From e3614a35ddef8be4cd8955eda22394ae6468a6c5 Mon Sep 17 00:00:00 2001 From: mireyavnk94266 Date: Wed, 9 Apr 2025 19:02:38 +0800 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..d71dc31 --- /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 created to facilitate the advancement of support knowing [algorithms](https://lepostecanada.com). It aimed to standardize how environments are specified in [AI](https://git.codebloq.io) research, making released research more quickly reproducible [24] [144] while providing users with a basic interface for connecting with these environments. In 2022, brand-new developments 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](https://www.xcoder.one) for reinforcement knowing (RL) research on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on optimizing agents to solve [single jobs](https://www.cittamondoagency.it). Gym Retro gives the capability to generalize in between games with comparable principles but different looks.
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RoboSumo
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[Released](https://krazzykross.com) in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents initially do not have knowledge of how to even walk, but are given the goals of finding out to move and to press the opposing agent out of the ring. [148] Through this adversarial learning procedure, the agents learn how to adapt to changing conditions. When a representative is then eliminated from this virtual environment and put in a brand-new [virtual environment](https://youtubegratis.com) with high winds, the agent braces to remain upright, recommending it had actually learned how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents might develop an intelligence "arms race" that could increase a representative's capability to work even outside the context of the competitors. [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 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 [yearly premiere](http://www5a.biglobe.ne.jp) championship tournament for [it-viking.ch](http://it-viking.ch/index.php/User:JanetteGreig1) the video 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 discovered by playing against itself for 2 weeks of real time, which the learning software was a step in the direction of producing software that can deal with complex tasks like a [cosmetic surgeon](https://wiki.asexuality.org). [152] [153] The system uses a type of support knowing, [wakewiki.de](https://www.wakewiki.de/index.php?title=Benutzer:BettyeSilvia) as the bots discover gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an enemy and taking map goals. [154] [155] [156] +
By June 2018, the capability of the bots broadened to play together as a complete team of 5, and they had the ability to defeat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against professional players, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:AlbertaHemmant6) but ended up losing both video 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 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] +
OpenAI 5's mechanisms in Dota 2's bot gamer reveals the difficulties of [AI](https://gitstud.cunbm.utcluj.ro) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has demonstrated the use of deep support knowing (DRL) representatives to attain superhuman [proficiency](https://121gamers.com) in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes machine [finding](https://wikibase.imfd.cl) out to train a Shadow Hand, a human-like robotic hand, to manipulate physical items. [167] It learns entirely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation issue by utilizing domain randomization, a simulation method 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 cams, also has RGB electronic cameras to enable the robot to manipulate an approximate things by seeing it. In 2018, OpenAI revealed that the system had the ability to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might solve a Rubik's Cube. The robot had the ability to solve 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 toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of producing gradually harder environments. ADR varies from manual [domain randomization](https://stagingsk.getitupamerica.com) by not needing a human to specify randomization varieties. [169] +
API
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In June 2020, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2672496) OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](https://www.happylove.it) models developed by OpenAI" to let designers call on it for "any English language [AI](https://endhum.com) job". [170] [171] +
Text generation
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The company has popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT design ("GPT-1")
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The initial paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his associates, and published in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative design of language might 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 and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative variations initially [launched](https://git.kuyuntech.com) to the public. The complete variation of GPT-2 was not instantly launched due to concern about possible misuse, consisting of applications for [composing phony](https://smarthr.hk) news. [174] Some professionals revealed uncertainty that GPT-2 presented a considerable hazard.
