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 <br>Announced in 2016, Gym is an open-source Python library created to assist in the development of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://vmi456467.contaboserver.net) research study, making released research more easily reproducible [24] [144] while supplying users with a simple interface for engaging with these environments. In 2022, brand-new developments of Gym have been moved to the [library Gymnasium](https://codeincostarica.com). [145] [146]
 <br>Gym Retro<br>
 <br>Released in 2018, Gym Retro is a platform for reinforcement learning (RL) research on video games [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on enhancing representatives to solve single tasks. Gym Retro gives the capability to generalize between video games with similar concepts however different looks.<br>
 <br>RoboSumo<br>
 <br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot representatives at first do not have understanding of how to even stroll, however are provided the objectives of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial learning procedure, the [representatives discover](http://qiriwe.com) how to adapt to altering conditions. When a [representative](http://20.198.113.1673000) is then removed from this virtual environment and placed in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually discovered how to balance in a generalized way. [148] [149] OpenAI's Igor  [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:DianaRosenthal) Mordatch argued that competition between agents could develop an intelligence "arms race" that could increase a representative's capability to function even outside the context of the competition. [148]
 <br>OpenAI 5<br>
 <br>OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that learn to play against human gamers at a high skill level totally through trial-and-error algorithms. Before becoming a group of 5, the very first public demonstration happened at The International 2017,  [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:WBKJosef646) the yearly best championship competition for the game, where Dendi, a professional [Ukrainian](https://moyatcareers.co.ke) 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 learned by playing against itself for 2 weeks of genuine time, and that the knowing software was a step in the instructions of creating software that can manage complex tasks like a surgeon. [152] [153] The system utilizes a type of support knowing, as the bots discover over time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an opponent and taking map goals. [154] [155] [156]
 <br>By June 2018, the capability of the bots broadened to play together as a full team of 5, and they were able to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018,  [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:DaniSchreiber98) OpenAI Five played in two exhibit matches against professional players, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the video game at the time, 2:0 in a live exhibition match in [San Francisco](https://m1bar.com). [163] [164] The bots' last public look came later that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those games. [165]
 <br>OpenAI 5's mechanisms in Dota 2's bot gamer shows the challenges of [AI](https://git.jiewen.run) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually demonstrated using deep reinforcement learning (DRL) representatives to attain superhuman skills in Dota 2 matches. [166]
 <br>Dactyl<br>
 <br>Developed in 2018, Dactyl uses device finding out to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It learns completely in [simulation](https://elsalvador4ktv.com) using the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the item orientation issue by utilizing domain randomization, a simulation method which exposes the student to a range of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having [movement tracking](https://gitea.evo-labs.org) video cameras, also has RGB electronic cameras to enable the robot to control an arbitrary things by seeing it. In 2018, OpenAI revealed that the system had the ability to [control](https://78.47.96.1613000) a cube and an octagonal prism. [168]
 <br>In 2019, OpenAI showed 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 [complicated physics](https://youtoosocialnetwork.com) that is harder to design. OpenAI did this by improving the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of producing gradually more tough environments. ADR differs from manual domain randomization by not needing 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 new [AI](https://git.tedxiong.com) models established by OpenAI" to let developers call on it for "any English language [AI](https://findspkjob.com) task". [170] [171]
 <br>Text generation<br>
 <br>The company has actually popularized 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 model was composed by Alec Radford and his associates, and published in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world understanding and [procedure long-range](http://www.mizmiz.de) reliances by pre-training on a diverse corpus with long stretches of contiguous text.<br>
 <br>GPT-2<br>
 <br>Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched [transformer language](https://cvbankye.com) model and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative versions initially launched to the general public. The complete version of GPT-2 was not right away launched due to concern about potential abuse, consisting of applications for composing fake news. [174] Some professionals revealed uncertainty that GPT-2 postured a substantial threat.<br>
 <br>In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to [discover](https://git.magicvoidpointers.com) "neural fake news". [175] Other researchers, such as Jeremy Howard, alerted of "the innovation to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the total version of the GPT-2 [language](http://mengqin.xyz3000) model. [177] Several sites host interactive presentations of various circumstances of GPT-2 and  [it-viking.ch](http://it-viking.ch/index.php/User:TawannaSancho) other transformer designs. [178] [179] [180]
 <br>GPT-2's authors argue without supervision language models to be general-purpose students, shown by GPT-2 attaining cutting edge precision and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not further trained on any [task-specific input-output](https://warleaks.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 a minimum of 3 [upvotes](http://61.174.243.2815863). It prevents certain concerns encoding vocabulary 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](http://cjma.kr) 3 (GPT-3) is a not being watched transformer language design and the successor to GPT-2. [182] [183] [184] [OpenAI mentioned](https://cello.cnu.ac.kr) that the complete variation of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as couple of as 125 million specifications were also trained). [186]
 <br>OpenAI stated that GPT-3 succeeded at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning between English and Romanian, and in between English and German. [184]
 <br>GPT-3 significantly improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs could be approaching or experiencing the fundamental ability constraints of predictive language models. [187] [Pre-training](https://gitlab.ui.ac.id) GPT-3 needed several thousand petaflop/s-days [b] of compute, 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 instantly launched to the general public for issues of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a two-month free personal beta that began in June 2020. [170] [189]
 <br>On September 23, 2020, GPT-3 was certified specifically to Microsoft. [190] [191]
 <br>Codex<br>
