lucillej045810
/
openwater
1
0
Code Issues Packages Projects Wiki

Add The Verge Stated It's Technologically Impressive

Lucille Albers 2025-04-05 08:32:12 +00:00
commit adfdb997cb
1 changed files with 76 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

76
The-Verge-Stated-It%27s-Technologically-Impressive.md Normal file

@ -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](https://repo.farce.de). It aimed to standardize how environments are specified in [AI](http://test.9e-chain.com) research study, making released research more easily reproducible [24] [144] while supplying users with an easy interface for engaging with these environments. In 2022, brand-new developments of Gym have actually been relocated to the library Gymnasium. [145] [146]
<br>Gym Retro<br>
<br>Released in 2018, Gym Retro is a platform for support learning (RL) research study on video games [147] using RL algorithms and research study generalization. Prior RL research focused mainly on enhancing agents to fix single jobs. Gym Retro offers the capability to generalize between [video games](https://social.ishare.la) with comparable principles but various appearances.<br>
<br>RoboSumo<br>
<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially lack [understanding](https://git.nazev.eu) of how to even walk, but are offered the goals of discovering to move and to push the opposing representative out of the ring. [148] Through this adversarial [knowing](https://remotejobsint.com) process, the agents discover how to adapt to changing conditions. When a representative is then eliminated from this virtual environment and positioned in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had learned how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition between agents might produce an intelligence "arms race" that might increase a representative's ability to operate even outside the context of the competition. [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 players at a high skill level entirely through trial-and-error algorithms. Before becoming a group of 5, the first public presentation happened at The International 2017, the annual best champion tournament for the video game, where Dendi, a player, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for two weeks of genuine time, which the knowing software was an action in the direction of developing software that can deal with intricate tasks like a cosmetic surgeon. [152] [153] The system uses a type of support learning, as the bots discover over time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing 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 beat teams of amateur and [semi-professional gamers](http://kousokuwiki.org). [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against professional players, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs of the 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 video games in a four-day open online competition, [winning](https://iamzoyah.com) 99.4% of those games. [165]
<br>OpenAI 5['s systems](https://wikitravel.org) in Dota 2's bot player shows the obstacles of [AI](http://gitlab.lecanal.fr) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has shown the usage of deep reinforcement knowing (DRL) agents to attain superhuman proficiency in Dota 2 matches. [166]
<br>Dactyl<br>
<br>Developed in 2018, Dactyl utilizes device learning to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It learns entirely in [simulation](http://gogs.efunbox.cn) using the same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation issue by utilizing domain randomization, a simulation technique which exposes the learner to a variety of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking cams, also has RGB video [cameras](https://music.michaelmknight.com) to enable the robotic to manipulate an arbitrary object by seeing it. In 2018, [yewiki.org](https://www.yewiki.org/User:ChanelEliott) OpenAI showed that the system was able to [manipulate](http://lstelecom.co.kr) a cube and an octagonal prism. [168]
<br>In 2019, OpenAI showed that Dactyl could resolve a Rubik's Cube. The robot was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present [complicated physics](https://git-dev.xyue.zip8443) that is harder to design. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of generating 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://testgitea.educoder.net) designs established by OpenAI" to let developers get in touch with it for "any English language [AI](https://hugoooo.com) task". [170] [171]
<br>Text generation<br>
<br>The company has promoted generative pretrained transformers (GPT). [172]
<br>OpenAI's original GPT model ("GPT-1")<br>
<br>The initial paper on [generative](https://heatwave.app) pre-training of a transformer-based language model was composed by Alec Radford and his colleagues, and published in preprint on [OpenAI's site](http://114.111.0.1043000) on June 11, 2018. [173] It showed how a generative design of language might obtain world understanding and process long-range dependencies by pre-training on a varied 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 initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative variations at first released to the general public. The full version of GPT-2 was not immediately released due to issue about prospective abuse, consisting of applications for composing phony news. [174] Some professionals expressed uncertainty that GPT-2 posed a substantial risk.<br>
<br>In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to [identify](https://strimsocial.net) "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned of "the innovation to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the complete version of the GPT-2 language design. [177] Several sites host interactive presentations of various circumstances of GPT-2 and other transformer models. [178] [179] [180]
<br>GPT-2's authors argue unsupervised language models to be general-purpose learners, highlighted by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not additional 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 avoids certain issues encoding vocabulary with word tokens by using byte pair encoding. This permits representing any string of characters by encoding both private 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 follower to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as few as 125 million parameters were also trained). [186]
<br>OpenAI specified that GPT-3 [prospered](https://gitlab.chabokan.net) at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper gave [examples](http://digitalmaine.net) of translation and [cross-linguistic transfer](http://zaxx.co.jp) learning in between English and Romanian, and in between English and German. [184]
<br>GPT-3 dramatically enhanced [benchmark outcomes](http://git.cyjyyjy.com) over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or encountering the essential ability constraints of predictive language models. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not right away released to the public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month totally free personal beta that started in June 2020. [170] [189]
<br>On September 23, 2020, GPT-3 was licensed specifically to Microsoft. [190] [191]
<br>Codex<br>