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In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to find "neural fake news". [175] Other researchers, such as Jeremy Howard, alerted of "the technology 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 released the complete version of the GPT-2 language design. [177] Several websites host interactive presentations of various instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue unsupervised language models to be general-purpose students, highlighted by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot jobs (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 somewhat 40 [gigabytes](https://bantooplay.com) of text from [URLs shared](http://8.222.216.1843000) in Reddit submissions with a minimum of 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both private 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 design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full version of GPT-3 contained 175 billion specifications, [184] two orders of magnitude bigger 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] +
OpenAI stated that GPT-3 succeeded at certain "meta-learning" tasks and could generalize the purpose 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 enhanced benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or coming across the fundamental ability constraints of predictive language models. [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 model. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately [released](http://orcz.com) to the public for issues of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month complimentary personal beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed 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://letsstartjob.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [private](https://dlya-nas.com) beta. [194] According to OpenAI, the design can create working code in over a dozen programs languages, most effectively in Python. [192] +
Several issues with problems, style flaws and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has actually been [accused](http://plus-tube.ru) of producing copyrighted code, without any 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 announced the release of Generative Pre-trained Transformer 4 (GPT-4), capable of [accepting text](https://corvestcorp.com) or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar examination with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, analyze or produce up to 25,000 words of text, and write code in all major programs languages. [200] +
Observers reported that the iteration of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has declined to expose different technical details and statistics about GPT-4, such as the exact size of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and released GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained advanced results in voice, multilingual, and vision criteria, setting new records in audio speech recognition 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 launched GPT-4o mini, a smaller sized variation of GPT-4o replacing 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 anticipates it to be especially helpful for business, startups and developers looking for to automate services with [AI](https://frce.de) representatives. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have actually been created to take more time to believe about their responses, resulting in higher precision. These designs are particularly reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [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 reasoning design. OpenAI likewise revealed o3-mini, a lighter and much faster variation of OpenAI o3. Since December 21, 2024, this design is not available for public usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, safety 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 with [telecoms](https://www.iqbagmarket.com) providers O2. [215] +
Deep research study
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Deep research is a representative established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out comprehensive web surfing, data analysis, and synthesis, providing detailed reports within a of 5 to thirty minutes. [216] With searching and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] +
Image classification
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CLIP
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[Revealed](https://wema.redcross.or.ke) in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to evaluate the semantic similarity in between text and images. It can significantly be used for image classification. [217] +
Text-to-image
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DALL-E
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Revealed in 2021, DALL-E is a Transformer model that develops 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 shaped like a pentagon" or "an isometric view of an unfortunate capybara") and create corresponding images. It can produce images of sensible things ("a stained-glass window with a picture of a blue strawberry") as well as things that do not exist in truth ("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 updated variation of the model with more sensible outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new basic 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 powerful design better able to create images from [complex descriptions](https://vibestream.tv) without manual prompt engineering and [render complicated](http://1.15.150.903000) details like hands and text. [221] It was released 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 brief detailed triggers [223] in addition to extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution up to 1920x1080 or 1080x1920. The maximal length of created videos is unidentified.
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Sora's advancement group called it after the Japanese word for "sky", to represent its "unlimited imaginative capacity". [223] Sora's innovation is an adaptation of the innovation behind the DALL ยท E 3 [text-to-image model](https://vlogloop.com). [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos licensed for that function, but did not reveal 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 might produce videos approximately one minute long. It also shared a technical report highlighting the methods used to train the design, and the design's capabilities. [225] It acknowledged a few of its shortcomings, consisting of battles mimicing intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", but kept in mind that they must have been cherry-picked and may not represent Sora's normal output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have actually revealed considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's ability to generate reasonable video from text descriptions, citing its potential to change storytelling and content production. He said that his excitement about [Sora's possibilities](https://vagyonor.hu) was so strong that he had chosen to pause prepare for expanding 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 acknowledgment design. [228] It is [trained](https://medatube.ru) on a big dataset of diverse audio and [surgiteams.com](https://surgiteams.com/index.php/User:Margret5196) is likewise a multi-task model that can carry out multilingual speech recognition in addition to speech translation and language identification. [229] +
Music generation
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MuseNet
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[Released](https://dreamtube.congero.club) in 2019, MuseNet is a deep neural net trained to forecast subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to begin fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for the web mental [thriller](http://carpetube.com) 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 create 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](http://121.40.194.1233000) the songs "show regional musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" and that "there is a considerable gap" between Jukebox and [human-generated music](https://scm.fornaxian.tech). The Verge mentioned "It's technically impressive, even if the results seem like mushy variations of tunes that might feel familiar", while Business Insider stated "remarkably, a few of the resulting songs are catchy and sound legitimate". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI launched the Debate Game, which teaches devices to dispute toy issues in front of a human judge. The purpose is to research whether such an approach might help in auditing [AI](https://tmsafri.com) decisions and in developing explainable [AI](http://wiki.myamens.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and nerve cell of eight neural network models which are typically studied in interpretability. [240] Microscope was created to evaluate the features that form inside these neural networks quickly. The designs consisted of are AlexNet, VGG-19, various versions of Inception, and different variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, [ChatGPT](http://rackons.com) is an artificial intelligence tool built on top of GPT-3 that supplies a conversational interface that enables users to ask questions in [natural language](http://youtubeer.ru). The system then reacts with a response within seconds.
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