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 <br>Announced in 2016, Gym is an [open-source Python](http://gitlab.digital-work.cn) library designed to assist in the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://gitlab.reemii.cn) research study, making published research study more easily reproducible [24] [144] while offering users with a simple interface for communicating with these environments. In 2022, new developments 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 support learning (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on optimizing agents to fix single tasks. Gym Retro provides the ability to [generalize](https://www.ycrpg.com) in between video games with comparable principles however different looks.<br>
 <br>RoboSumo<br>
 <br>Released in 2017, RoboSumo is a virtual world where [humanoid metalearning](https://jollyday.club) robot agents at first lack knowledge of how to even stroll, however are [offered](http://www.xyais.com) the goals of discovering to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing process, the agents find out how to adapt to altering conditions. When an agent is then removed from this virtual environment and [positioned](http://116.236.50.1038789) in a brand-new virtual environment with high winds, the representative braces to remain upright, suggesting it had found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between agents might develop an intelligence "arms race" that could increase an agent's ability to operate 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 computer game Dota 2, that learn 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 [occurred](http://47.122.26.543000) 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 individually](https://evove.io) matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had [discovered](https://901radio.com) by playing against itself for 2 weeks of actual time, which the learning software application was a step in the direction of creating software that can manage intricate jobs like a surgeon. [152] [153] The system uses a type of reinforcement learning, as the bots learn over time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an enemy and taking map goals. [154] [155] [156]
 <br>By June 2018, the capability of the bots broadened to play together as a full team of 5, and they were able to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The [International](http://123.206.9.273000) 2018, OpenAI Five played in 2 exhibition matches against professional gamers, however 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 exhibit match in San Francisco. [163] [164] The bots' last public appearance came later that month, where they played in 42,729 overall games in a four-day open online competitors,  [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11860868) winning 99.4% of those video games. [165]
 <br>OpenAI 5's systems in Dota 2's bot player reveals the challenges of [AI](https://actsfile.com) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has actually [demonstrated](https://git.elder-geek.net) the usage of deep support learning (DRL) representatives to attain superhuman competence in Dota 2 matches. [166]
 <br>Dactyl<br>
 <br>Developed in 2018, Dactyl uses device learning to train a Shadow Hand, a human-like robotic hand, to manipulate physical items. [167] It learns entirely in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the object orientation problem by using domain randomization, a simulation technique which exposes the learner to a variety of experiences rather than trying to fit to [reality](http://www.dahengsi.com30002). The set-up for Dactyl, aside from having movement tracking cams, likewise has RGB cameras to allow the robot to control an arbitrary object 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 demonstrated that Dactyl could resolve a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to model. OpenAI did this by improving the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of creating progressively [harder environments](http://tv.houseslands.com). 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 brand-new [AI](https://doop.africa) models developed by OpenAI" to let developers contact it for "any English language [AI](http://121.36.37.70:15501) job". [170] [171]
 <br>Text generation<br>
 <br>The company has popularized generative pretrained transformers (GPT). [172]
 <br>OpenAI's original GPT model ("GPT-1")<br>
 <br>The original paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his colleagues, and published in preprint on OpenAI's site on June 11, 2018. [173] It showed how a generative design of language might obtain world knowledge and procedure long-range [dependences](http://gogs.dev.fudingri.com) by [pre-training](https://dramatubes.com) on a diverse corpus with long stretches of adjoining text.<br>
 <br>GPT-2<br>
 <br>Generative Pre-trained Transformer 2 ("GPT-2") is an [unsupervised](https://www.jobseeker.my) [transformer language](http://47.122.26.543000) model and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative variations initially released to the public. The full variation of GPT-2 was not [instantly launched](http://64.227.136.170) due to issue about potential abuse, consisting of applications for composing fake news. [174] Some specialists expressed uncertainty that GPT-2 posed a considerable threat.<br>
 <br>In action to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural phony news". [175] Other researchers, such as Jeremy Howard, cautioned of "the innovation to absolutely 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 released the complete version of the GPT-2 language model. [177] Several sites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180]
 <br>GPT-2's authors argue not being watched language models to be general-purpose students, illustrated by GPT-2 attaining cutting edge accuracy and perplexity on 7 of 8 zero-shot jobs (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 somewhat 40 gigabytes of text from [URLs shared](https://doop.africa) in Reddit submissions with a minimum of 3 upvotes. It avoids 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 without supervision transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 contained 175 billion parameters, [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 few as 125 million criteria were also trained). [186]
 <br>OpenAI stated that GPT-3 was successful at certain "meta-learning" tasks 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 in between English and Romanian, and between English and German. [184]
 <br>GPT-3 dramatically enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or encountering the essential ability constraints of predictive language designs. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately launched to the public for concerns of possible abuse, although OpenAI planned to [enable gain](https://pandatube.de) access to through a paid cloud API after a two-month totally free private beta that started in June 2020. [170] [189]
 <br>On September 23, 2020, GPT-3 was certified specifically to Microsoft. [190] [191]
 <br>Codex<br>
 <br>Announced in mid-2021, Codex is a descendant of GPT-3 that has actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://64.227.136.170) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the model can develop working code in over a lots programs languages, most successfully in Python. [192]
 <br>Several problems with glitches, design defects and security vulnerabilities were mentioned. [195] [196]
