1 changed files with 76 additions and 0 deletions
@ -0,0 +1,76 @@ |
|||
<br>Announced in 2016, Gym is an open-source Python library designed to assist in the advancement of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://www.imf1fan.com) research study, making released research study more easily reproducible [24] [144] while supplying users with a simple interface for connecting with these environments. In 2022, brand-new developments 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 reinforcement knowing (RL) research study on computer game [147] utilizing RL algorithms and [ratemywifey.com](https://ratemywifey.com/author/christenaw4/) research study generalization. Prior RL research focused mainly on optimizing agents to fix single tasks. Gym Retro gives the ability to generalize between games with comparable concepts however different looks.<br> |
|||
<br>RoboSumo<br> |
|||
<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially do not have understanding of how to even stroll, however are offered the goals of discovering to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the representatives learn how to adapt to changing conditions. When a representative is then removed from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, recommending it had found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents could produce 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 team of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that find out to play against human gamers at a high ability level completely through trial-and-error algorithms. Before becoming a group of 5, the first public demonstration occurred at The International 2017, the yearly premiere champion tournament for the game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live one-on-one matchup. [150] [151] After the match, [CTO Greg](https://napolifansclub.com) Brockman explained that the bot had actually found out by playing against itself for two weeks of actual time, which the learning software was a step in the direction of creating software that can handle complicated jobs like a surgeon. [152] [153] The system utilizes a type of support knowing, as the bots learn with time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an enemy and taking map objectives. [154] [155] [156] |
|||
<br>By June 2018, the capability of the bots expanded to play together as a full team of 5, and they were able to beat groups of [amateur](http://182.92.163.1983000) and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against professional gamers, [kousokuwiki.org](http://kousokuwiki.org/wiki/%E5%88%A9%E7%94%A8%E8%80%85:ElvisBynum53054) but ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champions of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public appearance came later that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those video games. [165] |
|||
<br>OpenAI 5's systems in Dota 2's bot gamer reveals the challenges of [AI](https://pingpe.net) systems in [multiplayer online](http://gungang.kr) battle arena (MOBA) video games and how OpenAI Five has actually shown making use of deep support learning (DRL) representatives to attain superhuman [competence](https://gitlab.ngser.com) in Dota 2 [matches](https://geniusactionblueprint.com). [166] |
|||
<br>Dactyl<br> |
|||
<br>Developed in 2018, Dactyl utilizes machine finding out to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It discovers entirely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation problem by utilizing domain randomization, a simulation method which exposes the student to a variety of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having motion tracking cams, likewise has RGB electronic cameras to allow the robot to manipulate an approximate item 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 showed that Dactyl might fix a Rubik's Cube. The robotic had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube present complicated physics that is harder to model. OpenAI did this by improving the robustness of Dactyl to [perturbations](http://82.157.11.2243000) by using Automatic Domain Randomization (ADR), a simulation method of generating progressively more challenging environments. ADR varies from manual domain randomization by not requiring a human to specify [randomization ranges](https://ashawo.club). [169] |
|||
<br>API<br> |
|||
<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://ejamii.com) models established by OpenAI" to let designers call on it for "any English language [AI](https://mmatycoon.info) task". [170] [171] |
|||
<br>Text generation<br> |
|||
<br>The business has [popularized generative](https://www.nc-healthcare.co.uk) pretrained transformers (GPT). [172] |
|||
<br>OpenAI's initial GPT design ("GPT-1")<br> |
|||
<br>The initial paper on generative pre-training of a transformer-based language model was written by Alec Radford and his associates, and published in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of [language](https://955x.com) could obtain world knowledge 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 not being watched transformer language design and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only minimal demonstrative variations at first released to the general public. The full version of GPT-2 was not immediately launched due to concern about potential misuse, including applications for composing phony news. [174] Some experts expressed uncertainty that GPT-2 presented a significant risk.<br> |
|||
<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to identify "neural phony news". [175] Other researchers, such as Jeremy Howard, alerted of "the technology to absolutely 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 released the total variation of the GPT-2 language design. [177] Several websites host interactive demonstrations of various circumstances of GPT-2 and other transformer designs. [178] [179] [180] |
|||
<br>GPT-2's authors argue not being watched language designs to be general-purpose students, highlighted by GPT-2 attaining state-of-the-art accuracy and [perplexity](http://chichichichichi.top9000) on 7 of 8 zero-shot jobs (i.e. the design was not further 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 at least 3 upvotes. It avoids certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This [permits](http://zerovalueentertainment.com3000) 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 model and the successor to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 designs with as few as 125 million criteria were likewise trained). [186] |
|||
<br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning between [English](https://freedomlovers.date) and Romanian, and between English and German. [184] |
|||
<br>GPT-3 drastically enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or encountering the fundamental ability constraints of [predictive language](https://raumlaborlaw.com) models. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 [trained design](https://intermilanfansclub.com) was not right away released to the general public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month free personal 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](https://www.tobeop.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the design can produce working code in over a dozen shows languages, many successfully in Python. [192] |
|||
