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 <br>Announced in 2016, Gym is an  library developed to assist in the advancement of reinforcement learning algorithms. It aimed to standardize how environments are specified in [AI](https://firemuzik.com) research study, making published research study more quickly reproducible [24] [144] while offering users with an easy user interface for [communicating](https://probando.tutvfree.com) with these environments. In 2022, new developments of Gym have been relocated 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 study generalization. Prior RL research study focused mainly on optimizing agents to resolve single tasks. Gym Retro gives the ability to generalize between games with similar principles however different appearances.<br>
 <br>RoboSumo<br>
 <br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially lack understanding of how to even stroll, but are given the objectives of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the [representatives discover](https://hektips.com) how to adjust to changing conditions. When a representative is then gotten rid of from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright,  [links.gtanet.com.br](https://links.gtanet.com.br/zarakda51931) suggesting it had discovered how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between agents might develop an intelligence "arms race" that might [increase](https://git.kairoscope.net) an agent's capability to function even outside the context of the competitors. [148]
 <br>OpenAI 5<br>
 <br>OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that discover to play against human gamers at a high skill level entirely through experimental algorithms. Before becoming a group of 5, the very first public presentation happened at The International 2017, the annual premiere 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 learned by playing against itself for 2 weeks of genuine time, which the learning software application was a step in the direction of creating software that can handle complex jobs like a cosmetic surgeon. [152] [153] The system utilizes a kind of reinforcement knowing, as the bots learn with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an opponent and taking map goals. [154] [155] [156]
 <br>By June 2018, the ability of the bots broadened to play together as a complete group of 5, and they were able to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against professional players, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five [defeated](http://www.engel-und-waisen.de) OG, the ruling world champions of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last [public appearance](https://forum.freeadvice.com) came later on that month, where they played in 42,729 total 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 challenges of [AI](https://www.sexmasters.xyz) [systems](https://fogel-finance.org) in multiplayer online fight arena (MOBA) video games and how OpenAI Five has demonstrated using deep support knowing (DRL) representatives to [attain superhuman](https://burlesquegalaxy.com) skills in Dota 2 matches. [166]
 <br>Dactyl<br>
 <br>Developed in 2018, Dactyl uses machine learning to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It discovers entirely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the object orientation issue by utilizing domain randomization, a simulation technique which exposes the learner to a variety of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking electronic cameras, also has RGB video [cameras](http://worldjob.xsrv.jp) to permit the robot to manipulate an arbitrary item by seeing it. In 2018, OpenAI showed that the system had the ability to manipulate a cube and an octagonal prism. [168]
 <br>In 2019, [OpenAI demonstrated](http://www.heart-hotel.com) that Dactyl might resolve a Rubik's Cube. The robot had the [ability](https://bakery.muf-fin.tech) to solve the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to design. OpenAI did this by improving the robustness of Dactyl to perturbations by [utilizing Automatic](http://git.twopiz.com8888) Domain Randomization (ADR), a simulation approach of generating gradually more hard environments. ADR varies from manual domain randomization by not needing a human to define randomization varieties. [169]
 <br>API<br>
 <br>In June 2020,  [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:KathrinSabella) OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](https://chat.app8station.com) models developed by OpenAI" to let developers call on it for "any English language [AI](http://it-viking.ch) task". [170] [171]
 <br>Text generation<br>
 <br>The company has actually popularized generative pretrained transformers (GPT). [172]
 <br>OpenAI's initial GPT design ("GPT-1")<br>
 <br>The original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his associates, and released in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative model of language could obtain world understanding and procedure long-range 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 without supervision transformer language model and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just minimal demonstrative versions initially released to the general public. The full version of GPT-2 was not right away released due to concern about potential abuse, including applications for writing fake news. [174] Some [specialists](http://git.fast-fun.cn92) revealed uncertainty that GPT-2 presented a considerable risk.<br>
 <br>In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to identify "neural fake 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 muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the total version of the GPT-2 language design. [177] Several websites host interactive demonstrations of various circumstances of GPT-2 and other transformer models. [178] [179] [180]
 <br>GPT-2's authors argue without supervision language models to be general-purpose learners, highlighted by GPT-2 attaining advanced precision and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not further trained on any task-specific input-output examples).<br>
 <br>The corpus it was trained on, called WebText, contains somewhat 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain issues encoding [vocabulary](https://103.1.12.176) with word tokens by utilizing 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 an unsupervised transformer language model and the [successor](http://git.jetplasma-oa.com) to GPT-2. [182] [183] [184] OpenAI mentioned that the full version of GPT-3 contained 175 billion criteria, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as few as 125 million criteria were also trained). [186]
 <br>OpenAI specified 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 gave examples of translation and cross-linguistic transfer learning in between English and Romanian, and in between English and German. [184]
 <br>GPT-3 significantly improved benchmark results over GPT-2. OpenAI warned that such scaling-up of [language designs](https://www.milegajob.com) could be approaching or encountering the basic capability constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of compute, [compared](https://sebagai.com) to 10s of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not right away launched to the public for concerns of possible abuse, although OpenAI prepared 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 licensed solely to [Microsoft](https://78.47.96.1613000). [190] [191]
 <br>Codex<br>
 <br>Announced in mid-2021, Codex is a descendant of GPT-3 that has actually furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://bertlierecruitment.co.za) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can [produce](https://gemma.mysocialuniverse.com) working code in over a lots programming languages, the majority of effectively in Python. [192]
