commit
87cc890098
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 help with the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are specified in [AI](http://lstelecom.co.kr) research study, making [published](http://vk-mix.ru) research more easily reproducible [24] [144] while offering users with a simple interface for connecting 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 on video games [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on enhancing agents to resolve single jobs. Gym Retro offers the capability to generalize in between games with comparable ideas but different looks.<br> |
||||
<br>RoboSumo<br> |
||||
<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents [initially](https://kkhelper.com) do not have understanding of how to even stroll, but are given the goals of finding out to move and to push the opposing agent out of the ring. [148] Through this adversarial learning process, the representatives find out how to adjust to altering conditions. When an agent is then removed from this virtual environment and positioned in a brand-new virtual environment with high winds, the representative braces to remain upright, suggesting it had actually found out how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents could produce an intelligence "arms race" that could increase a representative's ability to function even outside the context of the competitors. [148] |
||||
<br>OpenAI 5<br> |
||||
<br>OpenAI Five is a team of 5 OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that discover to play against human players at a high ability level totally through trial-and-error algorithms. Before ending up being a team of 5, the very first public presentation happened at The International 2017, the annual best champion competition for the game, where Dendi, an expert Ukrainian player, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg [Brockman explained](https://code.flyingtop.cn) that the bot had found out by playing against itself for two weeks of real time, which the learning software application was a step in the direction of creating software that can handle complicated jobs like a surgeon. [152] [153] The system [utilizes](https://git.wsyg.mx) a type of support learning, as the bots discover gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as 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 group of 5, and they were able to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against expert players, but wound up losing both 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 exhibit match in San Francisco. [163] [164] The bots' final public appearance came later on 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 systems in Dota 2's bot player shows the challenges of [AI](https://git.adminkin.pro) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated the use of deep support [learning](https://www.yohaig.ng) (DRL) agents to [attain superhuman](http://git.iloomo.com) skills in Dota 2 matches. [166] |
||||
<br>Dactyl<br> |
||||
<br>Developed in 2018, Dactyl utilizes device learning to train a Shadow Hand, a human-like robot hand, to manipulate physical items. [167] It learns entirely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the object orientation problem by utilizing domain randomization, a simulation technique which exposes the student to a variety of experiences instead of [attempting](http://hrplus.com.vn) to fit to truth. The set-up for Dactyl, aside from having movement tracking cameras, likewise has RGB cams to enable the robot to control an arbitrary object 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 solve a Rubik's Cube. The robot had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube present complex [physics](http://8.136.42.2418088) that is harder to design. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic [Domain Randomization](https://jr.coderstrust.global) (ADR), a simulation method of creating gradually harder environments. ADR differs from manual domain randomization by not needing a human to define 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://kkhelper.com) designs established by OpenAI" to let developers call on it for "any English language [AI](http://139.9.50.163:3000) task". [170] [171] |
||||
<br>Text generation<br> |
||||
<br>The company has actually promoted generative pretrained transformers (GPT). [172] |
||||
<br>OpenAI's initial GPT model ("GPT-1")<br> |
||||
<br>The original paper on generative pre-training of a [transformer-based language](https://www.nikecircle.com) design was composed by Alec Radford and his coworkers, and published in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language might 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](http://playtube.ythomas.fr) Transformer 2 ("GPT-2") is a without supervision transformer language design and the follower to OpenAI's initial GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative [versions](http://66.112.209.23000) initially launched to the general public. The full version of GPT-2 was not immediately released due to issue about potential misuse, consisting of applications for writing fake news. [174] Some professionals revealed uncertainty that GPT-2 [postured](https://te.legra.ph) a considerable risk.<br> |
||||
<br>In action to GPT-2, the Allen Institute for Artificial Intelligence [responded](https://videoflixr.com) with a tool to detect "neural phony news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the complete variation of the GPT-2 language design. [177] Several websites host interactive demonstrations of various instances of GPT-2 and [pipewiki.org](https://pipewiki.org/wiki/index.php/User:ShellieGenders) other transformer designs. [178] [179] [180] |
||||
<br>GPT-2's authors argue unsupervised language designs to be general-purpose students, shown by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot tasks (i.e. the model 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 in Reddit submissions with a minimum of 3 upvotes. It prevents certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters by encoding both [specific characters](http://optx.dscloud.me32779) 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 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 larger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 designs with as few as 125 million [criteria](http://gogs.oxusmedia.com) were likewise trained). [186] |
||||
<br>OpenAI mentioned that GPT-3 prospered at certain "meta-learning" jobs and could generalize the [function](https://sebeke.website) of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning in between English and Romanian, and between English and German. [184] |
||||
<br>GPT-3 drastically improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or experiencing the essential ability constraints of predictive language designs. [187] Pre-training GPT-3 required a number of thousand petaflop/s-days [b] of compute, [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:MichaelCrocker0) compared to 10s of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not right away released to the public for concerns of possible abuse, although [OpenAI prepared](https://napvibe.com) to permit gain access to through a paid cloud API after a [two-month free](https://workbook.ai) personal 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://120.196.85.174:3000) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can create working code in over a lots programming languages, many effectively in Python. [192] |
