commit
40b8ef7f1c
@ -0,0 +1,76 @@
|
||||
<br>Announced in 2016, Gym is an open-source Python library created to assist in the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://skillsinternational.co.in) research, making published research more easily reproducible [24] [144] while offering users with a basic interface for communicating with these environments. In 2022, new developments 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 reinforcement knowing (RL) research study on video games [147] utilizing RL algorithms and research [study generalization](http://git.scdxtc.cn). Prior RL research study [focused](https://thisglobe.com) mainly on optimizing agents to resolve single jobs. Gym Retro gives the capability to generalize in between video games with comparable principles but different looks.<br>
|
||||
<br>RoboSumo<br>
|
||||
<br>[Released](https://git.olivierboeren.nl) in 2017, RoboSumo is a virtual world where humanoid metalearning robotic [representatives](http://vts-maritime.com) at first do not have knowledge of how to even stroll, but are given the goals of learning to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives discover how to adjust to changing conditions. When a representative is then removed from this virtual environment and positioned in a new virtual environment with high winds, the representative braces to remain upright, recommending it had actually learned how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives could create an intelligence "arms race" that could increase an agent's ability to function even outside the context of the competitors. [148]
|
||||
<br>OpenAI 5<br>
|
||||
<br>OpenAI Five is a group of 5 OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that find out to play against human players at a high ability level completely through experimental algorithms. Before ending up being a team of 5, the very first public demonstration happened at The International 2017, [it-viking.ch](http://it-viking.ch/index.php/User:MohammadCecil6) the annual premiere championship tournament for the video game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one [matchup](https://2flab.com). [150] [151] After the match, CTO Greg Brockman [explained](http://git.cattech.org) that the bot had found out by playing against itself for two weeks of actual time, which the learning software was an action in the instructions of producing software that can manage complex jobs like a cosmetic surgeon. [152] [153] The system utilizes a type of reinforcement learning, as the bots learn over time by playing against themselves [numerous](http://expertsay.blog) times a day for months, and are rewarded for actions such as killing an enemy and taking [map goals](https://www.longisland.com). [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 teams of amateur and semi-professional players. [157] [154] [158] [159] At The [International](https://techport.io) 2018, OpenAI Five played in two exhibit matches against [professional](https://git.yinas.cn) players, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat 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 appearance came later that month, where they played in 42,729 overall video games in a four-day open online competition, winning 99.4% of those games. [165]
|
||||
<br>OpenAI 5's mechanisms in Dota 2's bot player reveals the obstacles of [AI](http://139.224.213.4:3000) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually shown the usage of [deep reinforcement](https://sosmed.almarifah.id) knowing (DRL) representatives to attain superhuman skills in Dota 2 matches. [166]
|
||||
<br>Dactyl<br>
|
||||
<br>[Developed](https://git.intelgice.com) in 2018, Dactyl utilizes machine learning to train a Shadow Hand, a human-like robotic hand, to manipulate physical items. [167] It finds out entirely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI took on the things orientation problem by utilizing domain randomization, a simulation approach which exposes the learner to a range of experiences instead of to fit to reality. The set-up for Dactyl, aside from having movement tracking video cameras, likewise has [RGB cameras](https://git.uzavr.ru) to permit the robot to control an approximate things 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 that Dactyl might fix a Rubik's Cube. The robotic was able to fix 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 Domain Randomization (ADR), a simulation approach of [generating progressively](https://www.friend007.com) harder environments. ADR varies from manual domain randomization by not requiring a human to specify 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](http://git.swordlost.top) models established by OpenAI" to let designers contact it for "any English language [AI](https://www.calebjewels.com) task". [170] [171]
|
||||
<br>Text generation<br>
|
||||
<br>The business 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 design was written by Alec Radford and his coworkers, and published in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative design of language could obtain world understanding and procedure long-range dependences by pre-training on a diverse corpus with long stretches of adjoining 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 initial [GPT design](https://gitea.thisbot.ru) ("GPT-1"). GPT-2 was announced in February 2019, with only minimal demonstrative variations initially released to the public. The full variation of GPT-2 was not right away released due to concern about prospective misuse, consisting of applications for writing phony news. [174] Some specialists revealed uncertainty that GPT-2 positioned a substantial risk.<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](https://skillnaukri.com) of "the innovation to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out 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 presentations of different instances of GPT-2 and other transformer models. [178] [179] [180]
|
||||
<br>GPT-2's authors argue without supervision language designs to be [general-purpose](https://gitlab.anc.space) students, highlighted by GPT-2 attaining modern [accuracy](http://autogangnam.dothome.co.kr) and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not more 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 a minimum of 3 upvotes. It avoids certain problems [encoding vocabulary](https://tawtheaf.com) with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both individual 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 design and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion specifications, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million criteria were also trained). [186]
|
||||
<br>OpenAI stated that GPT-3 was successful at certain "meta-learning" jobs and could generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing in between English and Romanian, and between English and German. [184]
|
||||
