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 <br>Announced in 2016, Gym is an open-source Python library developed to assist in the development of reinforcement learning algorithms. It aimed to standardize how environments are specified in [AI](http://pyfup.com:3000) research study, making published research more quickly reproducible [24] [144] while offering users with an easy interface for communicating with these environments. In 2022, new advancements of Gym have been transferred to the library Gymnasium. [145] [146]
 <br>Gym Retro<br>
 <br>Released in 2018, Gym Retro is a platform for support knowing (RL) research study on computer game [147] using RL algorithms and research study generalization. Prior RL research focused mainly on optimizing representatives to solve single jobs. Gym Retro gives the ability to generalize 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 robot representatives at first lack knowledge of how to even stroll, however are given the goals of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing process, the representatives learn how to adjust to altering conditions. When a representative is then removed from this virtual environment and placed in a brand-new virtual environment with high winds, the [agent braces](http://192.241.211.111) to remain upright, suggesting it had found out how to balance in a generalized method. [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 operate 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 computer 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 first public demonstration took place at The International 2017, the annual best champion competition 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](http://202.90.141.173000) that the bot had discovered by playing against itself for two weeks of actual time, and that the knowing software was an action in the direction of developing software application that can deal with complicated tasks like a surgeon. [152] [153] The system uses a kind of reinforcement knowing,  [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:StefanValentino) as the bots find out over time by playing against themselves numerous times a day for  [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2684771) months, and are rewarded for actions such as killing an enemy and taking map goals. [154] [155] [156]
 <br>By June 2018, the capability of the bots expanded to play together as a full group of 5, and they were able to [beat teams](https://welcometohaiti.com) of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against professional players, but wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champions of the 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 competitors, winning 99.4% of those video games. [165]
 <br>OpenAI 5's mechanisms in Dota 2's bot gamer shows the difficulties of [AI](http://193.105.6.167:3000) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has shown the use of deep reinforcement learning (DRL) representatives to attain superhuman skills in Dota 2 matches. [166]
 <br>Dactyl<br>
 <br>Developed in 2018, Dactyl utilizes device finding out to train a Shadow Hand, a human-like robot hand, to control physical things. [167] It finds out completely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation issue by [utilizing](https://www.careermakingjobs.com) domain randomization, a simulation method which exposes the student to a variety of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having motion tracking electronic cameras, also has RGB cameras to allow the robotic to [manipulate](https://git.i2edu.net) an approximate things 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 was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce intricate physics that is harder to design. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of creating [progressively](https://www.florevit.com) more hard environments. ADR differs from manual domain randomization 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 brand-new [AI](https://tv.sparktv.net) models established by OpenAI" to let designers contact it for "any English language [AI](http://git.jaxc.cn) job". [170] [171]
 <br>Text generation<br>
 <br>The business has actually promoted generative pretrained transformers (GPT). [172]
 <br>[OpenAI's original](https://git.biosens.rs) 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](http://124.223.222.613000) on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world knowledge and procedure long-range dependences by pre-training on a diverse corpus with long stretches of contiguous text.<br>
 <br>GPT-2<br>
 <br> Transformer 2 ("GPT-2") is a not being watched transformer language model and the successor to OpenAI's original [GPT design](https://www.dynamicjobs.eu) ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative variations initially launched to the public. The full version of GPT-2 was not instantly released due to issue about potential misuse, including applications for writing phony news. [174] Some experts expressed uncertainty that GPT-2 positioned a significant threat.<br>
 <br>In action to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to discover "neural phony news". [175] Other researchers, such as Jeremy Howard, warned of "the innovation to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the total version of the GPT-2 language model. [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 designs to be general-purpose students, illustrated by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not [additional trained](http://124.221.76.2813000) on any [task-specific](https://www.dadam21.co.kr) [input-output](http://140.125.21.658418) 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 avoids certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This allows 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,  [surgiteams.com](https://surgiteams.com/index.php/User:RolandoHorniman) 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 version of GPT-3 contained 175 billion criteria, [184] 2 orders of [magnitude larger](https://grailinsurance.co.ke) than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were also trained). [186]
 <br>OpenAI stated that GPT-3 prospered at certain "meta-learning" jobs 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 improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs could be approaching or coming across the essential ability constraints of predictive language designs. [187] Pre-training GPT-3 required a number of thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately launched to the public for issues of possible abuse, although OpenAI planned to permit gain access to through a [paid cloud](https://gofleeks.com) API after a [two-month free](http://43.143.46.763000) private beta that began in June 2020. [170] [189]
 <br>On September 23, 2020, GPT-3 was licensed specifically to Microsoft. [190] [191]
 <br>Codex<br>
 <br>Announced in mid-2021, Codex is a descendant of GPT-3 that has actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://gitea.thuispc.dynu.net) [powering](https://abilliontestimoniesandmore.org) the code autocompletion tool GitHub Copilot. [193] In August 2021,  [raovatonline.org](https://raovatonline.org/author/angelicadre/) an API was released in private beta. [194] According to OpenAI, the model can produce working code in over a dozen shows languages, a lot of [efficiently](http://moyora.today) in Python. [192]
