From 7c5607590f25d9a3fa8753b38d9866ce34ea21f5 Mon Sep 17 00:00:00 2001 From: maryannshackel Date: Fri, 7 Feb 2025 02:14:41 -0600 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..c6d2b08 --- /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 developed to help with the development of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://eliteyachtsclub.com) research, making released research more quickly reproducible [24] [144] while supplying users with an easy interface for engaging with these environments. In 2022, new advancements of Gym have actually been moved to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support knowing (RL) research on video games [147] using RL algorithms and research study [generalization](https://coopervigrj.com.br). Prior RL research study focused mainly on optimizing agents to resolve single tasks. Gym Retro offers the capability to generalize between video games with similar principles however various looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where [humanoid metalearning](https://pattondemos.com) robot agents initially lack knowledge of how to even walk, but are provided the goals of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial learning process, the [agents discover](http://8.217.113.413000) how to adapt to altering conditions. When a representative is then gotten rid of from this virtual environment and positioned in a brand-new virtual environment with high winds, the agent 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 might produce an intelligence "arms race" that might increase a representative's ability to operate even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five computer [game Dota](https://dongochan.id.vn) 2, that discover to play against human gamers at a high skill level completely through experimental algorithms. Before becoming a team of 5, the very first public presentation took place at The International 2017, the [yearly premiere](https://workbook.ai) champion competition for the video game, where Dendi, a [professional Ukrainian](https://jobportal.kernel.sa) gamer, lost against a bot in a live one-on-one matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had learned by playing against itself for two weeks of actual time, which the learning software was an action in the direction of developing software that can manage complex jobs like a cosmetic surgeon. [152] [153] The system utilizes a form of support knowing, as the bots discover with time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an enemy and taking map objectives. [154] [155] [156] +
By June 2018, the ability of the bots expanded to play together as a full team of 5, and they had the ability to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 [exhibition matches](https://gitea.itskp-odense.dk) against expert players, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:LeilaniCable73) but ended 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' last public appearance came later on that month, where they played in 42,729 overall games in a four-day open online competition, winning 99.4% of those games. [165] +
OpenAI 5['s systems](http://xn--289an1ad92ak6p.com) in Dota 2's bot gamer reveals the [challenges](https://mssc.ltd) of [AI](https://git.lgoon.xyz) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually shown the usage of deep support learning (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, [Dactyl utilizes](https://peekz.eu) machine finding out to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It discovers entirely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation problem by utilizing domain randomization, a simulation approach which exposes the student to a range of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having motion tracking electronic cameras, also has RGB electronic cameras to permit the robotic to control an arbitrary things by seeing it. In 2018, OpenAI showed that the system had the ability to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robotic had the ability to solve the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to perturbations by [utilizing Automatic](http://47.120.20.1583000) [Domain Randomization](https://fromkorea.kr) (ADR), a simulation technique of producing progressively harder environments. ADR differs from manual domain randomization by not needing a human to define randomization ranges. [169] +
API
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In June 2020, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:SusieGoodwin) OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](https://phpcode.ketofastlifestyle.com) designs developed by OpenAI" to let [developers](http://47.102.102.152) get in touch with it for "any English language [AI](https://www.worlddiary.co) job". [170] [171] +
Text generation
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The business has actually promoted generative pretrained transformers (GPT). [172] +
OpenAI's original GPT design ("GPT-1")
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The initial paper on generative pre-training of a transformer-based [language model](https://famenest.com) was composed by Alec Radford and his coworkers, 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 dependences by pre-training on a diverse corpus with long stretches of contiguous 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](https://git.cyu.fr) and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just limited demonstrative versions [initially](https://nationalcarerecruitment.com.au) launched to the general public. The complete version of GPT-2 was not instantly released due to concern about possible misuse, including applications for composing phony news. [174] Some experts revealed uncertainty that GPT-2 positioned a substantial danger.
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In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to identify "neural fake news". [175] Other scientists, such as Jeremy Howard, warned of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush 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 different instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being [watched language](https://www.jobsalert.ai) models to be general-purpose learners, shown by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not more trained on any examples).
