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 <br>Announced in 2016, Gym is an open-source Python library designed to facilitate the development of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://tikness.com) research study, making released research study more quickly reproducible [24] [144] while providing users with a simple user interface for communicating with these environments. In 2022,  [genbecle.com](https://www.genbecle.com/index.php?title=Utilisateur:JulieBrower730) brand-new developments of Gym have been transferred to the [library Gymnasium](http://chotaikhoan.me). [145] [146]
 <br>Gym Retro<br>
 <br>Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research on video games [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing agents to solve single tasks. Gym Retro provides the capability to generalize in between games with comparable principles however various appearances.<br>
 <br>RoboSumo<br>
 <br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially do not have knowledge of how to even stroll, however are given the objectives of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the representatives discover how to adapt to [changing conditions](http://gpis.kr). 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, recommending it had learned how to balance in a [generalized](https://amore.is) way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between agents could create an intelligence "arms race" that could increase an agent's ability to work even outside the context of the [competition](https://qdate.ru). [148]
 <br>OpenAI 5<br>
 <br>OpenAI Five is a group of 5 OpenAI-curated bots used in the [competitive five-on-five](https://git.cbcl7.com) computer game Dota 2, that find out to play against [human players](https://rugraf.ru) at a high skill level completely through experimental algorithms. Before ending up being a group of 5, the very first public presentation happened at The International 2017, the yearly best championship competition for the 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 actual time, and that the knowing software was a step in the direction of developing software that can deal with [intricate jobs](https://gitlab.wah.ph) like a surgeon. [152] [153] The system uses a kind of support learning, as the bots find out gradually by playing against themselves hundreds of 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 ability of the bots expanded to play together as a full group of 5, and they had the ability to defeat teams of amateur and semi-professional players. [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 look came later that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games. [165]
 <br>OpenAI 5['s systems](https://fmstaffingsource.com) in Dota 2's bot gamer reveals the challenges of [AI](http://pyfup.com:3000) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has shown using deep reinforcement knowing (DRL) representatives to attain superhuman competence in Dota 2 matches. [166]
 <br>Dactyl<br>
 <br>Developed in 2018, Dactyl uses machine finding out to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It discovers completely in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the object orientation issue by utilizing domain randomization, a simulation approach which exposes the learner to a range of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking cameras, likewise has RGB cameras to permit the robot to manipulate an arbitrary object by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168]
 <br>In 2019, OpenAI showed that Dactyl could solve 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](https://leicestercityfansclub.com) that is harder to design. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a [simulation technique](http://139.9.50.1633000) of creating gradually harder environments. ADR differs from manual domain randomization by not requiring a human to specify randomization ranges. [169]
 <br>API<br>
 <br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://rosaparks-ci.com) designs established by OpenAI" to let developers call on it for "any English language [AI](https://socialnetwork.cloudyzx.com) task". [170] [171]
 <br>Text generation<br>
 <br>The company has promoted generative pretrained transformers (GPT). [172]
 <br>OpenAI's original GPT design ("GPT-1")<br>
 <br>The original paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his colleagues, and released in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative design of language might obtain world knowledge and procedure long-range dependencies 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](https://lovetechconsulting.net) transformer language design and the follower to [OpenAI's initial](https://familytrip.kr) GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only [limited demonstrative](https://smarthr.hk) [variations](https://www.ojohome.listatto.ca) initially launched to the general public. The complete variation of GPT-2 was not immediately released due to issue about potential misuse, including applications for writing phony news. [174] Some specialists revealed uncertainty that GPT-2 postured a substantial hazard.<br>
 <br>In response to GPT-2, the Allen Institute for Artificial Intelligence [responded](https://sso-ingos.ru) with a tool to find "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned of "the technology to totally 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 launched the total version of the GPT-2 language design. [177] Several sites 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 by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not additional trained on any task-specific input-output examples).<br>
 <br>The corpus it was trained on, called WebText, contains a little 40 [gigabytes](http://www.xn--739an41crlc.kr) of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents certain issues encoding vocabulary 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]
 <br>GPT-3<br>
 <br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a without supervision transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full 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 few as 125 million specifications were also trained). [186]
 <br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" tasks and could [generalize](https://nycu.linebot.testing.jp.ngrok.io) the function of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184]
 <br>GPT-3 considerably improved benchmark results over GPT-2. OpenAI warned that such scaling-up of [language designs](https://git.spitkov.hu) might be approaching or coming across the basic ability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for  [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:RusselEdler299) the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately released to the public for issues of possible abuse, although OpenAI prepared to enable gain access to through a paid cloud API after a two-month totally free personal beta that began 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://gitlab-mirror.scale.sc) [powering](https://linked.aub.edu.lb) 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 programs languages, the majority of effectively in Python. [192]
 <br>Several concerns with glitches, style defects and security vulnerabilities were pointed out. [195] [196]
 <br>GitHub Copilot has been accused of releasing copyrighted code, without any author attribution or license. [197]
