parent
8e3315d145
commit
e303281dee
@ -0,0 +1,76 @@
|
||||
<br>Announced in 2016, Gym is an open-source Python library developed to assist in the advancement of support knowing algorithms. It aimed to standardize how environments are defined in [AI](http://www.asiapp.co.kr) research, making released research more easily reproducible [24] [144] while providing users with a simple user interface for connecting with these environments. In 2022, new advancements of Gym have been transferred to the library Gymnasium. [145] [146]
|
||||
<br>Gym Retro<br>
|
||||
<br>Released in 2018, Gym Retro is a [platform](https://www.locumsanesthesia.com) for reinforcement knowing (RL) research study on computer game [147] using RL algorithms and research study generalization. Prior RL research focused mainly on optimizing representatives to solve single tasks. Gym Retro offers the capability to generalize in between video games with similar principles but different looks.<br>
|
||||
<br>RoboSumo<br>
|
||||
<br>Released in 2017, RoboSumo is a virtual world where robot representatives initially do not have understanding of how to even walk, however are provided the goals of learning to move and to push the opposing representative out of the ring. [148] Through this [adversarial knowing](https://gitlab.xfce.org) procedure, the representatives learn how to adjust to altering conditions. When an agent is then removed from this virtual environment and put in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had learned how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could create an intelligence "arms race" that might [increase](http://caxapok.space) 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 utilized in the competitive five-on-five computer game Dota 2, that discover to play against human gamers at a high ability level entirely through experimental algorithms. Before ending up being a group of 5, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:SashaJ9843126) the first public presentation happened at The International 2017, the annual premiere champion tournament for the game, where Dendi, an expert Ukrainian player, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for 2 weeks of real time, which the learning software was an action in the direction of creating software that can deal with intricate jobs like a surgeon. [152] [153] The system uses a type of reinforcement knowing, as the bots find out in time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an opponent and taking map objectives. [154] [155] [156]
|
||||
<br>By June 2018, the ability of the bots broadened to play together as a full team of 5, and they had the ability to [beat teams](https://git.hitchhiker-linux.org) of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against [professional](https://vmi456467.contaboserver.net) gamers, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five [defeated](https://consultoresdeproductividad.com) OG, the reigning world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public look came later on that month, where they played in 42,729 total video games in a four-day open online competition, winning 99.4% of those video games. [165]
|
||||
<br>OpenAI 5['s mechanisms](https://gitea.umrbotech.com) in Dota 2's bot gamer reveals the challenges of [AI](http://47.109.30.194:8888) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually shown the usage of deep reinforcement knowing (DRL) [representatives](https://eelam.tv) to attain superhuman skills in Dota 2 matches. [166]
|
||||
<br>Dactyl<br>
|
||||
<br>Developed in 2018, Dactyl utilizes maker finding out to train a Shadow Hand, a human-like robot hand, to control physical items. [167] It discovers completely in simulation utilizing the exact same RL algorithms and [training](http://1.92.66.293000) code as OpenAI Five. OpenAI dealt with the object orientation issue by utilizing domain randomization, a simulation approach which exposes the student to a range of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having [movement tracking](https://www.gc-forever.com) electronic cameras, also has RGB electronic [cameras](https://bgzashtita.es) to enable the robotic to manipulate an arbitrary item 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 could fix a Rubik's Cube. The robotic had the ability to solve 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](https://gogs.adamivarsson.com) (ADR), a simulation approach of creating gradually more hard environments. [ADR varies](https://git.the9grounds.com) from manual domain randomization by not needing a human to specify [randomization varieties](http://123.207.52.1033000). [169]
|
||||
<br>API<br>
|
||||
<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](http://www.zjzhcn.com) models established by OpenAI" to let developers get in touch with it for "any English language [AI](https://git.creeperrush.fun) job". [170] [171]
|
||||
<br>Text generation<br>
|
||||
<br>The company has promoted generative pretrained transformers (GPT). [172]
|
||||
<br>OpenAI's initial GPT model ("GPT-1")<br>
|
||||
<br>The initial paper on generative pre-training of a transformer-based language model was written by Alec Radford and his colleagues, and released in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative model of language could obtain world understanding and process long-range reliances by pre-training on a diverse corpus with long stretches of contiguous text.<br>
|
||||
<br>GPT-2<br>
|
||||
<br>Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language design and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative versions initially released to the public. The complete variation of GPT-2 was not right away released due to concern about possible abuse, including applications for writing fake news. [174] Some experts expressed uncertainty that GPT-2 posed a significant risk.<br>
|
||||
<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural fake news". [175] Other scientists, such as Jeremy Howard, warned 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 released the total version of the GPT-2 language design. [177] Several sites host interactive demonstrations of different 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, shown by GPT-2 attaining state-of-the-art accuracy 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 a little 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 using byte pair encoding. This allows 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 a without supervision transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were also trained). [186]
|
||||
<br>OpenAI specified that GPT-3 was successful at certain "meta-learning" tasks and might generalize the function 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 significantly enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the basic ability constraints of [predictive language](https://wiki.whenparked.com) models. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not right away launched to the general public for issues of possible abuse, although OpenAI prepared to enable gain access to through a paid cloud API after a two-month totally 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](http://1.117.194.115:10080) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the design can develop working code in over a lots shows languages, most effectively in Python. [192]
