From f8515428a5e21150b6433f51183e2762e8e295a2 Mon Sep 17 00:00:00 2001 From: muoilemmon397 Date: Thu, 10 Apr 2025 04:44:06 +0200 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..633eaba --- /dev/null +++ b/The-Verge-Stated-It%27s-Technologically-Impressive.md @@ -0,0 +1,76 @@ +
Announced in 2016, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:Rosalyn55R) Gym is an open-source Python library created to help with the development of support learning algorithms. It aimed to standardize how environments are defined in [AI](http://thegrainfather.com) research study, making published research study more quickly reproducible [24] [144] while offering users with a simple user interface for [interacting](https://www.eruptz.com) with these environments. In 2022, new developments of Gym have actually been [transferred](http://94.191.73.383000) 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 study on video games [147] using RL algorithms and research . Prior RL research study focused mainly on optimizing representatives to fix [single tasks](https://setiathome.berkeley.edu). Gym Retro gives the capability to generalize in 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 robot representatives initially lack understanding of how to even walk, however are offered the objectives of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing process, the representatives find out how to adapt to [changing conditions](https://git.goolink.org). When an agent is then gotten rid of from this virtual environment and positioned in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents could produce an intelligence "arms race" that might increase an agent's ability to work even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a group of 5 OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that discover to play against human gamers at a high ability level totally through experimental algorithms. Before becoming a group of 5, the very first public presentation occurred at The International 2017, the annual premiere champion competition for the game, where Dendi, an expert Ukrainian player, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman [explained](https://sc.e-path.cn) that the bot had learned by playing against itself for two weeks of real time, which the knowing software was an action in the instructions of producing software application that can manage intricate jobs like a surgeon. [152] [153] The system utilizes a form of reinforcement learning, as the bots learn over time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an opponent and taking map objectives. [154] [155] [156] +
By June 2018, the ability of the bots expanded to play together as a complete team of 5, and they had the ability to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two [exhibit matches](https://www.etymologiewebsite.nl) against [professional](http://ufidahz.com.cn9015) players, but ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 total video games in a four-day open online competition, winning 99.4% of those games. [165] +
OpenAI 5's mechanisms in Dota 2's bot player reveals the difficulties of [AI](http://code.chinaeast2.cloudapp.chinacloudapi.cn) systems in multiplayer online [battle arena](http://git.idiosys.co.uk) (MOBA) video games and how OpenAI Five has actually shown making use of deep support [knowing](https://tapeway.com) (DRL) agents to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses device discovering 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 code as OpenAI Five. OpenAI dealt with the object orientation problem by using domain randomization, a simulation method which exposes the student to a variety of experiences instead of [attempting](https://nbc.co.uk) to fit to truth. The set-up for Dactyl, aside from having motion tracking electronic cameras, also has RGB cams to allow the robotic to control an approximate item by seeing it. In 2018, OpenAI showed that the system was able to [control](https://candidates.giftabled.org) a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl could resolve a [Rubik's Cube](https://ready4hr.com). The robotic had the ability 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 method of producing gradually more tough environments. ADR differs from manual domain randomization by not requiring a human to define randomization ranges. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](https://git.hxps.ru) designs established by OpenAI" to let designers contact it for "any English language [AI](http://jobasjob.com) job". [170] [171] +
Text generation
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The business has popularized generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("GPT-1")
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The original paper on [generative pre-training](https://nakenterprisetv.com) of a transformer-based language model was written by Alec Radford and his associates, and published in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative design of language might obtain world knowledge and process long-range dependences 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 an unsupervised transformer language design and the [successor](https://git.amic.ru) to OpenAI's initial GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative versions initially launched to the public. The full version of GPT-2 was not instantly launched due to issue about potential misuse, including applications for composing phony news. [174] Some specialists expressed uncertainty that GPT-2 posed a significant danger.
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In action to GPT-2, the Allen Institute for Artificial Intelligence [responded](https://caringkersam.com) with a tool to identify "neural phony news". [175] Other researchers, such as Jeremy Howard, alerted of "the technology to completely 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 launched the total variation of the GPT-2 language design. [177] Several [websites](http://39.101.167.1953003) host interactive presentations of various instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue without supervision language designs to be general-purpose learners, illustrated by GPT-2 attaining state-of-the-art accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not more trained on any task-specific input-output examples).
