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 <br>Announced in 2016, Gym is an open-source Python library created to facilitate the development of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](http://dnd.achoo.jp) research study, making released research more quickly reproducible [24] [144] while offering users with a simple interface for engaging with these environments. In 2022, new advancements 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 knowing (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on [enhancing agents](https://git.prayujt.com) to fix [single tasks](http://git.lai-tech.group8099). Gym Retro provides the capability to generalize between games with comparable concepts but different looks.<br>
 <br>RoboSumo<br>
 <br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first do not have understanding of how to even walk, however are provided the objectives of finding out to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the agents find out how to adjust to changing conditions. When a representative is then eliminated from this virtual environment and put in a new [virtual environment](http://www.cl1024.online) with high winds, the agent braces to remain upright, suggesting it had discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives could produce an intelligence "arms race" that might increase an agent's ability to work even outside the context of the competition. [148]
 <br>OpenAI 5<br>
 <br>OpenAI Five is a group of 5 OpenAI-curated bots [utilized](http://xn--9t4b21gtvab0p69c.com) in the competitive five-on-five video game Dota 2, that discover to play against human gamers at a high ability level entirely through experimental algorithms. Before ending up being a team of 5, the very first public presentation took place at The International 2017, the yearly premiere championship competition for the game, where Dendi, an [expert Ukrainian](http://47.92.159.28) player, lost against a bot in a live one-on-one matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had learned by playing against itself for two weeks of genuine time, and that the knowing software application was an action in the instructions of developing software application that can deal with complex tasks like a surgeon. [152] [153] The system utilizes a kind of support learning, as the bots find out with time 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 groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert gamers, however ended 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 exhibit match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those games. [165]
 <br>OpenAI 5's systems in Dota 2's bot gamer shows the difficulties of [AI](https://dsspace.co.kr) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated using deep support knowing (DRL) representatives to attain superhuman competence in Dota 2 matches. [166]
 <br>Dactyl<br>
 <br>Developed in 2018, Dactyl uses maker discovering to train a Shadow Hand, a human-like robotic hand, to control physical objects. [167] It learns entirely in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation problem by using domain randomization, a simulation technique which exposes the student to a variety of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking electronic cameras, likewise has RGB video cameras to allow the robotic to manipulate an approximate object by seeing it. In 2018, OpenAI revealed that the system had the ability to manipulate a cube and an octagonal prism. [168]
 <br>In 2019, OpenAI [demonstrated](https://lonestartube.com) that Dactyl could resolve a Rubik's Cube. The robotic had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to design. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR),  [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:LindseyWalstab9) a simulation method of generating gradually more tough environments. ADR varies 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://slovenskymedved.sk) models developed by OpenAI" to let [developers contact](http://git.airtlab.com3000) it for "any English language [AI](https://git.googoltech.com) job". [170] [171]
 <br>Text generation<br>
 <br>The company has actually promoted 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](https://abileneguntrader.com) in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world knowledge and process long-range reliances by pre-training on a diverse corpus with long stretches of .<br>
 <br>GPT-2<br>
 <br>Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language model and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative versions initially launched to the public. The complete variation of GPT-2 was not immediately launched due to issue about [potential](https://tube.leadstrium.com) abuse, including applications for [writing phony](https://gitea.oo.co.rs) news. [174] Some experts revealed [uncertainty](https://musixx.smart-und-nett.de) that GPT-2 posed a significant hazard.<br>
 <br>In action to GPT-2, the Allen Institute for Artificial Intelligence [responded](http://47.119.20.138300) with a tool to discover "neural fake news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to completely 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 model. [177] Several websites host [interactive presentations](http://47.108.105.483000) of different circumstances of GPT-2 and other transformer models. [178] [179] [180]
 <br>GPT-2's authors argue unsupervised language designs to be general-purpose learners, shown by GPT-2 attaining cutting edge [accuracy](https://git.googoltech.com) and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not more [trained](http://dev.nextreal.cn) on any task-specific input-output 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. It [prevents](https://surmodels.com) certain issues encoding vocabulary 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 a without supervision transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full variation of GPT-3 contained 175 billion specifications, [184] two orders of magnitude larger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as few as 125 million [specifications](https://event.genie-go.com) were also trained). [186]
 <br>OpenAI stated that GPT-3 prospered at certain "meta-learning" jobs and might generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning between [English](https://hrvatskinogomet.com) and Romanian, and in between [English](http://unired.zz.com.ve) and German. [184]
 <br>GPT-3 drastically enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or experiencing the fundamental capability constraints of predictive language models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately launched to the public for concerns of possible abuse, although OpenAI prepared to [enable gain](http://digitalmaine.net) access to through a [paid cloud](https://squishmallowswiki.com) API after a two-month complimentary private 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 additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://huconnect.org) [powering](https://asteroidsathome.net) the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the design can develop working code in over a lots shows languages, a lot of effectively in Python. [192]