<br>Several issues with glitches, style defects and security vulnerabilities were cited. [195] [196] |
|||
<br>GitHub Copilot has been implicated of producing copyrighted code, with no author attribution or license. [197] |
|||
<br>OpenAI announced that they would discontinue 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), efficient in accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar exam 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 might likewise read, examine or create as much as 25,000 words of text, and compose code in all significant programs languages. [200] |
|||
<br>Observers reported that the version of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has declined to expose various technical details and stats about GPT-4, such as the exact size of the design. [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 advanced results in voice, multilingual, and vision standards, 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](http://60.23.29.2133060) to 86.5% by GPT-4. [207] |
|||
<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller version 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 anticipates it to be especially [beneficial](https://circassianweb.com) for business, startups and designers seeking to automate services with [AI](https://codes.tools.asitavsen.com) agents. [208] |
|||
<br>o1<br> |
|||
<br>On September 12, 2024, OpenAI launched the o1 and o1-mini designs, which have actually been developed to take more time to think of their reactions, leading to higher accuracy. These models are especially 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 replaced by o1. [211] |
|||
<br>o3<br> |
|||
<br>On December 20, 2024, OpenAI revealed o3, the follower of the o1 [reasoning design](https://mypungi.com). OpenAI likewise revealed o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, they are checking 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](http://120.77.240.2159701) with telecommunications services company O2. [215] |
|||
<br>Deep research<br> |
|||
<br>Deep research study is a representative developed by OpenAI, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11864354) unveiled on February 2, 2025. It leverages the [capabilities](https://howtolo.com) of OpenAI's o3 design to perform comprehensive web browsing, data analysis, and synthesis, delivering detailed [reports](https://wik.co.kr) within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools enabled, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120] |
|||
<br>Image category<br> |
|||
<br>CLIP<br> |
|||
<br>[Revealed](https://hebrewconnect.tv) in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to evaluate the semantic similarity between text and images. It can notably be utilized for image classification. [217] |
|||
<br>Text-to-image<br> |
|||
<br>DALL-E<br> |
|||
<br>Revealed in 2021, DALL-E is a Transformer model that produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images. It can produce images of sensible objects ("a stained-glass window with an image of a blue strawberry") as well as items 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 updated version of the model with more realistic outcomes. [219] In December 2022, OpenAI published on [GitHub software](http://www.yfgame.store) application for Point-E, a new rudimentary system for transforming a text description into a 3-dimensional model. [220] |
|||
<br>DALL-E 3<br> |
|||
<br>In September 2023, OpenAI revealed DALL-E 3, a more effective design better able to generate images from intricate descriptions without manual timely engineering and render intricate 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 design that can produce videos based on short detailed triggers [223] along with [extend existing](https://noaisocial.pro) videos forwards or backwards 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 development group called it after the Japanese word for "sky", to represent its "endless imaginative capacity". [223] Sora's technology is an adjustment of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos [certified](http://110.42.231.1713000) for that function, but did not reveal the number or the exact sources of the videos. [223] |
|||
<br>OpenAI demonstrated some Sora-created high-definition videos to the public on February 15, 2024, specifying that it could generate videos approximately one minute long. It also shared a technical report highlighting the approaches utilized to train the model, and the design's capabilities. [225] It acknowledged a few of its imperfections, including struggles simulating intricate 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 scholastic leaders following Sora's public demonstration, significant entertainment-industry figures have actually revealed considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's ability to create practical video from text descriptions, mentioning its potential to transform storytelling and [pediascape.science](https://pediascape.science/wiki/User:BarrettMacNeil5) content production. He said that his excitement about Sora's possibilities was so strong that he had actually decided to pause 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](https://repo.correlibre.org) acknowledgment model. [228] It is trained on a big dataset of diverse audio and is also a multi-task design that can perform multilingual speech recognition as well as 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 forecast subsequent musical notes in MIDI music files. It can produce songs with 10 instruments in 15 styles. According to The Verge, a tune created by MuseNet tends to begin fairly however then fall under turmoil the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized as early as 2020 for the internet psychological thriller Ben Drowned to develop music for the [titular](https://actsfile.com) 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](http://www.xn--80agdtqbchdq6j.xn--p1ai). OpenAI specified the songs "reveal local musical coherence [and] follow traditional chord patterns" however [acknowledged](http://dev.shopraves.com) that the songs do not have "familiar bigger musical structures such as choruses that duplicate" which "there is a substantial gap" between Jukebox and human-generated music. The Verge specified "It's highly excellent, even if the outcomes seem like mushy versions of tunes that might feel familiar", while Business Insider specified "remarkably, some of the resulting tunes are catchy and sound legitimate". [234] [235] [236] |
|||
<br>User interfaces<br> |
|||
<br>Debate Game<br> |
|||
<br>In 2018, OpenAI introduced the Debate Game, which teaches devices to debate toy issues in front of a human judge. The purpose is to research study whether such a technique may help in auditing [AI](https://aceme.ink) choices and in establishing explainable [AI](https://git.esc-plus.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 eight neural network models which are typically studied in interpretability. [240] Microscope was produced to examine the functions that form inside these neural networks quickly. The models included are AlexNet, VGG-19, various versions of Inception, and different 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 user interface that enables users to ask questions in natural language. The system then responds with a response within seconds.<br> |
|||
Loading…
Reference in new issue