 <br>Announced in mid-2021, Codex is a descendant of GPT-3 that has furthermore been [trained](http://101.34.87.71) on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://8.211.134.249:9000) powering the [code autocompletion](https://www.virfans.com) tool GitHub Copilot. [193] In August 2021, an API was [released](http://xn--9t4b21gtvab0p69c.com) in private beta. [194] According to OpenAI, the model can develop working code in over a lots [programs](https://aipod.app) languages, a lot of successfully in Python. [192]
 <br>Several issues with glitches, design defects and security vulnerabilities were pointed out. [195] [196]
 <br>GitHub Copilot has been accused of releasing copyrighted code, with no author attribution or license. [197]
 <br>OpenAI revealed that they would discontinue assistance for Codex API on March 23, 2023. [198]
 <br>GPT-4<br>
 <br>On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), [efficient](http://flexchar.com) in accepting text or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar test with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, analyze or generate approximately 25,000 words of text, and write code in all major programming languages. [200]
 <br>Observers reported that the iteration of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained some of the problems with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has decreased to expose different technical details and data about GPT-4, such as the accurate 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 advanced [outcomes](https://tikness.com) in voice, multilingual, and vision standards, 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]
 <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 interface. Its API costs $0.15 per million [input tokens](https://socialnetwork.cloudyzx.com) and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially helpful for business, start-ups and designers seeking to automate services with [AI](https://deepsound.goodsoundstream.com) representatives. [208]
 <br>o1<br>
 <br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been developed to take more time to think about their actions, leading to higher precision. These [designs](https://gitea.cronin.one) are particularly efficient in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was changed by o1. [211]
 <br>o3<br>
 <br>On December 20, 2024, OpenAI unveiled o3, the successor of the o1 thinking model. OpenAI also revealed o3-mini, a lighter and much faster variation of OpenAI o3. As of December 21, 2024, this model is not available for public use. According to OpenAI, they are evaluating o3 and 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 avoid confusion with telecommunications companies O2. [215]
 <br>Deep research<br>
 <br>Deep research study is a representative established by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 design to carry out extensive web browsing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools enabled, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [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 examine the semantic similarity between text and images. It can notably be used for image category. [217]
 <br>Text-to-image<br>
 <br>DALL-E<br>
 <br>Revealed in 2021, DALL-E is a Transformer design that produces images from [textual descriptions](https://sajano.com). [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of an unfortunate capybara") and create matching images. It can develop images of sensible objects ("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>
 <br>DALL-E 2<br>
 <br>In April 2022, OpenAI revealed DALL-E 2, an [updated variation](https://jobstoapply.com) of the design with more realistic outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new rudimentary system for converting 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 powerful model better able to generate images from [complex descriptions](https://aaalabourhire.com) without manual [timely engineering](https://161.97.85.50) and render complex details like hands and text. [221] It was launched to the general public as a ChatGPT Plus feature in October. [222]
 <br>Text-to-video<br>
 <br>Sora<br>
 <br>Sora is a text-to-video model that can create videos based upon short detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.<br>
 <br>Sora's advancement group called it after the Japanese word for "sky", to signify its "unlimited imaginative 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 certified for that function, but did not reveal the number or the precise sources of the videos. [223]
 <br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it might generate videos approximately one minute long. It also shared a technical report highlighting the methods utilized to train the design, and the model's capabilities. [225] It acknowledged a few of its imperfections, including struggles [replicating](http://jobshut.org) complex physics. [226] Will Douglas Heaven of the MIT [Technology Review](http://120.77.240.2159701) called the presentation videos "impressive", however noted that they need to have been cherry-picked and might not represent Sora's typical output. [225]
 <br>Despite uncertainty from some academic leaders following Sora's public demo, notable entertainment-industry figures have actually revealed considerable interest in the  potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's capability to generate sensible video from text descriptions, mentioning its prospective to change storytelling and content production. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to pause strategies 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 model. [228] It is trained on a large dataset of varied audio and is also a multi-task model that can carry out multilingual speech acknowledgment along with speech translation and language recognition. [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 designs. According to The Verge, a tune created by MuseNet tends to start fairly however then fall under [turmoil](http://dkjournal.co.kr) the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized as early as 2020 for the web psychological thriller Ben [Drowned](http://115.159.107.1173000) to create music for the [titular character](http://123.249.110.1285555). [232] [233]
 <br>Jukebox<br>
 <br>Released in 2020, Jukebox is an open-sourced algorithm to generate music with vocals. After [training](https://eukariyer.net) on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs song samples. OpenAI stated the songs "show regional musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" which "there is a considerable gap" in between Jukebox and human-generated music. The [Verge stated](https://axionrecruiting.com) "It's technologically excellent, even if the outcomes seem like mushy versions of songs that may feel familiar", while Business Insider mentioned "remarkably, some of the resulting songs are appealing and sound genuine". [234] [235] [236]
 <br>User interfaces<br>
 <br>Debate Game<br>
 <br>In 2018, OpenAI released the Debate Game, which teaches devices to debate toy issues in front of a human judge. The purpose is to research whether such a method may assist in auditing [AI](https://workonit.co) choices and in establishing explainable [AI](https://gogs.macrotellect.com). [237] [238]
 <br>Microscope<br>
 <br>Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and nerve cell of eight neural network models which are frequently studied in interpretability. [240] Microscope was developed to evaluate the functions that form inside these neural networks easily. The models included are AlexNet, VGG-19, different variations of Inception, and different versions of CLIP Resnet. [241]
 <br>ChatGPT<br>
 <br>Launched in November 2022, ChatGPT is an artificial intelligence tool developed on top of GPT-3 that provides a conversational user interface that enables users to ask questions in natural language. The system then responds with an answer within seconds.<br>