From d99a481bd55b34d23699d5c2cd4bb08951b33ae9 Mon Sep 17 00:00:00 2001 From: trudymcgruder8 Date: Thu, 3 Apr 2025 15:38:58 +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..e7771af --- /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](https://admin.gitea.eccic.net) the advancement of support learning algorithms. It aimed to standardize how environments are specified in [AI](http://lespoetesbizarres.free.fr) research, making published research study more easily reproducible [24] [144] while providing users with a basic user interface for connecting with these environments. In 2022, new advancements of Gym have been relocated to the library Gymnasium. [145] [146] +
Gym Retro
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[Released](http://39.105.203.1873000) in 2018, Gym Retro is a platform for reinforcement learning (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research study focused mainly on enhancing representatives to fix single jobs. Gym Retro provides the capability to generalize in between games with similar 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 at first lack knowledge of how to even walk, however are provided the objectives of discovering to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the agents learn how to adapt to changing conditions. When an agent is then removed from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, [suggesting](https://git.camus.cat) it had learned how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents could produce an intelligence "arms race" that might increase an agent's capability to operate even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a group of 5 OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that find out to play against human gamers at a high ability level entirely through experimental algorithms. Before ending up being a group of 5, [larsaluarna.se](http://www.larsaluarna.se/index.php/User:RenateGovan1811) the first public demonstration happened at The International 2017, the yearly best champion tournament for the game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had found out by playing against itself for two weeks of actual time, and that the learning software was a step in the instructions of creating software that can deal with complex jobs like a surgeon. [152] [153] The system utilizes a form of support learning, as the bots discover in time by playing against themselves [numerous](http://git.swordlost.top) times a day for months, and [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:JeannetteI75) are rewarded for actions such as killing an enemy and taking map goals. [154] [155] [156] +
By June 2018, the capability of the bots expanded to play together as a complete group of 5, and they were able to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against players, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champs of the game at the time, 2:0 in a live exhibit match in [San Francisco](https://deadreckoninggame.com). [163] [164] The bots' final public appearance came later on that month, where they played in 42,729 overall video games in a four-day open online competition, winning 99.4% of those [video games](https://corvestcorp.com). [165] +
OpenAI 5's systems in Dota 2's bot player shows the difficulties of [AI](https://10mektep-ns.edu.kz) systems in multiplayer online battle arena (MOBA) games and [89u89.com](https://www.89u89.com/author/maniegillin/) how OpenAI Five has shown the use of deep reinforcement knowing (DRL) representatives to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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[Developed](https://probando.tutvfree.com) in 2018, Dactyl utilizes maker discovering to train a Shadow Hand, a human-like robotic hand, to control physical objects. [167] It finds out totally in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI tackled the object [orientation](http://121.36.37.7015501) problem by utilizing domain randomization, a simulation approach which exposes the student to a variety of [experiences](http://101.43.18.2243000) rather than attempting to fit to reality. The set-up for Dactyl, aside from having motion tracking video cameras, likewise has RGB cameras to allow the robotic to control an arbitrary things by seeing it. In 2018, OpenAI showed that the system had the ability to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl could resolve a Rubik's Cube. The robotic was able to solve the puzzle 60% of the time. Objects like the [Rubik's Cube](https://git.mhurliman.net) present [intricate physics](https://event.genie-go.com) that is harder to design. OpenAI did this by enhancing the [toughness](http://115.29.48.483000) of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating gradually harder environments. ADR differs 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](https://noteswiki.net) which it said was "for accessing new [AI](http://39.106.223.11) designs established by OpenAI" to let [developers](https://gitea.moerks.dk) get in touch with it for "any English language [AI](https://www.panjabi.in) task". [170] [171] +
Text generation
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The company has promoted generative pretrained transformers (GPT). [172] +
[OpenAI's initial](https://git.jackbondpreston.me) 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 coworkers, 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 procedure long-range reliances by pre-training on a diverse corpus with long stretches of [contiguous text](https://startuptube.xyz).
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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 follower to OpenAI's initial GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative variations initially launched to the public. The complete version of GPT-2 was not immediately released due to issue about prospective abuse, consisting of applications for composing phony news. [174] Some experts expressed uncertainty that GPT-2 presented a significant danger.