 <br>Several problems with problems, design defects and [security](https://www.yewiki.org) vulnerabilities were cited. [195] [196]
 <br>GitHub Copilot has been accused of emitting copyrighted code, with no author [attribution](https://git.starve.space) 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 revealed the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They revealed that the updated innovation passed a simulated law school bar examination with a score around the top 10% of [test takers](http://124.222.6.973000). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could likewise check out, examine or generate up to 25,000 words of text, and compose code in all significant programming languages. [200]
 <br>Observers reported that the iteration of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal numerous technical details and statistics about GPT-4, such as the accurate size of the model. [203]
 <br>GPT-4o<br>
 <br>On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained advanced [outcomes](http://113.98.201.1408888) in voice, multilingual, and vision criteria, setting brand-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 version of GPT-4o replacing GPT-3.5 Turbo on the [ChatGPT interface](http://47.120.20.1583000). Its API costs $0.15 per million input tokens and $0.60 per million output tokens,  [links.gtanet.com.br](https://links.gtanet.com.br/zarakda51931) 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](https://igita.ir) with [AI](http://163.228.224.105:3000) agents. [208]
 <br>o1<br>
 <br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have been designed to take more time to consider their reactions, resulting in higher precision. These models are particularly efficient in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was changed by o1. [211]
 <br>o3<br>
 <br>On December 20, 2024, OpenAI revealed o3, the follower of the o1 thinking design. OpenAI likewise unveiled o3-mini, a lighter and quicker 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, security and security scientists had the opportunity to obtain early access to these models. [214] The design is called o3 rather than o2 to prevent confusion with telecommunications companies O2. [215]
 <br>Deep research study<br>
 <br>Deep research is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out extensive web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools enabled, 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 design that is trained to analyze the [semantic resemblance](http://testyourcharger.com) in between text and images. It can especially 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 interpret natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can create images of practical things ("a stained-glass window with a picture of a blue strawberry") along with [objects](https://solegeekz.com) 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, an upgraded version of the model with more reasonable outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new rudimentary system for converting a [text description](https://tv.360climatechange.com) into a 3-dimensional design. [220]
 <br>DALL-E 3<br>
 <br>In September 2023, OpenAI announced DALL-E 3, a more effective model better able to produce images from intricate descriptions without manual prompt engineering and [render complex](http://47.113.115.2393000) details like hands and text. [221] It was released to the public as a ChatGPT Plus function in October. [222]
 <br>Text-to-video<br>
 <br>Sora<br>
 <br>Sora is a text-to-video model that can generate videos based on short detailed triggers [223] along with [extend existing](https://51.68.46.170) videos forwards or in reverse in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.<br>
 <br>Sora's advancement team named it after the Japanese word for "sky", to represent its "unlimited imaginative capacity". [223] Sora's technology is an adjustment of the technology behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos licensed for that purpose, but did not reveal 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, stating that it could [generate videos](https://git.andrewnw.xyz) up to one minute long. It also shared a technical report highlighting the techniques used to train the design,  [pipewiki.org](https://pipewiki.org/wiki/index.php/User:FelipaPruett850) and the design's capabilities. [225] It acknowledged some of its shortcomings, consisting of battles mimicing complex physics. [226] Will Douglas Heaven of the MIT [Technology](https://playtube.ann.az) Review called the [presentation](http://101.35.184.1553000) videos "impressive", however kept in mind that they should have been cherry-picked and may not represent Sora's [common output](https://www.armeniapedia.org). [225]
 <br>Despite uncertainty from some academic leaders following Sora's public demonstration, notable entertainment-industry figures have actually shown considerable interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's capability to produce reasonable video from text descriptions, citing its prospective to change storytelling and content development. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to stop briefly 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 acknowledgment design. [228] It is trained on a large dataset of varied audio and is also a multi-task model that can perform 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 predict subsequent [musical notes](https://git.googoltech.com) in MIDI music files. It can create songs with 10 instruments in 15 designs. According to The Verge, a tune generated by MuseNet tends to start fairly however then fall under mayhem 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. [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 mentioned the tunes "show local musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that repeat" which "there is a substantial space" in between Jukebox and human-generated music. The Verge mentioned "It's highly excellent, even if the outcomes seem like mushy variations of tunes that might feel familiar", while Business Insider stated "surprisingly, a few of the resulting tunes are catchy and sound genuine". [234] [235] [236]
 <br>Interface<br>
 <br>Debate Game<br>
 <br>In 2018, OpenAI launched the Debate Game, which teaches devices to discuss toy issues in front of a human judge. The function is to research whether such an approach might help in auditing [AI](http://jatushome.myqnapcloud.com:8090) decisions and in developing explainable [AI](https://git.buckn.dev). [237] [238]
 <br>Microscope<br>
 <br>Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and neuron of 8 [neural network](https://in.fhiky.com) models which are typically studied in interpretability. [240] Microscope was produced to evaluate the functions that form inside these neural networks quickly. The designs consisted of are AlexNet, VGG-19, various variations of Inception, and various versions of CLIP Resnet. [241]
 <br>ChatGPT<br>
 <br>Launched in November 2022, ChatGPT is an artificial intelligence tool built on top of GPT-3 that supplies a conversational interface that allows users to ask [questions](https://inamoro.com.br) in natural language. The system then responds with an answer within seconds.<br>