|
||||
<br>Several [concerns](https://gitlab.zogop.com) with glitches, design flaws and security vulnerabilities were mentioned. [195] [196]
|
||||
<br>GitHub Copilot has actually been implicated of producing copyrighted code, without any 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 revealed the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the updated innovation passed a simulated law school bar test with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise read, examine or [produce](https://geohashing.site) as much as 25,000 words of text, and write code in all major shows languages. [200]
|
||||
<br>Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based version, with the caution that GPT-4 retained some of the problems with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to expose different technical details and [raovatonline.org](https://raovatonline.org/author/lewismccrae/) stats about GPT-4, such as the accurate 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 cutting edge lead to voice, multilingual, and vision standards, setting new records in audio speech acknowledgment 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 version of GPT-4o [replacing](https://www.findnaukri.pk) 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 useful for enterprises, startups and developers seeking to automate services with [AI](http://durfee.mycrestron.com:3000) representatives. [208]
|
||||
<br>o1<br>
|
||||
<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have actually been designed to take more time to think of their actions, leading to higher accuracy. These designs are particularly reliable in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1[-preview](http://82.146.58.193) was changed by o1. [211]
|
||||
<br>o3<br>
|
||||
<br>On December 20, 2024, OpenAI revealed o3, the successor of the o1 [reasoning design](http://harimuniform.co.kr). OpenAI likewise unveiled o3-mini, a lighter and quicker version of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the opportunity to obtain early access to these designs. [214] The model is called o3 instead of o2 to [prevent confusion](http://artin.joart.kr) with telecoms providers O2. [215]
|
||||
<br>Deep research<br>
|
||||
<br>Deep research study is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to perform extensive web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty 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](https://jobs.cntertech.com) to analyze the semantic resemblance in 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 model that produces images from textual descriptions. [218] DALL-E uses 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 create matching images. It can develop images of practical objects ("a stained-glass window with an image of a blue strawberry") in addition to 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 announced DALL-E 2, an updated version of the design with more realistic results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new fundamental system for converting 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 powerful design better able to generate images from complex 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 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](https://idemnaposao.rs) upon short detailed triggers [223] in addition to extend [existing videos](https://www.securityprofinder.com) forwards or backwards in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.<br>
|
||||
<br>Sora's development group named it after the Japanese word for "sky", to symbolize its "limitless innovative capacity". [223] Sora's technology is an adaptation of the innovation behind the DALL · E 3 [text-to-image](https://www.joinyfy.com) model. [225] OpenAI trained the system utilizing publicly-available videos as well as copyrighted videos certified for that purpose, 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, mentioning that it could generate videos approximately one minute long. It also shared a technical report highlighting the techniques utilized to train the model, and the model's capabilities. [225] It acknowledged some of its shortcomings, including battles simulating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", but noted 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 demo, notable entertainment-industry figures have actually revealed considerable interest in the innovation's capacity. In an interview, actor/filmmaker Tyler [Perry expressed](https://uniondaocoop.com) his astonishment at the technology's capability to generate [reasonable video](https://malidiaspora.org) from text descriptions, mentioning its prospective to reinvent storytelling and content creation. He said that his enjoyment about Sora's possibilities was so strong that he had 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 recognition model. [228] It is trained on a large dataset of diverse audio and is likewise a multi-task design that can perform multilingual speech acknowledgment 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 generate tunes with 10 instruments in 15 designs. According to The Verge, a tune generated by MuseNet tends to start fairly however then fall under mayhem the longer it plays. [230] [231] In popular culture, preliminary applications 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 produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs tune samples. OpenAI specified the tunes "reveal local musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that duplicate" and that "there is a significant gap" between Jukebox and [photorum.eclat-mauve.fr](http://photorum.eclat-mauve.fr/profile.php?id=252314) human-generated music. The Verge mentioned "It's technically remarkable, even if the results seem like mushy versions of tunes that may feel familiar", while Business Insider specified "remarkably, some of the resulting tunes are catchy and sound genuine". [234] [235] [236]
|
||||
<br>User user interfaces<br>
|
||||
<br>Debate Game<br>
|
||||
<br>In 2018, OpenAI launched the Debate Game, which teaches makers to debate toy problems in front of a human judge. The [purpose](https://southwales.com) is to research whether such a method might assist in auditing [AI](https://gitea.dgov.io) decisions and in developing explainable [AI](https://vibefor.fun). [237] [238]
|
||||
<br>Microscope<br>
|
||||
<br>Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and nerve cell of eight neural network designs which are often studied in interpretability. [240] Microscope was created to evaluate the functions that form inside these neural networks quickly. The models included are AlexNet, VGG-19, different versions of Inception, and different [variations](http://135.181.29.1743001) of CLIP Resnet. [241]
|
||||
<br>ChatGPT<br>
|
||||
<br>Launched in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that offers a conversational user interface that permits users to ask concerns in natural language. The system then reacts with an answer within seconds.<br>
|
||||
Loading…
Reference in new issue