 <br>Several concerns with problems, design defects and security vulnerabilities were cited. [195] [196]
 <br>GitHub Copilot has been accused of emitting copyrighted code, without any author attribution or license. [197]
 <br>OpenAI announced that they would stop 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 revealed that the updated innovation passed a simulated law school bar examination 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 check out, examine or produce approximately 25,000 words of text, and compose code in all major shows languages. [200]
 <br>Observers reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to expose various technical details and data about GPT-4, such as the precise size of the model. [203]
 <br>GPT-4o<br>
 <br>On May 13, 2024, OpenAI announced and released GPT-4o, which can process and [generate](https://xhandler.com) text, images and audio. [204] GPT-4o [attained state-of-the-art](https://learninghub.fulljam.com) lead to voice, multilingual, and vision benchmarks, setting brand-new records in audio speech acknowledgment and [translation](https://ayjmultiservices.com). [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 launched GPT-4o mini, a smaller variation of GPT-4o replacing GPT-3.5 Turbo on the [ChatGPT interface](https://virnal.com). 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 especially helpful for business, start-ups and designers seeking to automate services with [AI](https://gogs.2dz.fi) agents. [208]
 <br>o1<br>
 <br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have actually been developed to take more time to think about their actions, [leading](http://152.136.187.229) to higher accuracy. These designs are particularly effective in science, coding, and thinking tasks, and were made available to ChatGPT Plus and  [pediascape.science](https://pediascape.science/wiki/User:ChandaRidenour) 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 follower of the o1 reasoning design. 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 usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the opportunity to obtain early access to these designs. [214] The model is called o3 rather than o2 to avoid confusion with telecoms providers O2. [215]
 <br>Deep research<br>
 <br>Deep research is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform extensive 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 a precision of 26.6 percent on HLE (Humanity's Last Exam) [standard](https://agora-antikes.gr). [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 resemblance in between text and images. It can significantly 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 [analyze natural](http://8.139.7.16610880) language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images. It can produce pictures of realistic things ("a stained-glass window with an image of a blue strawberry") as well as 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 announced DALL-E 2,  [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2672496) an upgraded variation of the model with more [reasonable outcomes](https://canadasimple.com). [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new fundamental system for converting a text description into a 3[-dimensional](http://sopoong.whost.co.kr) model. [220]
 <br>DALL-E 3<br>
 <br>In September 2023, OpenAI revealed DALL-E 3, a more effective model better able to generate images from complicated descriptions without manual timely engineering and [render intricate](https://bphomesteading.com) [details](http://www.scitqn.cn3000) like hands and text. [221] It was [released](http://107.172.157.443000) to the general public as a [ChatGPT](https://www.wcosmetic.co.kr5012) Plus function in October. [222]
 <br>Text-to-video<br>
 <br>Sora<br>
 <br>Sora is a text-to-video design that can create videos based on short detailed triggers [223] in addition to extend existing videos forwards or backwards in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The maximal length of created videos is [unknown](https://www.oscommerce.com).<br>
 <br>Sora's development group called it after the Japanese word for "sky", to symbolize its "limitless creative capacity". [223] Sora's innovation is an adjustment of the technology behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos licensed for that function, but did not expose the number or the precise sources of the videos. [223]
 <br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, specifying that it could generate videos approximately one minute long. It also shared a technical report highlighting the techniques used to train the design, and the design's abilities. [225] It acknowledged some of its drawbacks, including battles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", however kept in mind that they need to have been cherry-picked and may not represent Sora's common output. [225]
 <br>Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have actually revealed considerable interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry [expressed](https://www.laciotatentreprendre.fr) his awe at the technology's ability to produce practical video from text descriptions, citing its possible to revolutionize storytelling and material creation. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to pause strategies for expanding his Atlanta-based motion picture studio. [227]
 <br>Speech-to-text<br>
 <br>Whisper<br>
 <br>Released in 2022, Whisper is a general-purpose speech acknowledgment model. [228] It is trained on a big [dataset](https://jobsthe24.com) of varied audio and is likewise a multi-task model that can perform multilingual speech acknowledgment as well as speech [translation](https://finance.azberg.ru) and language recognition. [229]
 <br>Music generation<br>
 <br>MuseNet<br>
 <br>Released in 2019, MuseNet is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 designs. According to The Verge, a song created by MuseNet tends to start fairly however then fall into chaos the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used 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 generate 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 mentioned the tunes "show regional musical coherence [and] follow conventional chord patterns" however acknowledged that the songs lack "familiar larger musical structures such as choruses that repeat" and that "there is a significant space" in between [Jukebox](https://krazzykross.com) and human-generated music. The Verge stated "It's technically remarkable, even if the outcomes sound like mushy variations of songs that may feel familiar", while Business Insider stated "remarkably, a few of the resulting tunes are memorable and sound genuine". [234] [235] [236]
 <br>Interface<br>
 <br>Debate Game<br>
 <br>In 2018, [OpenAI released](http://59.57.4.663000) the Debate Game, which teaches machines to discuss toy issues in front of a human judge. The purpose is to research study whether such a technique might help in auditing [AI](https://yourrecruitmentspecialists.co.uk) choices and in establishing explainable [AI](https://hektips.com). [237] [238]
 <br>Microscope<br>
 <br>Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of eight neural network models which are often studied in [interpretability](https://gitea.mrc-europe.com). [240] Microscope was developed to analyze the functions that form inside these neural networks easily. The models included are AlexNet, VGG-19, various variations of Inception, and different versions of CLIP Resnet. [241]
 <br>ChatGPT<br>
 <br>Launched in November 2022, ChatGPT is a synthetic intelligence tool constructed on top of GPT-3 that supplies a conversational interface that enables users to ask concerns in natural language. The system then reacts with an answer within seconds.<br>