commit 988d0c43869cc703cac08abe8e9e3c13f5602d59 Author: irenepickering Date: Fri Feb 21 20:35:46 2025 +0800 Add The Verge Stated It's Technologically Impressive 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..69e6c69 --- /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 assist in the development of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](http://gitlab.y-droid.com) research study, making [published](https://git.songyuchao.cn) research more quickly reproducible [24] [144] while supplying users with a basic interface for engaging with these environments. In 2022, new advancements of Gym have been transferred to the [library Gymnasium](https://adsall.net). [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on enhancing representatives to resolve single jobs. Gym Retro provides the capability to generalize between games with comparable principles but various appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first do not have understanding of how to even stroll, but are provided the goals of discovering to move and to press the [opposing representative](http://ja7ic.dxguy.net) out of the ring. [148] Through this adversarial knowing process, the representatives learn how to adapt to altering conditions. When a representative is then gotten rid of from this virtual environment and [larsaluarna.se](http://www.larsaluarna.se/index.php/User:Arturo0965) put in a brand-new virtual environment with high winds, the representative braces to remain upright, recommending it had actually [learned](http://git.edazone.cn) how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives might create an intelligence "arms race" that could increase an agent's ability to operate even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a team of 5 OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that find out to play against human players at a high ability level entirely through experimental algorithms. Before becoming a team of 5, the first public presentation happened at The International 2017, the annual best championship competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live one-on-one matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually learned by playing against itself for [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:DwightLangler4) two weeks of genuine time, and that the [knowing software](https://clickcareerpro.com) application was an action in the direction of creating software that can handle intricate tasks like a surgeon. [152] [153] The system uses a type of support learning, as the bots learn 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 ability of the [bots broadened](http://47.242.77.180) to play together as a full group 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 2 [exhibit matches](https://www.jgluiggi.xyz) against expert players, but wound up losing both video 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 exhibition match in San Francisco. [163] [164] The [bots' final](https://celflicks.com) public look came later on 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](https://contractoe.com) systems in [multiplayer online](http://8.134.237.707999) battle arena (MOBA) games and how OpenAI Five has shown the usage of deep support learning (DRL) agents to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses maker finding out to train a Shadow Hand, a human-like robotic hand, to manipulate physical things. [167] It discovers completely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the object orientation problem by utilizing domain randomization, a simulation [technique](https://abcdsuppermarket.com) which exposes the student to a variety of [experiences](http://60.23.29.2133060) rather than [attempting](http://jialcheerful.club3000) to fit to reality. The set-up for Dactyl, aside from having motion tracking cams, also has RGB electronic cameras to permit the robotic to manipulate an approximate item by seeing it. In 2018, OpenAI showed that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robot was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex 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 producing gradually harder environments. ADR varies from manual domain randomization by not needing a human to specify 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://www.uaehire.com) models developed by OpenAI" to let developers contact it for "any English language [AI](https://eurosynapses.giannistriantafyllou.gr) job". [170] [171] +
Text generation
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The company has actually popularized generative pretrained [transformers](https://firemuzik.com) (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 written by Alec Radford and his coworkers, and published in preprint on OpenAI's site on June 11, 2018. [173] It showed how a generative design of language could obtain world understanding and procedure long-range dependences by pre-training on a diverse corpus with long [stretches](https://blogram.online) of adjoining text.
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GPT-2
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Generative Pre-trained Transformer 2 ("GPT-2") is a without [supervision](https://marcosdumay.com) transformer language model and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative variations initially launched to the public. The full variation of GPT-2 was not right away released due to issue about potential misuse, consisting of applications for writing fake news. [174] Some professionals expressed uncertainty that GPT-2 presented a considerable risk.
