From e0989c1df3254a9e574996bba2e250c3cbb1bb5d Mon Sep 17 00:00:00 2001 From: elverasantos24 Date: Sat, 22 Feb 2025 01:21:41 +0100 Subject: [PATCH] Add 'The Verge Stated It's Technologically Impressive' --- ...tated-It%27s-Technologically-Impressive.md | 26 +++++++++++++++++++ 1 file changed, 26 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..cf42335 --- /dev/null +++ b/The-Verge-Stated-It%27s-Technologically-Impressive.md @@ -0,0 +1,26 @@ +
Announced in 2016, Gym is an open-source Python library designed to assist in the advancement of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](https://git.perbanas.id) research, making published research more quickly reproducible [24] [144] while providing users with a simple interface for interacting with these environments. In 2022, brand-new advancements of Gym have actually been relocated to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, [Gym Retro](https://code.karsttech.com) is a platform for support knowing (RL) research on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on optimizing agents to resolve single jobs. Gym Retro provides the ability to generalize between video games with comparable concepts however different looks.
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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, but are [offered](https://jobs.askpyramid.com) the objectives of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the representatives discover how to adjust to changing conditions. When an agent is then eliminated from this virtual environment and put in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had found out how to stabilize in a [generalized method](https://pantalassicoembalagens.com.br). [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might produce an intelligence "arms race" that could increase a representative's ability to operate even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a team of five OpenAI-curated bots [utilized](http://test.wefanbot.com3000) in the competitive five-on-five video game Dota 2, that find out to play against human gamers at a high ability level totally through trial-and-error algorithms. Before becoming a group of 5, the first public presentation happened at The International 2017, the annual best championship tournament for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had learned by playing against itself for two weeks of genuine time, and that the knowing software application was an action in the instructions of [developing software](https://www.jobplanner.eu) application that can manage complex tasks like a surgeon. [152] [153] The system uses a form of reinforcement knowing, as the bots learn with 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] +
By June 2018, [it-viking.ch](http://it-viking.ch/index.php/User:ShannanMullen43) the ability of the bots expanded to play together as a complete team of 5, and they had the ability to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against professional gamers, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public look 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 player shows the difficulties of [AI](http://170.187.182.121:3000) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated the usage of deep support knowing (DRL) agents to attain superhuman proficiency in Dota 2 matches. [166] +
Dactyl
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[Developed](https://jobs.cntertech.com) in 2018, Dactyl uses device discovering to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It learns entirely in simulation using the exact same RL algorithms and [training](https://richonline.club) code as OpenAI Five. OpenAI took on the object orientation problem by utilizing domain randomization, a simulation technique which exposes the student to a variety of experiences rather than trying to fit to truth. The set-up for Dactyl, aside from having movement tracking video cameras, also has RGB video [cameras](https://corvestcorp.com) to enable the robot to control an approximate item by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl could resolve a Rubik's Cube. The robotic was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to model. 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 varieties. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](http://nas.killf.info:9966) designs established by OpenAI" to let [designers](https://www.viewtubs.com) call on it for "any English language [AI](https://kittelartscollege.com) job". [170] [171] +
Text generation
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The company has actually promoted 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 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 understanding and process long-range dependences by pre-training on a varied 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 ("GPT-1"). GPT-2 was announced in February 2019, with just limited demonstrative variations at first released to the general public. The complete variation of GPT-2 was not right away launched due to issue about potential abuse, consisting of applications for composing fake news. [174] Some professionals revealed uncertainty that GPT-2 posed a considerable hazard.
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In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to discover "neural fake news". [175] Other researchers, such as Jeremy Howard, warned of "the technology to completely 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 launched the complete variation 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](http://git.e365-cloud.com) argue not being watched language designs to be general-purpose students, shown by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot tasks (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 at least 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This permits 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 design and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion specifications, [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 few as 125 million specifications were also trained). [186] +
OpenAI specified that GPT-3 was successful at certain "meta-learning" tasks and [forum.batman.gainedge.org](https://forum.batman.gainedge.org/index.php?action=profile \ No newline at end of file