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The corpus it was trained on, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents certain concerns encoding [vocabulary](https://gitlab.rlp.net) 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 a not being watched transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 designs with as few as 125 million criteria were also trained). [186] +
OpenAI stated that GPT-3 was successful at certain "meta-learning" jobs and might generalize the function of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning between English and Romanian, and in between English and German. [184] +
GPT-3 dramatically improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of [language designs](https://82.65.204.63) might be approaching or coming across the essential capability constraints of predictive language models. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 [trained model](http://8.130.72.6318081) was not right away launched to the public for issues of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a two-month free personal beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified exclusively to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has additionally been [trained](http://47.102.102.152) on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://47.120.20.158:3000) powering the [code autocompletion](https://teachinthailand.org) tool [GitHub Copilot](https://arbeitsschutz-wiki.de). [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the model can produce working code in over a lots programs languages, most effectively in Python. [192] +
Several issues with glitches, design defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been [accused](https://www.meetgr.com) of giving off copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would cease assistance for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the [updated technology](http://release.rupeetracker.in) passed a simulated law school bar test with a score around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, analyze or produce up to 25,000 words of text, and write code in all major programs languages. [200] +
[Observers](https://www.bridgewaystaffing.com) reported that the model 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 issues with earlier modifications. [201] GPT-4 is also [capable](https://git.logicp.ca) of taking images as input on ChatGPT. [202] OpenAI has [decreased](https://intermilanfansclub.com) to reveal various technical details and stats about GPT-4, such as the precise 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 advanced lead to voice, multilingual, and vision criteria, setting brand-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] +
On July 18, 2024, OpenAI released GPT-4o mini, a smaller variation of GPT-4o changing GPT-3.5 Turbo on the [ChatGPT](https://git.aaronmanning.net) 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 particularly useful for business, start-ups and developers looking for [disgaeawiki.info](https://disgaeawiki.info/index.php/User:MariaKuehner) to automate services with [AI](https://castingnotices.com) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1[-preview](https://git.gumoio.com) and o1-mini designs, which have been developed to take more time to consider their responses, leading to greater precision. These designs are especially efficient in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was [changed](http://123.111.146.2359070) by o1. [211] +
o3
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On December 20, 2024, OpenAI revealed o3, the successor of the o1 thinking model. OpenAI likewise unveiled o3-mini, a lighter and quicker variation of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:ChantalKopsen2) they are checking 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 rather than o2 to avoid confusion with telecommunications services service provider O2. [215] +
Deep research
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Deep research study is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform substantial web browsing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools allowed, it [reached](https://gitea.ecommercetools.com.br) a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] +
Image category
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CLIP
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Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to analyze the semantic resemblance between text and images. It can notably be used 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 design that [produces](https://tiktack.socialkhaleel.com) 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 purse formed like a pentagon" or "an isometric view of an unfortunate capybara") and generate matching images. It can produce pictures of reasonable objects ("a stained-glass window with an image of a blue strawberry") as well as objects that do not exist in reality ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.
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DALL-E 2
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In April 2022, OpenAI announced DALL-E 2, an upgraded variation of the design with more reasonable results. [219] In December 2022, OpenAI published on GitHub software for Point-E, a brand-new fundamental system for [converting](http://175.24.176.23000) 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 design much better able to create images from complicated descriptions without manual prompt 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 create videos based upon short detailed prompts [223] in addition to extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.
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Sora's development team named it after the Japanese word for "sky", to symbolize its "unlimited creative potential". [223] Sora's innovation 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 certified for that function, however did not reveal the number or the exact sources of the videos. [223] +
[OpenAI demonstrated](http://82.223.37.137) some Sora-created high-definition videos to the general public on February 15, 2024, [stating](http://git.superiot.net) that it could create videos as much as one minute long. It likewise shared a technical report [highlighting](https://mssc.ltd) the approaches used to train the design, and the model's abilities. [225] It acknowledged a few of its shortcomings, consisting of battles mimicing complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", however noted that they should have been cherry-picked and may not represent Sora's normal output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, significant entertainment-industry figures have revealed significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's ability to create sensible video from text descriptions, mentioning its potential to revolutionize storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had chosen to stop briefly prepare for [wiki.whenparked.com](https://wiki.whenparked.com/User:Bernadette71H) expanding 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 acknowledgment model. [228] It is trained on a large dataset of varied audio and is also a multi-task model that can perform multilingual speech acknowledgment along with speech translation and [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:KarissaGleason) language recognition. [229] +
Music generation
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MuseNet
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Released in 2019, MuseNet is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 designs. According to The Verge, [gratisafhalen.be](https://gratisafhalen.be/author/rebbeca9609/) a song generated by MuseNet tends to start fairly but then fall into mayhem the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for the web psychological 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 generate music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs tune samples. [OpenAI stated](https://git.lgoon.xyz) the songs "reveal regional musical coherence [and] follow standard chord patterns" but acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" which "there is a considerable gap" between Jukebox and [human-generated music](http://macrocc.com3000). The Verge stated "It's highly outstanding, even if the outcomes seem like mushy versions of songs that might feel familiar", while Business Insider specified "remarkably, a few of the resulting songs are appealing and sound legitimate". [234] [235] [236] +
User user interfaces
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Debate Game
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In 2018, OpenAI launched the Debate Game, which teaches devices to [debate toy](https://www.gritalent.com) problems in front of a human judge. The purpose is to research whether such a technique might assist in auditing [AI](http://106.55.3.105:20080) decisions and in developing explainable [AI](http://39.99.134.165:8123). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and nerve cell of eight neural network designs which are typically studied in interpretability. [240] Microscope was developed to examine the functions that form inside these neural networks easily. The models included are AlexNet, VGG-19, different variations of Inception, and different versions of CLIP Resnet. [241] +
ChatGPT
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[Launched](http://47.101.131.2353000) in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that offers a conversational interface that permits users to ask questions in natural language. The system then reacts with a response within seconds.
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