<br>GPT-3 dramatically improved benchmark results 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 [required](https://tagreba.org) a number of thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly launched to the general public for issues of possible abuse, although OpenAI planned to permit gain 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 exclusively 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](http://gitlab.hupp.co.kr) 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 create working code in over a lots shows languages, a lot of successfully in Python. [192]
|
||||
<br>Several problems with glitches, style flaws and security vulnerabilities were mentioned. [195] [196]
|
||||
<br>GitHub Copilot has actually been implicated 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), capable of accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar test with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also check out, analyze or generate as much as 25,000 words of text, and compose code in all major programs languages. [200]
|
||||
<br>Observers reported that the version of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose different technical details and stats about GPT-4, such as the accurate size of the design. [203]
|
||||
<br>GPT-4o<br>
|
||||
<br>On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained advanced lead to voice, multilingual, and vision benchmarks, setting 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, 2024, OpenAI launched GPT-4o mini, a smaller sized variation of GPT-4o [changing](https://www.diekassa.at) GPT-3.5 Turbo on the ChatGPT 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](https://palkwall.com) it to be particularly [helpful](http://git.baobaot.com) for business, startups and developers seeking to automate services with [AI](https://bdenc.com) agents. [208]
|
||||
<br>o1<br>
|
||||
<br>On September 12, 2024, OpenAI launched the o1[-preview](https://git.tesinteractive.com) and o1-mini models, which have actually been developed to take more time to consider their responses, leading to greater precision. These models are especially reliable in science, coding, and thinking tasks, 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 unveiled o3, the follower of the o1 thinking design. OpenAI likewise unveiled o3-mini, a lighter and much faster variation of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers 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 supplier O2. [215]
|
||||
<br>Deep research<br>
|
||||
<br>Deep research study is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform comprehensive web browsing, data analysis, and synthesis, [providing detailed](https://likemochi.com) reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools enabled, it reached an accuracy 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 similarity 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 design that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural [language inputs](https://sameday.iiime.net) (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can produce pictures of practical 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"). As of March 2021, no API or code is available.<br>
|
||||
<br>DALL-E 2<br>
|
||||
<br>In April 2022, OpenAI revealed DALL-E 2, an upgraded version of the design with more realistic results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new simple 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 model better able to create images from complex descriptions without manual timely engineering and render intricate 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](https://micircle.in) based upon short detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.<br>
|
||||
<br>Sora's development team called it after the Japanese word for "sky", to symbolize its "unlimited creative capacity". [223] Sora's innovation is an adaptation of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos accredited for that function, however did not expose the number or the specific 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 might generate videos up to one minute long. It also shared a technical report highlighting the methods utilized to train the model, and the design's capabilities. [225] It acknowledged a few of its shortcomings, consisting of struggles mimicing 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 might not represent Sora's common output. [225]
|
||||
<br>Despite uncertainty from some academic leaders following Sora's public demonstration, significant entertainment-industry figures have shown substantial interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's ability to produce realistic video from text descriptions, mentioning its possible to change storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had decided 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 recognition model. [228] It is trained on a large dataset of varied audio and is likewise a multi-task design that can carry out multilingual speech acknowledgment along with 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](https://it-storm.ru3000) musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a song produced by MuseNet tends to start fairly however then fall into mayhem the longer it plays. [230] [231] In popular culture, [initial applications](https://www.armeniapedia.org) of this tool were utilized as early as 2020 for the internet mental thriller Ben Drowned to create 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 bit of lyrics and outputs tune samples. OpenAI stated the songs "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the songs do not have "familiar larger musical structures such as choruses that repeat" and that "there is a substantial space" between Jukebox and [human-generated music](http://8.134.253.2218088). The Verge mentioned "It's technologically remarkable, even if the results seem like mushy variations of tunes that may feel familiar", while [Business Insider](https://www.genbecle.com) mentioned "remarkably, a few of the resulting tunes are memorable and sound legitimate". [234] [235] [236]
|
||||
<br>User interfaces<br>
|
||||
<br>Debate Game<br>
|
||||
<br>In 2018, [OpenAI introduced](http://43.143.245.1353000) the Debate Game, which [teaches makers](http://dibodating.com) to [dispute toy](http://ev-gateway.com) issues in front of a human judge. The function is to research study whether such a technique might help in auditing [AI](https://hyg.w-websoft.co.kr) [choices](http://vts-maritime.com) and in establishing explainable [AI](https://desarrollo.skysoftservicios.com). [237] [238]
|
||||
<br>Microscope<br>
|
||||
<br>Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and nerve cell of 8 neural network models which are frequently studied in interpretability. [240] Microscope was developed to [analyze](https://gitlab.liangzhicn.com) the functions that form inside these neural networks quickly. The models included are AlexNet, VGG-19, different versions of Inception, and various [versions](https://koubry.com) of CLIP Resnet. [241]
|
||||
<br>ChatGPT<br>
|
||||
<br>Launched in November 2022, ChatGPT is an artificial intelligence tool constructed on top of GPT-3 that offers a conversational user interface that allows users to ask concerns in [natural language](https://jobspaddy.com). The system then responds with an answer within seconds.<br>
|
||||
Loading…
Reference in new issue