1 changed files with 76 additions and 0 deletions
@ -0,0 +1,76 @@ |
|||
<br>Announced in 2016, Gym is an open-source Python library created to assist in the development of reinforcement learning [algorithms](http://119.130.113.2453000). It aimed to standardize how environments are specified in [AI](https://warleaks.net) research study, making published research more easily reproducible [24] [144] while supplying users with an easy interface for engaging with these environments. In 2022, brand-new advancements of Gym have actually been transferred to the library Gymnasium. [145] [146] |
|||
<br>Gym Retro<br> |
|||
<br>Released in 2018, Gym Retro is a platform for support learning (RL) research on computer game [147] using RL algorithms and research study generalization. Prior RL research study focused mainly on optimizing agents to resolve single tasks. Gym Retro provides the capability to generalize between video games with comparable principles however different appearances.<br> |
|||
<br>RoboSumo<br> |
|||
<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents at first lack understanding of how to even stroll, however are given the goals of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives find out how to adapt to changing conditions. When a representative is then removed from this virtual environment and put in a new virtual environment with high winds, the agent braces to remain upright, recommending it had learned how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition between agents could create an intelligence "arms race" that might 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 used in the [competitive five-on-five](https://virtualoffice.com.ng) computer game Dota 2, that learn to play against [human gamers](https://projectblueberryserver.com) at a high ability level [totally](https://janhelp.co.in) 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](https://crossborderdating.com) championship tournament for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had found out by playing against itself for 2 weeks of genuine time, which the knowing software [application](https://kaykarbar.com) was a step in the direction of creating software that can manage complicated tasks like a cosmetic surgeon. [152] [153] The system utilizes a kind of support knowing, as the bots learn with time by playing against themselves hundreds of times a day for months, and are rewarded for [actions](https://fototik.com) such as eliminating an enemy and taking [map objectives](https://centerdb.makorang.com). [154] [155] [156] |
|||
<br>By June 2018, the ability of the bots broadened to play together as a full group of 5, and they had the ability to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against expert gamers, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five [defeated](https://www.keyfirst.co.uk) OG, the ruling world champions of the game at the time, 2:0 in a match in San Francisco. [163] [164] The bots' last 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 video games. [165] |
|||
<br>OpenAI 5['s mechanisms](https://amore.is) in Dota 2's bot gamer shows the challenges of [AI](http://zaxx.co.jp) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually shown the usage of deep support learning (DRL) agents to attain superhuman proficiency in Dota 2 matches. [166] |
|||
<br>Dactyl<br> |
|||
<br>Developed in 2018, Dactyl utilizes machine discovering to train a Shadow Hand, a human-like robot hand, to manipulate physical objects. [167] It discovers totally in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the object orientation issue by utilizing domain randomization, a simulation approach which [exposes](https://www.womplaz.com) the learner to a range of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having movement tracking video cameras, also has RGB electronic cameras to enable the robot to manipulate an arbitrary object by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168] |
|||
<br>In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robotic was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to model. OpenAI did this by improving the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of producing gradually harder environments. ADR varies from manual domain randomization by not needing a human to specify randomization ranges. [169] |
|||
<br>API<br> |
|||
<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://git.pm-gbr.de) designs developed by OpenAI" to let developers call on it for "any English language [AI](http://www.zjzhcn.com) task". [170] [171] |
|||
<br>Text generation<br> |
|||
<br>The business has popularized generative pretrained transformers (GPT). [172] |
|||
<br>OpenAI's initial GPT model ("GPT-1")<br> |
|||
<br>The [original paper](https://git.parat.swiss) on generative pre-training of a transformer-based language design was composed by Alec Radford and his associates, [pediascape.science](https://pediascape.science/wiki/User:BettyeParent1) and released in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative design of language might obtain world knowledge and procedure long-range dependences by pre-training on a diverse corpus with long stretches of contiguous text.<br> |
|||
<br>GPT-2<br> |
|||
<br>Generative [Pre-trained Transformer](https://maarifatv.ng) 2 ("GPT-2") is a without supervision transformer language model and the follower to OpenAI's original [GPT design](https://www.joboont.in) ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative variations initially released to the public. The complete variation of GPT-2 was not right away launched due to concern about prospective abuse, consisting of applications for writing phony news. [174] Some experts revealed uncertainty that GPT-2 presented a considerable danger.<br> |
|||
<br>In response to GPT-2, the Allen Institute for Artificial Intelligence [responded](https://git.gilesmunn.com) with a tool to spot "neural fake news". [175] Other researchers, such as Jeremy Howard, warned 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 complete version of the GPT-2 language design. [177] Several websites host interactive presentations of various 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 learners, highlighted by GPT-2 attaining advanced precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further trained 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 at least 3 upvotes. It prevents certain problems encoding vocabulary with word tokens by utilizing 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 not being [watched transformer](https://gitlab.ucc.asn.au) language design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned 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 complete variation of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were also trained). [186] |
|||
<br>OpenAI specified that GPT-3 was successful at certain "meta-learning" tasks and might generalize the [function](https://193.31.26.118) of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing between English and Romanian, and between English and German. [184] |
|||
<br>GPT-3 drastically enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or experiencing the essential ability constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, [compared](http://111.9.47.10510244) to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not right away [released](https://git.eugeniocarvalho.dev) to the public for issues of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month free private beta that began in June 2020. [170] [189] |
|||