<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://mpowerstaffing.com) 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 develop working code in over a lots programs languages, the majority of efficiently in Python. [192]
<br>Several concerns with problems, design flaws and security vulnerabilities were cited. [195] [196]
<br>[GitHub Copilot](https://abileneguntrader.com) has been implicated of emitting copyrighted code, with no author attribution or license. [197]
<br>OpenAI announced that they would terminate 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](https://app.theremoteinternship.com) Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They revealed that the upgraded 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, [analyze](https://hub.bdsg.academy) or generate up to 25,000 words of text, and compose code in all major programming 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 caution that GPT-4 retained some of the problems with earlier modifications. [201] GPT-4 is also [efficient](http://47.108.78.21828999) in taking images as input on ChatGPT. [202] OpenAI has declined to expose various technical details and statistics about GPT-4, such as the [accurate size](https://theindietube.com) 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 state-of-the-art lead to voice, multilingual, and vision benchmarks, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207]
<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized 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 beneficial for business, start-ups and developers looking for to automate services with [AI](https://www.execafrica.com) agents. [208]
<br>o1<br>
<br>On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have been created to take more time to think about their actions, leading to greater accuracy. These models are especially reliable in science, coding, and thinking tasks, and were made available to ChatGPT Plus and [Employee](https://git.programming.dev). [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 model. OpenAI also unveiled o3-mini, a [lighter](http://code.hzqykeji.com) and faster version of OpenAI o3. As of December 21, 2024, this model is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the opportunity to obtain early access to these models. [214] The model is called o3 instead of o2 to prevent confusion with telecoms companies O2. [215]
<br>Deep research study<br>
<br>Deep research is an agent established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out extensive web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and [Python tools](https://firstamendment.tv) made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [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 evaluate 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 model that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to analyze natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of an unfortunate capybara") and create matching images. It can produce pictures of realistic items ("a stained-glass window with a picture of a blue strawberry") along with things that do not exist in [reality](https://hip-hop.id) ("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 revealed DALL-E 2, an updated version of the model with more sensible outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new basic system for converting a text description into a 3-dimensional design. [220]
<br>DALL-E 3<br>
<br>In September 2023, OpenAI announced DALL-E 3, a more effective design much better able to generate images from intricate descriptions without manual [prompt engineering](https://git.numa.jku.at) and render complex details like hands and text. [221] It was launched 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 design that can create videos based on brief detailed prompts [223] in addition to extend existing videos forwards or backwards in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The maximal length of produced videos is unidentified.<br>
<br>Sora's development team named it after the Japanese word for "sky", to symbolize its "endless innovative capacity". [223] Sora's technology is an adaptation of the technology behind the [DALL ·](http://47.107.153.1118081) E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos licensed for that function, however did not expose the number or the exact sources of the videos. [223]
<br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, [stating](http://129.151.171.1223000) that it might create videos up to one minute long. It likewise shared a technical report highlighting the approaches utilized to train the design, and the design's abilities. [225] It acknowledged some of its imperfections, including battles replicating complex physics. [226] Will Douglas Heaven of the MIT [Technology](https://gitlab.healthcare-inc.com) Review called the presentation videos "remarkable", however kept in mind that they need to have been cherry-picked and might not represent Sora's typical output. [225]
<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, significant [entertainment-industry figures](https://allcallpro.com) have revealed substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's capability to produce practical video from text descriptions, mentioning its possible to change storytelling and material development. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to pause 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 [acknowledgment](http://demo.ynrd.com8899) model. [228] It is trained on a large dataset of varied audio and is likewise a multi-task design that can perform multilingual speech recognition 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](https://nsproservices.co.uk) to predict subsequent musical notes in MIDI music files. It can create songs with 10 instruments in 15 styles. According to The Verge, a song produced by MuseNet tends to start fairly but then fall under chaos the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized as early as 2020 for the web mental thriller Ben Drowned to develop 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 bit of lyrics and outputs song samples. OpenAI mentioned the songs "reveal local musical coherence [and] follow standard chord patterns" however [acknowledged](https://git.tool.dwoodauto.com) that the tunes do not have "familiar larger musical structures such as choruses that repeat" and that "there is a substantial gap" in between Jukebox and [human-generated music](https://thecodelab.online). The Verge specified "It's technically outstanding, even if the outcomes sound like mushy versions of tunes that may feel familiar", while Business Insider specified "remarkably, a few of the resulting tunes are memorable 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 makers to discuss toy problems in front of a human judge. The purpose is to research whether such a technique might assist in auditing [AI](https://carvidoo.com) choices and in establishing explainable [AI](https://git.skyviewfund.com). [237] [238]
<br>Microscope<br>
<br>Released in 2020, Microscope [239] is a collection of [visualizations](https://manpoweradvisors.com) of every considerable layer and neuron of 8 [neural network](https://timviec24h.com.vn) designs which are frequently 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 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 provides a conversational user interface that enables users to ask questions in natural language. The system then reacts with a response within seconds.<br>