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In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to discover "neural phony news". [175] Other researchers, such as Jeremy Howard, alerted of "the innovation 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 released the total version of the GPT-2 language design. [177] Several websites host interactive demonstrations of various instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue unsupervised language designs to be general-purpose learners, shown by GPT-2 attaining cutting edge precision 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 somewhat 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by [utilizing byte](http://yhxcloud.com12213) pair encoding. This permits representing any string of characters by encoding both specific 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 specified that the complete version of GPT-3 contained 175 billion parameters, [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 few as 125 million parameters were likewise trained). [186] +
OpenAI mentioned that GPT-3 prospered at certain "meta-learning" jobs and might generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer knowing in between English 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 designs might be approaching or coming across the fundamental ability constraints of predictive language models. [187] Pre-training GPT-3 needed numerous 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 model was not instantly released to the public for issues of possible abuse, although OpenAI prepared to enable 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 specifically to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has actually furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://gitlab.ngser.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the design can [develop](https://gitea.deprived.dev) working code in over a lots programs languages, a lot of efficiently in Python. [192] +
Several issues with glitches, design defects and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has actually been accused of releasing copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would discontinue 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), efficient in accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar exam with a rating around the top 10% of [test takers](https://jobs.careersingulf.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, [examine](https://becalm.life) or create approximately 25,000 words of text, and write code in all significant shows [languages](https://www.dailynaukri.pk). [200] +
Observers 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](http://8.129.8.58) some 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 reveal different technical details and data about GPT-4, such as the [precise size](http://www.andreagorini.it) of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI announced and released GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained state-of-the-art [outcomes](https://wooshbit.com) in voice, multilingual, and vision benchmarks, [setting brand-new](https://social.oneworldonesai.com) records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the [Massive Multitask](http://39.106.43.96) [Language Understanding](https://www.nikecircle.com) (MMLU) standard compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI launched GPT-4o mini, a smaller version 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 expects it to be especially helpful for enterprises, startups and developers seeking to automate services with [AI](https://pittsburghtribune.org) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been developed to take more time to consider their responses, [raovatonline.org](https://raovatonline.org/author/dustinz7422/) leading to higher accuracy. These models 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 replaced by o1. [211] +
o3
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On December 20, 2024, OpenAI unveiled o3, [wakewiki.de](https://www.wakewiki.de/index.php?title=Benutzer:BellaDenehy6165) the follower of the o1 thinking model. OpenAI also revealed o3-mini, a lighter and quicker variation of OpenAI o3. As of December 21, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) 2024, this model 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 researchers had the opportunity to obtain early access to these designs. [214] The design is called o3 rather than o2 to avoid confusion with telecommunications providers O2. [215] +
Deep research
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Deep research study is an agent established by OpenAI, unveiled on February 2, 2025. It [leverages](https://repo.serlink.es) the capabilities of [OpenAI's](https://wheeoo.com) o3 model to carry out extensive web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools enabled, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] +
Image classification
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CLIP
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Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the semantic similarity between text and images. It can significantly 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 model that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate [natural language](http://114.55.2.296010) inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can develop images of [realistic](https://gitea.chofer.ddns.net) things ("a stained-glass window with a picture of a blue strawberry") along with 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 design with more reasonable outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new basic system for transforming a text description into a 3-dimensional design. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, a more effective model much better able to generate images from [intricate descriptions](https://ideezy.com) without manual timely engineering and render complicated details like hands and text. [221] It was launched to the general public as a ChatGPT Plus [feature](https://git.juxiong.net) in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video model that can produce videos based on brief [detailed triggers](https://arthurwiki.com) [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with [resolution](https://hitechjobs.me) as much as 1920x1080 or 1080x1920. The maximal length of generated videos is [unknown](https://kerjayapedia.com).
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Sora's development group called it after the Japanese word for "sky", to represent its "unlimited creative capacity". [223] Sora's innovation is an adaptation of the innovation behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos as well as copyrighted videos accredited for that function, however did not reveal the number or the exact 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 likewise shared a technical report [highlighting](http://carvis.kr) the methods utilized to train the model, and the model's abilities. [225] It acknowledged some of its drawbacks, including battles simulating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but kept in mind that they must have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, significant entertainment-industry figures have revealed substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to generate practical video from text descriptions, citing its possible to reinvent storytelling and material development. He said that his excitement about Sora's possibilities was so strong that he had decided to stop briefly prepare for expanding his Atlanta-based movie 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 design that can carry out multilingual speech acknowledgment as well as speech translation and 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 forecast subsequent musical notes in MIDI music files. It can produce songs with 10 instruments in 15 styles. According to The Verge, a tune produced by [MuseNet](http://modulysa.com) tends to begin fairly however then fall under mayhem the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were used as early as 2020 for the internet 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 create music with vocals. After training on 1.2 million samples, the system [accepts](https://bahnreise-wiki.de) a category, artist, and a bit of lyrics and outputs song samples. OpenAI mentioned the songs "show regional musical coherence [and] follow conventional chord patterns" however acknowledged that the songs lack "familiar larger musical structures such as choruses that repeat" which "there is a substantial space" between Jukebox and human-generated music. The Verge stated "It's technologically impressive, even if the results seem like mushy variations of songs that may feel familiar", while Business Insider mentioned "surprisingly, a few of the resulting songs are memorable and sound legitimate". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, [OpenAI released](https://gitea.sitelease.ca3000) the Debate Game, which teaches devices to dispute toy problems in front of a human judge. The purpose is to research whether such an approach may assist in auditing [AI](https://kyigit.kyigd.com:3000) decisions and in developing explainable [AI](https://spreek.me). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and nerve cell of 8 neural network models which are frequently studied in interpretability. [240] Microscope was developed to analyze the features that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, various versions of Inception, and different versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that supplies a conversational interface that allows users to ask [questions](http://xn--ok0b850bc3bx9c.com) in natural language. The system then responds with an answer within seconds.
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