<br>On September 23, 2020, GPT-3 was certified solely 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://vydiio.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [private](https://gitlab.dndg.it) beta. [194] According to OpenAI, the model can create working code in over a lots programming languages, a lot of efficiently in Python. [192] |
|||
<br>Several issues with glitches, design defects and security vulnerabilities were mentioned. [195] [196] |
|||
<br>GitHub Copilot has been implicated of emitting copyrighted code, with no author attribution or license. [197] |
|||
<br>OpenAI announced that they would terminate 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 or image inputs. [199] They announced that the upgraded innovation passed a simulated law school bar examination 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 could likewise check out, examine or generate as much as 25,000 words of text, and compose code in all significant programming languages. [200] |
|||
<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the problems with earlier revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose various technical details and stats about GPT-4, such as the exact size of the model. [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 standards, 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 launched GPT-4o mini, a smaller variation of GPT-4o replacing 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 anticipates it to be especially helpful for enterprises, startups and designers seeking to automate services with [AI](https://clinicial.co.uk) representatives. [208] |
|||
<br>o1<br> |
|||
<br>On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have actually been developed to take more time to consider their reactions, leading to higher precision. These designs are particularly effective in science, coding, and reasoning 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 unveiled o3, the successor of the o1 reasoning design. OpenAI likewise unveiled o3-mini, a lighter and quicker variation of OpenAI o3. Since December 21, 2024, this model is not available for public usage. According to OpenAI, they are testing 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 model is called o3 instead of o2 to avoid confusion with telecommunications services provider O2. [215] |
|||
<br>Deep research<br> |
|||
<br>Deep research study is an agent developed by OpenAI, unveiled on February 2, 2025. It [leverages](http://124.222.7.1803000) the capabilities of OpenAI's o3 model to [perform comprehensive](http://hulaser.com) web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools made it possible for, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) standard. [120] |
|||
<br>Image category<br> |
|||
<br>CLIP<br> |
|||
<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the semantic similarity in between text and images. It can especially be utilized for image category. [217] |
|||
<br>Text-to-image<br> |
|||
<br>DALL-E<br> |
|||
<br>Revealed in 2021, DALL-E is a Transformer design that produces images from textual descriptions. [218] DALL-E [utilizes](http://1.92.128.2003000) a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of an unfortunate capybara") and create corresponding images. It can create pictures of sensible items ("a stained-glass window with a picture of a blue strawberry") in addition to objects 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 variation of the design with more reasonable results. [219] In December 2022, [OpenAI released](https://kiwiboom.com) on GitHub software application for Point-E, a new simple system for transforming 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 produce images from [intricate descriptions](https://jobsportal.harleysltd.com) without manual timely engineering and render complex details like hands and text. [221] It was released to the general 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 create videos based upon brief detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution up to 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.<br> |
|||
<br>Sora's development group called it after the Japanese word for "sky", to signify its "unlimited innovative potential". [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 in addition to copyrighted videos licensed for that purpose, however did not reveal the number or the exact sources of the videos. [223] |
|||
<br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, specifying that it could create videos as much as one minute long. It likewise shared a technical report highlighting the methods utilized to train the model, and the design's abilities. [225] It acknowledged some of its imperfections, consisting of battles replicating complex [physics](https://git.kicker.dev). [226] Will [Douglas Heaven](https://aipod.app) of the MIT Technology Review called the presentation videos "remarkable", however kept in mind that they must have been [cherry-picked](https://weworkworldwide.com) and may not represent Sora's normal output. [225] |
|||
<br>Despite uncertainty from some academic leaders following Sora's public demo, notable entertainment-industry figures have revealed substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's capability to create sensible video from text descriptions, citing its possible to transform storytelling and content production. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen 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://redmonde.es) acknowledgment model. [228] It is trained on a big dataset of varied audio and is likewise a multi-task design that can carry out multilingual speech recognition 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 anticipate subsequent musical notes in [MIDI music](https://community.scriptstribe.com) files. It can produce tunes with 10 [instruments](http://git.moneo.lv) in 15 styles. According to The Verge, a tune created by MuseNet tends to start fairly however then fall into chaos 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 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 snippet of lyrics and outputs tune samples. OpenAI specified the tunes "show local musical coherence [and] follow standard chord patterns" however acknowledged that the songs lack "familiar bigger musical structures such as choruses that repeat" and that "there is a significant gap" between Jukebox and human-generated music. The Verge mentioned "It's highly excellent, even if the outcomes seem like mushy versions of tunes that might feel familiar", while Business Insider mentioned "surprisingly, some of the resulting songs are memorable and sound legitimate". [234] [235] [236] |
|||
<br>User interfaces<br> |
|||
<br>Debate Game<br> |
|||
<br>In 2018, OpenAI launched the Debate Game, which teaches makers to [discuss toy](https://epcblind.org) problems in front of a human judge. The [function](https://gitlab.donnees.incubateur.anct.gouv.fr) is to research study whether such a technique might assist in auditing [AI](https://hiremegulf.com) choices and in establishing explainable [AI](https://gitea.jessy-lebrun.fr). [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 designs which are typically studied in interpretability. [240] Microscope was created to analyze the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, various variations of Inception, and various variations of CLIP Resnet. [241] |
|||
<br>ChatGPT<br> |
|||
<br>Launched in November 2022, ChatGPT is an artificial intelligence tool developed on top of GPT-3 that provides a conversational user interface that enables users to ask concerns in natural language. The system then responds with a response within seconds.<br> |
|||
Loading…
Reference in new issue