 <br>OpenAI announced that they would [cease support](https://git.purplepanda.cc) 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 in accepting text or image inputs. [199] They revealed that the upgraded innovation passed a simulated law school bar exam 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, examine or produce approximately 25,000 words of text, and write code in all significant shows languages. [200]
 <br>Observers reported that the version of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is also [capable](http://www.hanmacsamsung.com) of taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose numerous technical details and data about GPT-4, such as the exact size of the model. [203]
 <br>GPT-4o<br>
 <br>On May 13, 2024, OpenAI revealed and launched GPT-4o, which can [process](https://pittsburghtribune.org) and create text, images and audio. [204] GPT-4o attained state-of-the-art lead to voice, multilingual, and vision benchmarks, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207]
 <br>On July 18, 2024, OpenAI launched 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 anticipates it to be particularly beneficial for business, startups and designers seeking to automate services with [AI](https://loveyou.az) agents. [208]
 <br>o1<br>
 <br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been designed to take more time to think of their responses, causing higher accuracy. These designs are especially reliable in science, coding, and thinking tasks, and  [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:ReubenQid343925) were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was replaced by o1. [211]
 <br>o3<br>
 <br>On December 20, 2024, OpenAI unveiled o3, the follower of the o1 thinking model. OpenAI likewise revealed o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this design is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and [security scientists](http://zaxx.co.jp) had the chance to obtain early access to these models. [214] The design is called o3 instead of o2 to prevent confusion with telecoms providers O2. [215]
 <br>Deep research<br>
 <br>Deep research study is an agent developed 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 thirty minutes. [216] With browsing and Python tools enabled, it [reached](https://gitlab.companywe.co.kr) a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120]
 <br>Image classification<br>
 <br>CLIP<br>
 <br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the semantic similarity in between text and images. It can especially be utilized for image category. [217]
 <br>Text-to-image<br>
 <br>DALL-E<br>
 <br>Revealed in 2021, DALL-E is a Transformer design that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to translate natural [language](http://dev.onstyler.net30300) inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and [generate matching](https://tokemonkey.com) images. It can create [pictures](http://gitlab.zbqdy666.com) of [practical items](https://pakkjob.com) ("a stained-glass window with an image of a blue strawberry") along with items 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 upgraded version of the design with more practical results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a new rudimentary system for [converting](https://wamc1950.com) 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 much better able to produce images from complex descriptions without manual prompt engineering and render complex details like hands and text. [221] It was released 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 design that can generate videos based upon brief detailed triggers [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with resolution up to 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", to symbolize its "limitless innovative potential". [223] [Sora's innovation](http://121.36.37.7015501) is an adjustment of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos licensed for that purpose, however 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](https://bphomesteading.com) that it could create videos approximately one minute long. It likewise shared a technical report highlighting the approaches used to train the design, and the model's capabilities. [225] It  some of its imperfections, consisting of battles mimicing complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", but noted that they should have been [cherry-picked](http://aat.or.tz) and might not represent Sora's typical output. [225]
 <br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, notable entertainment-industry figures have shown substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his [astonishment](http://test.9e-chain.com) at the innovation's ability to create [practical](http://47.97.6.98081) video from text descriptions, citing its prospective to change storytelling and content [production](http://git.chaowebserver.com). He said that his excitement about Sora's possibilities was so strong that he had actually decided to stop briefly prepare for broadening his Atlanta-based film studio. [227]
 <br>Speech-to-text<br>
 <br>Whisper<br>
 <br>Released in 2022, Whisper is a general-purpose speech acknowledgment design. [228] It is trained on a large dataset of diverse audio and is likewise a [multi-task](https://skillnaukri.com) design that can perform multilingual speech recognition as well as 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](http://47.110.52.1323000) musical notes in MIDI music files. It can produce tunes with 10 [instruments](http://gogs.efunbox.cn) in 15 designs. According to The Verge, a song created by MuseNet tends to start fairly but then fall under chaos the longer it plays. [230] [231] In popular culture, [preliminary applications](http://187.216.152.1519999) of this tool were used as early as 2020 for the internet psychological thriller Ben Drowned to develop music for the [titular character](https://pinecorp.com). [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 category, artist, and a bit of lyrics and outputs tune samples. OpenAI stated the tunes "show local musical coherence [and] follow standard chord patterns" however acknowledged that the songs do not have "familiar bigger musical structures such as choruses that repeat" which "there is a significant space" in between Jukebox and human-generated music. The Verge specified "It's highly remarkable, even if the results sound like mushy versions of songs that may feel familiar", while Business Insider stated "surprisingly, some of the resulting tunes are catchy and sound legitimate". [234] [235] [236]
 <br>User user interfaces<br>
 <br>Debate Game<br>
 <br>In 2018, OpenAI launched the Debate Game, which teaches makers to [dispute toy](https://www.assistantcareer.com) issues in front of a human judge. The function is to research whether such a technique may assist in auditing [AI](http://042.ne.jp) decisions and in developing explainable [AI](https://inktal.com). [237] [238]
 <br>Microscope<br>
 <br>Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and neuron of 8 neural network models which are often studied in interpretability. [240] Microscope was developed to analyze the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, different variations of Inception, and various versions of CLIP Resnet. [241]
 <br>ChatGPT<br>
 <br>Launched in November 2022, ChatGPT is a synthetic intelligence tool built 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>