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 <br>Announced in 2016, Gym is an open-source Python library created to facilitate the advancement of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](https://essencialponto.com.br) research study, making published research more quickly reproducible [24] [144] while providing users with a simple user interface for engaging with these environments. In 2022, brand-new advancements of Gym have actually been relocated to the library Gymnasium. [145] [146]
 <br>Gym Retro<br>
 <br>Released in 2018, Gym Retro is a platform for reinforcement learning (RL) research on video games [147] using RL algorithms and study generalization. Prior RL research focused mainly on enhancing agents to [resolve single](http://www.grainfather.com.au) tasks. Gym Retro gives the capability to generalize in between video games with similar concepts however different appearances.<br>
 <br>RoboSumo<br>
 <br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents initially lack knowledge of how to even stroll, however are given the objectives of discovering to move and to press the opposing agent out of the ring. [148] Through this adversarial learning process, the representatives learn how to adapt to altering conditions. When an agent is then eliminated from this virtual environment and positioned in a brand-new virtual environment with high winds, the representative braces to remain upright, recommending it had actually learned how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives could create an intelligence "arms race" that might increase an agent's ability to function even outside the context of the competition. [148]
 <br>OpenAI 5<br>
 <br>OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that learn to play against human players at a high ability level entirely through experimental algorithms. Before ending up being a group of 5, the very first public presentation took place at The International 2017, the yearly best championship tournament for the video game, where Dendi, a professional 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 found out by playing against itself for two weeks of actual time, and that the knowing software application was a step in the direction of creating software application that can deal with complex tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of reinforcement knowing, as the bots find out gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an  and taking map objectives. [154] [155] [156]
 <br>By June 2018, the ability of the bots broadened to play together as a full group of 5, and they were able to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against professional gamers, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG,  [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:KatrinaPolding1) the reigning world [champions](https://git.lain.church) of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public appearance 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](https://code.estradiol.cloud) in Dota 2's bot player reveals the challenges of [AI](http://thinking.zicp.io:3000) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has shown making use of deep support learning (DRL) representatives to attain superhuman skills 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 robotic hand, to manipulate physical things. [167] It learns completely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the things orientation issue by utilizing domain randomization, a simulation technique which exposes the student to a range of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having [movement tracking](https://tnrecruit.com) cams, likewise has RGB video cameras to permit the robotic to manipulate an arbitrary things by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168]
 <br>In 2019, OpenAI showed that Dactyl could fix a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to model. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic [Domain Randomization](https://gitlab.lizhiyuedong.com) (ADR), a simulation method of generating gradually harder environments. ADR varies from manual [domain randomization](https://sea-crew.ru) by not needing a human to specify randomization ranges. [169]
 <br>API<br>
 <br>In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://gitlab.damage.run) models established by OpenAI" to let [developers](http://gitlab.marcosurrey.de) call on it for "any English language [AI](https://mypungi.com) task". [170] [171]
 <br>Text generation<br>
 <br>The business has actually popularized generative pretrained transformers (GPT). [172]
 <br>OpenAI's original GPT model ("GPT-1")<br>
 <br>The initial paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his coworkers, and released in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world understanding and process long-range dependences 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://www.fionapremium.com) design and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative variations at first [launched](https://ruraltv.in) to the general public. The complete variation of GPT-2 was not right away launched due to issue about prospective abuse, including applications for composing phony news. [174] Some specialists [expressed uncertainty](https://crossdark.net) that GPT-2 presented a substantial threat.<br>
 <br>In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to spot "neural phony news". [175] Other researchers, such as Jeremy Howard, alerted of "the innovation to totally 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 variation of the GPT-2 language model. [177] Several websites host interactive demonstrations of different instances of GPT-2 and other [transformer models](https://smartcampus-seskoal.id). [178] [179] [180]
 <br>GPT-2's authors argue without supervision language designs to be general-purpose students, shown by GPT-2 attaining cutting edge precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not [additional trained](https://git.cacpaper.com) on any task-specific input-output examples).<br>
 <br>The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents certain concerns encoding vocabulary with word tokens by using 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 not being watched transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as couple of as 125 million parameters were likewise trained). [186]
 <br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the function 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 between English and German. [184]
 <br>GPT-3 considerably improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or encountering the essential ability constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for 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 allow gain access to through a [paid cloud](https://wiki.monnaie-libre.fr) API after a two-month complimentary private 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](http://bryggeriklubben.se) powering the code autocompletion [tool GitHub](https://hcp.com.gt) Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the model can produce working code in over a dozen programs languages, many effectively in Python. [192]
 <br>Several concerns with glitches, design defects and security vulnerabilities were pointed out. [195] [196]