 <br>GitHub Copilot has actually been accused of emitting copyrighted code, with no author attribution or license. [197]
 <br>OpenAI revealed that they would stop assistance for Codex API on March 23, 2023. [198]
 <br>GPT-4<br>
 <br>On March 14, 2023, OpenAI announced the [release](https://www.soundofrecovery.org) of Generative Pre-trained [Transformer](http://ptxperts.com) 4 (GPT-4), capable of accepting text or image inputs. [199] They [revealed](https://flowndeveloper.site) that the updated innovation passed a simulated law school bar exam with a score around the top 10% of [test takers](https://wiki.project1999.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise check out, examine or create approximately 25,000 words of text, and compose code in all major shows languages. [200]
 <br>Observers reported that the version of ChatGPT using GPT-4 was an improvement 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 efficient in taking images as input on ChatGPT. [202] OpenAI has actually declined to expose different technical details and stats about GPT-4, such as the precise size of the design. [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 state-of-the-art lead to voice, multilingual, and vision standards, setting brand-new records in audio speech acknowledgment and translation. [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,  [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:ChantalKopsen2) 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 and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI expects it to be especially beneficial for enterprises, start-ups and designers seeking to automate services with [AI](https://novashop6.com) representatives. [208]
 <br>o1<br>
 <br>On September 12,  [forum.pinoo.com.tr](http://forum.pinoo.com.tr/profile.php?id=1321148) 2024, OpenAI launched the o1-preview and o1-mini models, which have been developed to take more time to think about their responses, leading to greater precision. These models are particularly effective in science, coding, and [thinking](https://aipod.app) 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](https://www.hrdemployment.com) o3, the follower of the o1 reasoning model. OpenAI likewise revealed o3-mini, a lighter and faster variation of OpenAI o3. As of December 21, 2024, this design 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 researchers](https://git.chocolatinie.fr) had the [opportunity](https://neejobs.com) to obtain early access to these [designs](https://englishlearning.ketnooi.com). [214] The design is called o3 instead of o2 to prevent confusion with telecommunications [providers](https://161.97.85.50) O2. [215]
 <br>Deep research study<br>
 <br>Deep research is an agent developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out extensive web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and  [surgiteams.com](https://surgiteams.com/index.php/User:AshliLent31607) Python tools enabled, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) criteria. [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 between text and images. It can notably be used for 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](https://www.linkedaut.it). [218] DALL-E uses a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can create pictures of sensible things ("a stained-glass window with an image of a blue strawberry") along with things that do not exist in [reality](http://101.200.181.61) ("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](https://topbazz.com) DALL-E 2, an [updated variation](http://szyg.work3000) of the model with more sensible results. [219] In December 2022, OpenAI published on GitHub software for Point-E, a new basic system for converting a text description into a 3-dimensional model. [220]
 <br>DALL-E 3<br>
 <br>In September 2023, OpenAI announced DALL-E 3, a more powerful design better able to generate images from intricate descriptions without manual prompt engineering and render complicated 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 model that can create videos based upon short detailed triggers [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.<br>
 <br>Sora's development team named it after the Japanese word for "sky",  [garagesale.es](https://www.garagesale.es/author/trenapridha/) to symbolize its "limitless imaginative capacity". [223] Sora's technology is an adjustment of the innovation behind the [DALL ·](https://git.markscala.org) E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos licensed for that function, however did not expose the number or the exact sources of the videos. [223]
 <br>OpenAI showed 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 used to train the design, and the design's abilities. [225] It acknowledged a few of its drawbacks, including battles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", however noted that they should have been cherry-picked and might not represent Sora's normal output. [225]
 <br>Despite uncertainty from some scholastic leaders following Sora's public demo, noteworthy entertainment-industry figures have revealed substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his [astonishment](https://theneverendingstory.net) at the innovation's capability to generate sensible video from text descriptions, mentioning its potential to revolutionize storytelling and content development. He said that his enjoyment about Sora's possibilities was so strong that he had chosen 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 [recognition](https://www.virsocial.com) design. [228] It is trained on a large dataset of diverse audio and is likewise a multi-task design that can carry out multilingual speech  along with speech translation 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 create tunes with 10 instruments in 15 styles. According to The Verge, a tune generated by MuseNet tends to begin fairly but then fall into turmoil the longer it plays. [230] [231] In popular culture, preliminary 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 [produce music](https://git.obo.cash) 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 specified the tunes "reveal local musical coherence [and] follow conventional chord patterns" but acknowledged that the songs do not have "familiar larger musical structures such as choruses that repeat" and that "there is a significant gap" in between Jukebox and human-generated music. The Verge stated "It's highly excellent, even if the outcomes sound like mushy versions of songs that may feel familiar",  [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:BritneyVivier19) while Business Insider mentioned "surprisingly, a few of the resulting songs are appealing and sound genuine". [234] [235] [236]
 <br>User interfaces<br>
 <br>Debate Game<br>
 <br>In 2018, OpenAI introduced the Debate Game, which [teaches makers](https://crossdark.net) to dispute toy issues in front of a human judge. The purpose is to research whether such a technique may assist in auditing [AI](http://hi-couplering.com) decisions and in developing explainable [AI](https://hugoooo.com). [237] [238]
 <br>Microscope<br>
 <br>Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and nerve cell of 8 neural network models which are typically studied in interpretability. [240] Microscope was produced to examine the features that form inside these neural networks easily. The designs consisted of are AlexNet, VGG-19, different versions of Inception, and various variations 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 interface that enables users to ask questions in natural language. The system then responds with an answer within seconds.<br>