||||
<br>Several issues with problems, style defects and security vulnerabilities were cited. [195] [196] |
||||
<br>[GitHub Copilot](https://code.estradiol.cloud) has actually been accused of emitting copyrighted code, with no author attribution or license. [197] |
||||
<br>OpenAI revealed that they would cease assistance 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), efficient in [accepting text](https://chatgay.webcria.com.br) or image inputs. [199] They announced that the updated technology passed a simulated law school bar examination 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, evaluate or produce as much as 25,000 words of text, and write code in all major shows languages. [200] |
||||
<br>Observers reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained some 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 reveal different technical details and statistics about GPT-4, such as the precise size of the design. [203] |
||||
<br>GPT-4o<br> |
||||
<br>On May 13, 2024, OpenAI announced and released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained advanced lead to voice, multilingual, and vision criteria, setting 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 released GPT-4o mini, a smaller sized version of GPT-4o changing GPT-3.5 Turbo on the ChatGPT interface. Its API costs $0.15 per million [input tokens](https://savico.com.br) and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially beneficial for business, startups and designers looking for to automate services with [AI](https://www.trappmasters.com) agents. [208] |
||||
<br>o1<br> |
||||
<br>On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been developed to take more time to consider their actions, causing greater accuracy. These designs are particularly efficient in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Employee. [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 model. OpenAI likewise revealed o3-mini, a lighter and much faster variation of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these designs. [214] The design is called o3 instead of o2 to prevent confusion with telecoms [providers](https://glhwar3.com) 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 model to carry out comprehensive web browsing, information analysis, and synthesis, [delivering](https://git.yharnam.xyz) detailed reports 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) criteria. [120] |
||||
<br>Image classification<br> |
||||
<br>CLIP<br> |
||||
<br>Revealed 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 significantly be utilized for image category. [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 variation of GPT-3 to translate natural language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and produce corresponding images. It can produce pictures of sensible things ("a stained-glass window with an image of a blue strawberry") in addition to objects that do not exist in reality ("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 announced DALL-E 2, an updated variation of the model with more sensible results. [219] In December 2022, OpenAI published on GitHub software for Point-E, a brand-new primary system for [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:PHZIsis067429) transforming a text description into a 3-dimensional design. [220] |
||||
<br>DALL-E 3<br> |
||||
<br>In September 2023, OpenAI revealed DALL-E 3, a more effective design better able to create images from complicated descriptions without manual prompt engineering and render intricate [details](https://kewesocial.site) like hands and text. [221] It was [launched](https://www.telix.pl) 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 create videos based on brief detailed triggers [223] in addition to extend existing videos forwards or backwards in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.<br> |
||||
<br>Sora's advancement team called it after the Japanese word for "sky", to signify its "limitless creative potential". [223] Sora's technology is an adjustment 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 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 public on February 15, 2024, specifying that it might [generate videos](https://gitea.ymyd.site) as much as one minute long. It also shared a technical report highlighting the approaches used to train the design, and the design's capabilities. [225] It acknowledged a few of its imperfections, [consisting](https://raisacanada.com) of struggles simulating intricate [physics](https://spm.social). [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", but noted that they need to have been cherry-picked and may not represent Sora's normal output. [225] |
||||
<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have revealed considerable interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the innovation's capability to [produce](https://worship.com.ng) sensible video from text descriptions, mentioning its prospective to reinvent storytelling and content development. He said that his excitement about [Sora's possibilities](https://home.zhupei.me3000) was so strong that he had chosen to stop briefly prepare for broadening his Atlanta-based film 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 diverse audio and is likewise a multi-task model 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 predict subsequent musical notes in MIDI music files. It can [generate songs](https://agalliances.com) with 10 instruments in 15 designs. According to The Verge, a tune created by MuseNet tends to begin fairly however then fall into mayhem the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized 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 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 stated the songs "show regional musical coherence [and] follow standard chord patterns" but acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" and that "there is a substantial gap" between Jukebox and human-generated music. The Verge mentioned "It's highly excellent, even if the outcomes seem like mushy variations of songs that may feel familiar", while Business Insider mentioned "remarkably, some of the resulting tunes are catchy and sound legitimate". [234] [235] [236] |
||||
<br>User user interfaces<br> |
||||
<br>Debate Game<br> |
||||
<br>In 2018, OpenAI launched the Debate Game, which teaches machines to debate toy issues in front of a human judge. The purpose is to research whether such an approach might help in auditing [AI](https://gogs.jublot.com) [decisions](https://e-sungwoo.co.kr) and in establishing explainable [AI](https://code.linkown.com). [237] [238] |
||||
<br>Microscope<br> |
||||
<br>Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and neuron of eight neural network models which are typically studied in interpretability. [240] Microscope was produced to analyze the functions that form inside these neural networks easily. The designs included are AlexNet, VGG-19, various versions of Inception, and various versions of CLIP Resnet. [241] |
||||
<br>ChatGPT<br> |
||||
<br>Launched in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that supplies a conversational user interface that enables users to ask [questions](http://hybrid-forum.ru) in natural language. The system then reacts with an answer within seconds.<br> |
||||
Loading…
Reference in new issue