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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 issues 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 a not being watched transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI mentioned that the full version of GPT-3 contained 175 billion criteria, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as couple of as 125 million parameters were also trained). [186] +
OpenAI specified that GPT-3 prospered 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 knowing in between [English](http://1.14.125.63000) and Romanian, and in between English and German. [184] +
GPT-3 considerably improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 required a number of thousand petaflop/s-days [b] of calculate, [compared](https://links.gtanet.com.br) to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly launched to the general public for issues of possible abuse, although OpenAI prepared to permit gain access to through a paid cloud API after a two-month free private beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed 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](https://gitea.ravianand.me) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://macphersonwiki.mywikis.wiki) 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 dozen programs languages, a lot of [efficiently](http://106.52.134.223000) in Python. [192] +
Several concerns with glitches, style defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been implicated of producing copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would discontinue support for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, [larsaluarna.se](http://www.larsaluarna.se/index.php/User:KaseyA400699235) 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the upgraded innovation passed a simulated law school bar exam 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 check out, examine or generate up to 25,000 words of text, and write code in all major programs languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has actually declined to expose various technical details and stats about GPT-4, such as the accurate size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained state-of-the-art outcomes in voice, multilingual, and vision standards, 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 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 expects it to be especially useful for enterprises, startups and developers looking for to automate services with [AI](https://dztrader.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 think of their responses, leading to higher precision. These models are particularly efficient in science, coding, and [thinking](https://code.in-planet.net) jobs, and were made available to ChatGPT Plus and [raovatonline.org](https://raovatonline.org/author/hrqjeannine/) Staff member. [209] [210] In December 2024, o1-preview was changed by o1. [211] +
o3
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On December 20, 2024, [OpenAI unveiled](http://git.datanest.gluc.ch) o3, the follower of the o1 thinking model. OpenAI likewise revealed o3-mini, a [lighter](http://www.thegrainfather.co.nz) and much faster version of OpenAI o3. Since December 21, 2024, this design is not available for public usage. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the opportunity to obtain early access to these models. [214] The model is called o3 instead of o2 to prevent confusion with telecommunications companies O2. [215] +
Deep research study
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Deep research is an agent established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform extensive web browsing, information analysis, and synthesis, providing detailed [reports](https://seenoor.com) within a timeframe of 5 to 30 minutes. [216] With searching and Python tools enabled, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) standard. [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 examine the semantic resemblance between text and 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 version of GPT-3 to translate natural language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and generate corresponding images. It can develop images of sensible items ("a stained-glass window with an image of a blue strawberry") as well as [objects](https://collegetalks.site) 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 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 new rudimentary system for transforming a text description into a 3-dimensional model. [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more effective design much better able to generate images from intricate descriptions without manual timely engineering and render complicated details like hands and text. [221] It was launched to the public as a ChatGPT Plus [feature](https://51.68.46.170) in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video design that can produce videos based on brief detailed prompts [223] along with extend existing videos forwards or backwards in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.
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Sora's development team called it after the Japanese word for "sky", to represent 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](http://47.107.80.2363000) licensed for that function, but did not expose the number or the exact sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, mentioning that it could create videos approximately one minute long. It likewise shared a technical report highlighting the approaches used to train the design, and the design's capabilities. [225] It acknowledged some of its drawbacks, consisting of battles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", but kept in mind that they need to have been cherry-picked and might not [represent Sora's](http://gungang.kr) typical output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, [notable entertainment-industry](http://www.vokipedia.de) figures have shown significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's capability to create sensible video from text descriptions, mentioning its prospective to transform storytelling and material development. He said that his excitement about Sora's possibilities was so strong that he had actually decided to pause strategies for broadening his Atlanta-based motion picture studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, Whisper is a general-purpose speech recognition design. [228] It is trained on a big dataset of varied audio and is also a multi-task model that can carry out multilingual speech recognition as well as 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 [predict subsequent](http://gitlabhwy.kmlckj.com) musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 styles. According to The Verge, a tune generated by [MuseNet](http://117.72.17.1323000) tends to begin fairly however then fall into chaos the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the internet psychological thriller Ben [Drowned](http://165.22.249.528888) to create 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 bit of lyrics and outputs song samples. OpenAI specified the tunes "reveal regional musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" which "there is a significant gap" in between Jukebox and human-generated music. The Verge stated "It's highly impressive, even if the outcomes sound like mushy versions of songs that might feel familiar", while Business Insider mentioned "remarkably, a few of the resulting tunes are memorable and sound legitimate". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI released the Debate Game, which teaches machines to debate toy issues in front of a human judge. The function is to research whether such an approach might assist in auditing [AI](http://47.113.115.239:3000) choices and in establishing explainable [AI](https://www.yewiki.org). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every [substantial layer](http://carvis.kr) and nerve cell of 8 neural network models which are often studied in interpretability. [240] Microscope was developed to examine the features 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] +
ChatGPT
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Launched in November 2022, [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:LettieWhipple7) ChatGPT is an artificial intelligence tool developed on top of GPT-3 that provides a conversational user interface that allows users to ask concerns in [natural language](https://aubameyangclub.com). The system then reacts with an answer within seconds.
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