAI announced and  [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2857223) launched GPT-4o, which can [process](https://lifeinsuranceacademy.org) and generate text, images and audio. [204] GPT-4o attained modern results in voice, multilingual,  [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:FloyBoothman940) and vision criteria, setting new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) benchmark compared to 86.5% by GPT-4. [207]
 <br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller version of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI expects it to be especially useful for enterprises, [start-ups](http://charmjoeun.com) and developers looking for to automate services with [AI](http://git.sanshuiqing.cn) representatives. [208]
 <br>o1<br>
 <br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have actually been designed to take more time to consider their actions, causing greater accuracy. These models are particularly effective in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was replaced by o1. [211]
 <br>o3<br>
 <br>On December 20, 2024, OpenAI unveiled o3, the successor of the o1 [thinking design](https://mp3talpykla.com). OpenAI likewise unveiled o3-mini, a lighter and faster variation of OpenAI o3. As of December 21, 2024, this model is not available for public usage. According to OpenAI, they are [checking](https://spreek.me) 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 prevent confusion with telecommunications providers O2. [215]
 <br>Deep research<br>
 <br>Deep research is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out extensive web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty 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]
 <br>Image category<br>
 <br>CLIP<br>
 <br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to evaluate the semantic similarity in between text and images. It can especially be used for  [wakewiki.de](https://www.wakewiki.de/index.php?title=Benutzer:DarciDexter026) image classification. [217]
 <br>Text-to-image<br>
 <br>DALL-E<br>
 <br>Revealed in 2021, DALL-E is a Transformer design that [produces](https://git.kicker.dev) images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather purse formed like a pentagon" or "an isometric view of an unfortunate capybara") and generate matching images. It can create images of reasonable things ("a stained-glass window with a picture of a blue strawberry") along with objects that do not exist in truth ("a cube with the texture of a porcupine"). As of 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 design with more practical results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new primary system for  [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:ScarlettMorris) transforming a text description into a 3-dimensional design. [220]
 <br>DALL-E 3<br>
 <br>In September 2023, OpenAI revealed DALL-E 3, a more powerful model better able to produce images from complex descriptions without manual timely engineering and render intricate 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 design that can produce videos based upon short detailed triggers [223] in addition to extend existing videos [forwards](https://taar.me) or backwards in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of created videos is unknown.<br>
 <br>Sora's development group called it after the Japanese word for "sky",  [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1092690) to symbolize its "limitless innovative capacity". [223] Sora's technology is an adjustment of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos as well as copyrighted videos accredited for that purpose, but did not reveal the number or the [precise sources](http://163.66.95.1883001) of the videos. [223]
 <br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it could generate videos up to one minute long. It likewise shared a technical report highlighting the approaches utilized to train the design, and the model's capabilities. [225] It acknowledged some of its shortcomings, including struggles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but noted that they must have been cherry-picked and may not represent Sora's typical output. [225]
 <br>Despite uncertainty from some academic leaders following Sora's public demonstration, [notable entertainment-industry](https://www.opentx.cz) [figures](http://120.79.218.1683000) have revealed significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to [generate](https://jobsdirect.lk) sensible video from text descriptions, citing its possible to revolutionize storytelling and content creation. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to stop briefly plans for broadening his Atlanta-based movie studio. [227]
 <br>Speech-to-text<br>
 <br>Whisper<br>
 <br>Released in 2022, Whisper is a general-purpose speech recognition design. [228] It is trained on a big dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition in addition to speech translation and language identification. [229]
 <br>Music generation<br>
 <br>MuseNet<br>
 <br>Released in 2019, MuseNet is a deep neural net trained to forecast subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 styles. According to The Verge, a song produced by MuseNet tends to start fairly but then fall into mayhem the longer it plays. [230] [231] In popular culture, initial applications of this tool were used as early as 2020 for  [disgaeawiki.info](https://disgaeawiki.info/index.php/User:Iola72K6038620) the internet psychological thriller Ben [Drowned](https://www.genbecle.com) to develop music for the titular character. [232] [233]
 <br>Jukebox<br>
 <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 snippet of lyrics and outputs song samples. OpenAI mentioned the tunes "show regional musical coherence [and] follow standard chord patterns" however acknowledged that the tunes lack "familiar larger musical structures such as choruses that repeat" which "there is a significant gap" in between Jukebox and human-generated music. The Verge specified "It's highly remarkable, even if the outcomes seem like mushy variations of tunes that may feel familiar", while Business Insider specified "surprisingly, a few of the resulting tunes are appealing and sound genuine". [234] [235] [236]
 <br>User interfaces<br>
 <br>Debate Game<br>
 <br>In 2018, OpenAI introduced the Debate Game, which teaches machines to debate toy issues in front of a human judge. The purpose is to research whether such an approach might assist in auditing [AI](https://sosmed.almarifah.id) [decisions](https://www.imf1fan.com) and in establishing explainable [AI](https://selfyclub.com). [237] [238]
 <br>Microscope<br>
 <br>Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and nerve cell of eight neural network designs which are often studied in interpretability. [240] Microscope was developed to examine the features that form inside these neural networks easily. The designs included are AlexNet, VGG-19, various variations of Inception, and various variations of CLIP Resnet. [241]
 <br>ChatGPT<br>
 <br>[Launched](https://localglobal.in) in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that offers a conversational interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.<br>