From 5ad02dad5cee6032b825fad5551b22d2eac4e15b Mon Sep 17 00:00:00 2001 From: Lidia Kim Date: Sat, 15 Feb 2025 02:20:07 +0000 Subject: [PATCH] Add 'The Verge Stated It's Technologically Impressive' --- ...tated-It%27s-Technologically-Impressive.md | 76 +++++++++++++++++++ 1 file changed, 76 insertions(+) create mode 100644 The-Verge-Stated-It%27s-Technologically-Impressive.md diff --git a/The-Verge-Stated-It%27s-Technologically-Impressive.md b/The-Verge-Stated-It%27s-Technologically-Impressive.md new file mode 100644 index 0000000..8ef457f --- /dev/null +++ b/The-Verge-Stated-It%27s-Technologically-Impressive.md @@ -0,0 +1,76 @@ +
Announced in 2016, Gym is an open-source Python library designed to facilitate the development of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://higgledy-piggledy.xyz) research study, making released research study more quickly reproducible [24] [144] while supplying users with an easy user interface for engaging with these environments. In 2022, brand-new developments of Gym have been moved to the library Gymnasium. [145] [146] +
Gym Retro
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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](http://harimuniform.co.kr). Prior RL research study focused mainly on optimizing agents to fix single jobs. Gym Retro gives the capability to generalize between video games with comparable ideas however different appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents initially do not have knowledge of how to even walk, however are offered the goals of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the [agents learn](http://118.190.145.2173000) how to adjust to changing conditions. When a representative is then eliminated from this virtual environment and put in a new virtual [environment](http://huaang6688.gnway.cc3000) with high winds, the representative braces to remain upright, recommending it had actually learned how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could develop an intelligence "arms race" that might increase a representative's ability to function even outside the context of the [competition](http://183.221.101.893000). [148] +
OpenAI 5
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OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that learn to play against human players at a high skill level entirely through [trial-and-error](https://workmate.club) algorithms. Before becoming a team of 5, the very first public demonstration happened at The International 2017, the annual premiere champion tournament for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually learned by playing against itself for two weeks of genuine time, which the learning software application was a step in the instructions of creating software that can deal with intricate jobs like a cosmetic surgeon. [152] [153] The system uses a form of support learning, as the bots discover with time by playing against themselves hundreds of times a day for months, and [surgiteams.com](https://surgiteams.com/index.php/User:CathleenMadison) are rewarded for actions such as [killing](http://218.17.2.1033000) an opponent and taking map goals. [154] [155] [156] +
By June 2018, the [capability](https://www.behavioralhealthjobs.com) of the bots broadened to play together as a complete group of 5, and they were able to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, [bio.rogstecnologia.com.br](https://bio.rogstecnologia.com.br/mia335414507) OpenAI Five played in 2 [exhibition matches](https://dev-members.writeappreviews.com) against professional players, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions 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 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] +
OpenAI 5's systems in Dota 2's bot gamer reveals the challenges of [AI](http://git.motr-online.com) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has demonstrated making use of deep reinforcement knowing (DRL) representatives to attain superhuman skills in Dota 2 [matches](https://git.tesinteractive.com). [166] +
Dactyl
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Developed in 2018, Dactyl utilizes maker learning to train a Shadow Hand, a human-like robot hand, to [manipulate](https://puzzle.thedimeland.com) physical objects. [167] It finds out entirely in simulation using the same RL algorithms and [training](https://git.newpattern.net) code as OpenAI Five. OpenAI tackled the things orientation issue by utilizing domain randomization, a simulation approach which exposes the student to a variety of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking video cameras, also has RGB cameras to permit the robot to control an arbitrary item by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might solve 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 design. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation approach of [producing progressively](http://git.hongtusihai.com) harder environments. ADR varies from manual domain randomization by not requiring a human to define randomization varieties. [169] +
API
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In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](http://charmjoeun.com) models developed by OpenAI" to let developers contact it for "any English language [AI](https://www.meetgr.com) job". [170] [171] +
Text generation
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The company has actually popularized generative pretrained transformers (GPT). [172] +
OpenAI's original GPT design ("GPT-1")
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The original paper on generative pre-training of a transformer-based language design was written by Alec Radford and his associates, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world knowledge and process long-range dependencies by pre-training on a diverse corpus with long stretches of adjoining text.
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GPT-2
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Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language model and the successor to OpenAI's initial [GPT model](https://members.advisorist.com) ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative versions initially launched to the public. The complete variation of GPT-2 was not instantly launched due to concern about prospective abuse, consisting of applications for writing fake news. [174] Some specialists revealed uncertainty that GPT-2 postured a substantial hazard.
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In response to GPT-2, the Allen Institute for Artificial Intelligence [reacted](https://wacari-git.ru) with a tool to find "neural fake news". [175] Other scientists, such as Jeremy Howard, cautioned of "the technology to totally 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 model. [177] Several sites host interactive presentations of various circumstances of GPT-2 and other [transformer models](https://interlinkms.lk). [178] [179] [180] +
GPT-2's authors argue not being watched language models to be general-purpose students, highlighted by GPT-2 attaining advanced precision and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not more trained on any task-specific input-output examples).