 <br>GitHub Copilot has actually been implicated of giving off copyrighted code, with no author attribution or license. [197]
 <br>OpenAI revealed that they would terminate 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](https://git.hichinatravel.com) 4 (GPT-4), capable of accepting text or image inputs. [199] They revealed 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 read, evaluate or produce approximately 25,000 words of text, and write code in all significant shows languages. [200]
 <br>Observers reported that the model of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 [retained](http://carpediem.so30000) some of the issues with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has decreased to expose numerous technical details and stats 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 state-of-the-art [outcomes](https://code.oriolgomez.com) in voice, multilingual, and vision standards, [setting brand-new](https://sosmed.almarifah.id) 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 replacing GPT-3.5 Turbo on the ChatGPT user interface. Its API costs $0.15 per million [input tokens](http://xn--9t4b21gtvab0p69c.com) and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially useful for enterprises, start-ups and [designers](https://www.medexmd.com) looking for to automate services with [AI](https://gitea.bone6.com) agents. [208]
 <br>o1<br>
 <br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models,  [larsaluarna.se](http://www.larsaluarna.se/index.php/User:AlineCox0079049) which have actually been created to take more time to consider their reactions, causing greater accuracy. These designs are especially efficient in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was replaced by o1. [211]
 <br>o3<br>
 <br>On December 20, 2024, OpenAI revealed o3, the follower of the o1 reasoning design. OpenAI likewise revealed 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 evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and [security researchers](https://app.joy-match.com) had the opportunity to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecoms services service provider O2. [215]
 <br>Deep research study<br>
 <br>Deep research study is a representative developed by OpenAI, [revealed](https://volunteering.ishayoga.eu) on February 2, 2025. It leverages the abilities of OpenAI's o3 model to carry out substantial web browsing, data analysis, and synthesis, delivering 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](https://git.gday.express). [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](http://git.mutouyun.com3005) in between text and images. It can significantly be used for image classification. [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 utilizes a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can create pictures of reasonable things ("a stained-glass window with an image of a blue strawberry") along with [objects](https://nextcode.store) that do not exist in [reality](http://161.97.176.30) ("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 of the design with more sensible results. [219] In December 2022, OpenAI released on GitHub software application for Point-E,  [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:JerriRabinovitch) a [brand-new fundamental](http://124.16.139.223000) system for [converting](https://git.partners.run) a text description into a 3[-dimensional](http://www.gbape.com) model. [220]
 <br>DALL-E 3<br>
 <br>In September 2023, OpenAI announced DALL-E 3, a more powerful design better able to produce images from intricate descriptions without manual prompt 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 create videos based upon short detailed prompts [223] along with extend existing videos forwards or backwards in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of generated videos is unknown.<br>
 <br>Sora's advancement team called it after the Japanese word for "sky", to represent its "endless imaginative potential". [223] Sora's innovation is an adjustment of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos licensed for that purpose, however did not expose the number or the specific sources of the videos. [223]
 <br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, stating that it could generate videos up to one minute long. It likewise shared a technical report highlighting the approaches utilized to train the model, and the model's capabilities. [225] It acknowledged some of its drawbacks, including battles simulating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "excellent", but kept in mind 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, noteworthy entertainment-industry figures have revealed considerable interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the innovation's ability to create sensible video from text descriptions, mentioning its possible to reinvent storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had [decided](https://tenacrebooks.com) to pause prepare for expanding his Atlanta-based movie 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](https://croart.net) on a large dataset of varied audio and is also a multi-task model that can carry out multilingual speech acknowledgment 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 musical notes in MIDI music files. It can create songs with 10 instruments in 15 styles. According to The Verge, a song produced by [MuseNet](https://git.karma-riuk.com) tends to begin fairly however then fall under mayhem the longer it plays. [230] [231] In popular culture, initial applications of this tool were used as early as 2020 for the web psychological 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 create music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs song samples. OpenAI stated the songs "show regional musical coherence [and] follow traditional chord patterns" but acknowledged that the songs lack "familiar bigger musical structures such as choruses that repeat" and that "there is a considerable space" in between Jukebox and human-generated music. The Verge mentioned "It's technologically outstanding, even if the results sound like mushy versions of songs that may feel familiar", while Business Insider specified "surprisingly, some of the resulting tunes are appealing and sound legitimate". [234] [235] [236]
 <br>User user interfaces<br>
 <br>Debate Game<br>
 <br>In 2018, OpenAI released the Debate Game, which teaches machines to discuss toy issues in front of a human judge. The function is to research whether such an approach may assist in [auditing](https://bewerbermaschine.de) [AI](http://82.157.77.120:3000) decisions and in developing explainable [AI](https://canworkers.ca). [237] [238]
 <br>Microscope<br>
 <br>Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of 8 neural network models which are typically studied in interpretability. [240] Microscope was created to examine the functions that form inside these neural networks quickly. The models included are AlexNet, VGG-19, various variations of Inception, and different variations of [CLIP Resnet](https://gitea.thisbot.ru). [241]
 <br>ChatGPT<br>
 <br>Launched in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that provides a conversational interface that permits users to ask questions in natural language. The system then responds with an answer within seconds.<br>