 <br>Several issues with problems, style defects and security [vulnerabilities](https://git.lab.evangoo.de) were mentioned. [195] [196]
 <br>GitHub Copilot has been accused of [releasing copyrighted](http://git.yang800.cn) code, without any author attribution or license. [197]
 <br>OpenAI revealed that they would cease support for Codex API on March 23, 2023. [198]
 <br>GPT-4<br>
 <br>On March 14,  [larsaluarna.se](http://www.larsaluarna.se/index.php/User:Rosalind2029) 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 top 10% of [test takers](http://47.106.228.1133000). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, examine or generate approximately 25,000 words of text, and compose code in all major shows languages. [200]
 <br>[Observers](https://git.muhammadfahri.com) reported that the model of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caution 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 stats about GPT-4, such as the exact size of the model. [203]
 <br>GPT-4o<br>
 <br>On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision standards, setting new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask [Language Understanding](https://4stour.com) (MMLU) criteria compared to 86.5% by GPT-4. [207]
 <br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized version of GPT-4o replacing GPT-3.5 Turbo on the [ChatGPT interface](http://62.234.217.1373000). Its [API costs](https://jr.coderstrust.global) $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 useful for business, start-ups and designers looking for to automate services with [AI](http://193.30.123.188:3500) representatives. [208]
 <br>o1<br>
 <br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have been developed to take more time to consider their actions, leading to greater accuracy. These designs are particularly efficient in science, coding, and reasoning jobs, 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 revealed o3, the successor of the o1 thinking design. OpenAI likewise revealed o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the opportunity to obtain early access to these designs. [214] The design is called o3 rather than o2 to prevent confusion with telecommunications companies O2. [215]
 <br>Deep research<br>
 <br>Deep research is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform substantial web surfing, data analysis, and synthesis, [providing detailed](http://git.medtap.cn) reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools made it possible for, it reached a precision 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 model that is trained to analyze the semantic similarity between text and  [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:DinaHolcomb495) images. It can especially be [utilized](http://47.76.210.1863000) for  [bio.rogstecnologia.com.br](https://bio.rogstecnologia.com.br/halleybodin) image category. [217]
 <br>Text-to-image<br>
 <br>DALL-E<br>
 <br>Revealed in 2021, DALL-E is a Transformer design that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of a sad capybara") and generate matching images. It can produce pictures of sensible items ("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 revealed DALL-E 2, an updated variation of the model with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new rudimentary system for transforming a text description into a 3[-dimensional design](https://voovixtv.com). [220]
 <br>DALL-E 3<br>
 <br>In September 2023, OpenAI revealed DALL-E 3, a more effective design better able to produce images from complicated descriptions without manual prompt engineering and render complex details like hands and text. [221] It was launched to the 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 generate videos based upon brief detailed prompts [223] in addition to extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of created videos is unidentified.<br>
 <br>Sora's advancement group called it after the Japanese word for "sky", to signify its "limitless innovative potential". [223] Sora's technology is an adaptation of the innovation behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos in addition to [copyrighted](http://47.98.226.2403000) videos licensed for that function, but did not reveal 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, mentioning that it might generate videos approximately one minute long. It also shared a technical report highlighting the techniques used to train the model, and the model's capabilities. [225] It acknowledged a few of its drawbacks, including struggles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", however noted that they must have been cherry-picked and might not represent Sora's common output. [225]
 <br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, notable entertainment-industry figures have shown substantial interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's ability to create practical video from text descriptions, mentioning its potential to reinvent storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had decided to stop briefly prepare 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 acknowledgment design. [228] It is trained on a large dataset of diverse audio and is likewise a multi-task model that can perform multilingual speech acknowledgment in addition to speech translation and language recognition. [229]
 <br>Music generation<br>
 <br>MuseNet<br>
 <br>Released in 2019, [MuseNet](https://gitea.linkensphere.com) is a deep neural net [trained](http://hitbat.co.kr) to forecast subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to begin fairly but then fall under turmoil the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the internet psychological thriller Ben Drowned to develop music for the titular [character](https://bibi-kai.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 [snippet](https://gitee.mmote.ru) of lyrics and outputs song [samples](http://mao2000.com3000). OpenAI specified the tunes "show local musical coherence [and] follow standard chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" which "there is a significant space" between Jukebox and human-generated music. The Verge specified "It's highly impressive, even if the results seem like mushy variations of songs that may feel familiar", while Business Insider mentioned "surprisingly, some of the resulting songs are memorable and sound genuine". [234] [235] [236]
 <br>User interfaces<br>
 <br>Debate Game<br>
 <br>In 2018, OpenAI released the Debate Game, which teaches machines to discuss toy problems in front of a human judge. The function is to research whether such a technique may assist in [auditing](http://47.92.218.2153000) [AI](http://music.afrixis.com) decisions and in establishing explainable [AI](http://git.medtap.cn). [237] [238]
 <br>Microscope<br>
 <br>Released in 2020, Microscope [239] is a [collection](http://yhxcloud.com12213) of [visualizations](http://39.100.139.16) of every substantial layer and neuron of 8 neural network models which are frequently studied in interpretability. [240] Microscope was produced to evaluate the features that form inside these [neural networks](https://ugit.app) quickly. The designs included are AlexNet, VGG-19, different versions of Inception, and various [variations](http://wiki.lexserve.co.ke) 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 offers a conversational user interface that enables users to ask questions in natural language. The system then reacts with an answer within seconds.<br>