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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 problems encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters by encoding both individual characters and multiple-character tokens. [181] +
GPT-3
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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 mentioned that the complete version of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 designs with as few as 125 million parameters were likewise trained). [186] +
OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the function of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184] +
GPT-3 drastically enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or coming across the essential capability constraints of predictive language designs. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, compared to tens 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 general 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 private beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified specifically to Microsoft. [190] [191] +
Codex
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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](https://sound.descreated.com) powering the [code autocompletion](https://atomouniversal.com.br) tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the model can create working code in over a lots programming languages, a lot of effectively in Python. [192] +
Several [concerns](https://spiritustv.com) with problems, style defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been [accused](https://www.bakicicepte.com) of discharging copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would stop support for Codex API on March 23, 2023. [198] +
GPT-4
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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 updated technology 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 could likewise read, evaluate or create as much as 25,000 words of text, and compose code in all major programming languages. [200] +
Observers reported that the iteration of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has actually declined to expose numerous technical details and data about GPT-4, such as the accurate size of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision benchmarks, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) [benchmark compared](https://social.ppmandi.com) to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI launched GPT-4o mini, a smaller [variation](https://japapmessenger.com) of GPT-4o changing GPT-3.5 Turbo on the ChatGPT user [interface](https://lekoxnfx.com4000). 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 developers seeking to automate services with [AI](https://git.fpghoti.com) representatives. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been created to take more time to consider their responses, causing higher precision. These models are especially effective in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was changed by o1. [211] +
o3
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On December 20, 2024, OpenAI revealed o3, the successor of the o1 thinking design. OpenAI also revealed o3-mini, a lighter and much faster variation 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 researchers had the opportunity to obtain early access to these designs. [214] The model is called o3 rather than o2 to avoid confusion with [telecommunications providers](http://gitlab.ileadgame.net) O2. [215] +
Deep research study
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Deep research is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to carry out [comprehensive web](https://gitea.alexandermohan.com) browsing, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:SusieChipman) data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120] +
Image classification
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CLIP
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[Revealed](https://git.owlhosting.cloud) in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to evaluate the semantic similarity between text and [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:NikoleDeschamps) images. It can significantly be utilized for image category. [217] +
Text-to-image
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DALL-E
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Revealed in 2021, DALL-E is a Transformer model that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to analyze natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of an unfortunate capybara") and create matching images. It can develop pictures of sensible objects ("a stained-glass window with an image of a blue strawberry") along with 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.
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DALL-E 2
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In April 2022, OpenAI revealed DALL-E 2, an upgraded version of the design with more realistic outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new primary system for converting a text description into a 3-dimensional model. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, a more effective model much better able to images from complex descriptions without manual timely engineering and render intricate details like hands and text. [221] It was launched to the general public as a ChatGPT Plus feature in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video model that can generate videos based upon short detailed triggers [223] in addition to extend existing videos forwards or backwards in time. [224] It can generate videos with resolution up to 1920x1080 or 1080x1920. The maximal length of generated videos is [unidentified](http://www.asystechnik.com).
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Sora's development team called it after the Japanese word for "sky", to signify its "unlimited imaginative capacity". [223] Sora's technology is an adaptation of the innovation behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos licensed for that purpose, but did not expose the number or the precise sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it could generate videos as much as one minute long. It also shared a technical report highlighting the methods used to train the model, and the model's capabilities. [225] It acknowledged a few of its imperfections, including battles replicating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "excellent", but noted that they should have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, notable entertainment-industry figures have shown considerable interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's ability to generate realistic video from text descriptions, citing its potential to transform storytelling and content production. He said that his excitement about Sora's possibilities was so strong that he had chosen to stop briefly strategies for broadening his Atlanta-based film studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, Whisper is a general-purpose speech recognition model. [228] It is trained on a large dataset of diverse audio and is also a [multi-task](https://git.laser.di.unimi.it) design that can perform multilingual speech acknowledgment along with speech translation and language identification. [229] +
Music generation
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MuseNet
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Released in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in MIDI music files. It can generate songs with 10 [instruments](https://zkml-hub.arml.io) in 15 designs. According to The Verge, a [tune produced](https://jobs.ethio-academy.com) by [MuseNet](https://www.meditationgoodtip.com) tends to [start fairly](https://geniusactionblueprint.com) however 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 internet mental thriller Ben Drowned to develop music for the titular character. [232] [233] +
Jukebox
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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 [snippet](http://120.77.240.2159701) of lyrics and outputs tune samples. OpenAI specified the tunes "show regional musical coherence [and] follow conventional chord patterns" however acknowledged that the songs do not have "familiar larger musical structures such as choruses that repeat" and that "there is a considerable space" in between Jukebox and human-generated music. The Verge mentioned "It's highly impressive, even if the outcomes seem like mushy variations of tunes that may feel familiar", while Business Insider specified "remarkably, a few of the resulting tunes are appealing and sound legitimate". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, OpenAI released the Debate Game, which teaches devices to dispute toy problems in front of a [human judge](https://kommunalwiki.boell.de). The function is to research study whether such a technique might help in auditing [AI](https://www.basketballshoecircle.com) choices and in establishing explainable [AI](https://www.top5stockbroker.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and neuron of 8 neural network models which are often studied in interpretability. [240] Microscope was produced to analyze the features that form inside these neural networks easily. The designs included are AlexNet, VGG-19, various variations of Inception, and different [variations](http://git.jaxc.cn) of CLIP Resnet. [241] +
ChatGPT
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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 a response within seconds.
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