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In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to find "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned of "the innovation to totally 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 complete version of the GPT-2 language design. [177] Several sites host interactive presentations of various instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue not being watched language designs to be general-purpose learners, highlighted by GPT-2 attaining cutting edge accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not further trained on any task-specific input-output 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 at least 3 upvotes. It prevents certain issues encoding vocabulary with word tokens by using 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 a not being watched transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion parameters, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were likewise trained). [186] +
OpenAI mentioned that GPT-3 was successful at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning in between English and Romanian, and between English and German. [184] +
GPT-3 considerably enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of [language models](https://gitlab.wah.ph) could be approaching or coming across the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 required a number of thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not right away released to the public for issues of possible abuse, although OpenAI prepared to permit gain access to through a [paid cloud](https://bikrikoro.com) API after a two-month complimentary private beta that started 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 [additionally](https://wiki.whenparked.com) been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://www.hanmacsamsung.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can [develop](https://www.jobtalentagency.co.uk) working code in over a lots programming languages, the majority of efficiently in Python. [192] +
Several problems with glitches, [style defects](https://bvbborussiadortmundfansclub.com) and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has actually been accused of discharging copyrighted code, without any author attribution or license. [197] +
OpenAI announced 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](https://git.ycoto.cn) that the updated technology passed a [simulated law](https://kittelartscollege.com) [school bar](http://8.222.247.203000) 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 could likewise check out, [analyze](http://45.67.56.2143030) or create as much as 25,000 words of text, and write code in all major [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:IraBvi6733883) programming languages. [200] +
[Observers](http://www.zeil.kr) reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to expose numerous technical details and statistics 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 released GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained cutting edge lead to voice, multilingual, and vision criteria, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) benchmark compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI launched GPT-4o mini, a smaller sized 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 anticipates it to be particularly helpful for business, startups and developers seeking to automate services with [AI](https://newhopecareservices.com) representatives. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been created to take more time to consider their actions, resulting in greater [accuracy](http://39.98.79.181). These models are particularly efficient in science, coding, and thinking jobs, and were made available to ChatGPT Plus and [pediascape.science](https://pediascape.science/wiki/User:LoriHsu3056) Staff member. [209] [210] In December 2024, o1-preview was replaced by o1. [211] +
o3
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On December 20, 2024, OpenAI unveiled o3, the follower of the o1 [reasoning design](https://code.balsoft.ru). OpenAI likewise revealed o3-mini, a lighter and much faster version of OpenAI o3. As of December 21, [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:LaneHaining) 2024, this model is not available for public use. According to OpenAI, they are evaluating 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 prevent confusion with telecoms services service provider O2. [215] +
Deep research study
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Deep research is a [representative established](http://142.93.151.79) by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform substantial web surfing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools allowed, 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 analyze the semantic resemblance between text and images. It can especially 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 produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and produce corresponding images. It can produce images of reasonable objects ("a stained-glass window with an image of a blue strawberry") along with objects 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](https://51.75.215.219) of the design with more reasonable outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new primary system for transforming 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 better able to produce images from complicated descriptions without manual prompt engineering and render intricate details like hands and text. [221] It was released to the public as a [ChatGPT](https://thesecurityexchange.com) 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 short detailed prompts [223] along with extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The maximal length of created videos is unknown.
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Sora's development group called it after the Japanese word for "sky", to signify its "endless creative potential". [223] Sora's technology is an [adaptation](http://www.xn--9m1b66aq3oyvjvmate.com) of the innovation behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos accredited for that function, but did not expose the number or the precise 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 create videos up to one minute long. It likewise shared a technical report highlighting the techniques utilized to train the model, and the [model's capabilities](https://hesdeadjim.org). [225] It acknowledged some of its drawbacks, consisting of battles mimicing complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", however kept in mind that they need to have been cherry-picked and may not represent Sora's common output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, noteworthy entertainment-industry figures have shown substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his at the innovation's ability to create realistic video from text descriptions, citing its potential to transform storytelling and content production. He said that his excitement about Sora's possibilities 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 model. [228] It is trained on a large dataset of varied audio and is also a [multi-task](https://wiki.vst.hs-furtwangen.de) model that can carry out multilingual speech acknowledgment as well as speech translation and [oeclub.org](https://oeclub.org/index.php/User:MauricioRdz) 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 anticipate 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 mayhem the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:BernadinePowell) the internet psychological thriller Ben [Drowned](https://studentvolunteers.us) 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 category, artist, and a snippet of lyrics and outputs tune samples. OpenAI mentioned the songs "reveal local musical coherence [and] follow traditional chord patterns" however acknowledged that the songs lack "familiar bigger musical structures such as choruses that duplicate" and that "there is a significant space" in between Jukebox and human-generated music. The Verge stated "It's technologically outstanding, even if the outcomes sound like mushy versions of tunes that might feel familiar", while Business Insider mentioned "surprisingly, a few of the resulting songs are memorable 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 makers](http://git.jetplasma-oa.com) to debate toy problems in front of a human judge. The function is to research study whether such a technique might help in auditing [AI](https://git.skyviewfund.com) decisions and in establishing explainable [AI](http://git.jetplasma-oa.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and neuron of 8 neural network designs which are frequently studied in interpretability. [240] Microscope was developed to evaluate the functions that form inside these neural networks easily. The models included are AlexNet, VGG-19, various variations of Inception, and different variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is a synthetic intelligence tool developed on top of GPT-3 that provides a conversational user interface that enables users to ask questions in natural language. The system then responds with an answer within seconds.
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