From 53ce55c7f466891437d4a93cc90f509f16d0d73a Mon Sep 17 00:00:00 2001 From: tommie22802409 Date: Sun, 16 Feb 2025 03:49:17 +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..01406b9 --- /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 developed to facilitate the development of reinforcement learning algorithms. It aimed to standardize how environments are specified in [AI](https://gurjar.app) research, making published research study more easily reproducible [24] [144] while supplying users with a basic user for engaging 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 for reinforcement knowing (RL) research on computer game [147] using RL algorithms and study generalization. Prior RL research focused mainly on optimizing agents to resolve single jobs. Gym Retro gives the capability to generalize between games with similar ideas but 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 do not have 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](https://aquarium.zone) [learning](https://dev.clikviewstorage.com) process, the representatives discover how to adapt to changing conditions. When an agent is then gotten rid of from this virtual environment and placed in a brand-new virtual environment with high winds, the representative braces to remain upright, suggesting it had learned how to balance in a generalized method. [148] [149] [OpenAI's](https://iadgroup.co.uk) Igor Mordatch argued that competitors in between representatives could produce an intelligence "arms race" that could increase an agent's capability to operate even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a team of 5 OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that discover to play against human players at a high skill level completely through trial-and-error algorithms. Before becoming a group of 5, the first public demonstration took place at The International 2017, the annual premiere championship competition 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 actually learned by playing against itself for two weeks of actual time, and that the learning software application was a step in the direction of creating software that can manage intricate jobs like a cosmetic surgeon. [152] [153] The system uses a kind of reinforcement knowing, as the bots find out with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an enemy and taking map objectives. [154] [155] [156] +
By June 2018, the ability of the bots broadened to play together as a complete group of 5, and they had the ability to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against expert gamers, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public look came later on that month, where they played in 42,729 overall 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 player reveals the challenges of [AI](http://git.iloomo.com) systems in [multiplayer online](https://git.dadunode.com) battle arena (MOBA) video games and how OpenAI Five has demonstrated the usage of deep reinforcement learning (DRL) agents to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses machine discovering to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It learns totally in [simulation utilizing](http://git.9uhd.com) the very same RL algorithms and training code as OpenAI Five. OpenAI took on the item orientation issue by utilizing domain randomization, a simulation [technique](https://rapostz.com) which exposes the learner to a variety of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having motion tracking cams, likewise has RGB cameras to permit the robotic to manipulate an [arbitrary item](https://titikaka.unap.edu.pe) by seeing it. In 2018, OpenAI revealed that the system had the [ability](https://git.maxwellj.xyz) to manipulate a cube and an octagonal prism. [168] +
In 2019, [OpenAI demonstrated](https://novashop6.com) that Dactyl might solve a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to model. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation method of producing progressively harder environments. ADR varies from manual domain randomization by not requiring a human to specify randomization varieties. [169] +
API
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In June 2020, OpenAI announced a [multi-purpose API](http://geoje-badapension.com) which it said was "for accessing brand-new [AI](http://111.53.130.194:3000) models established by OpenAI" to let designers get in touch with it for "any English language [AI](https://gitea.adminakademia.pl) job". [170] [171] +
Text generation
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The business has actually popularized generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("GPT-1")
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The initial paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his coworkers, and published in preprint on [OpenAI's website](http://64.227.136.170) on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world understanding and procedure long-range dependencies by pre-training on a [varied corpus](https://startuptube.xyz) 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 design and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just restricted demonstrative versions initially launched to the general public. The full variation of GPT-2 was not right away launched due to concern about prospective misuse, consisting of applications for writing fake news. [174] Some specialists revealed [uncertainty](http://101.36.160.14021044) that GPT-2 posed a significant danger.
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In action to GPT-2, the Allen Institute for [Artificial Intelligence](https://dronio24.com) reacted with a tool to discover "neural fake news". [175] Other scientists, such as Jeremy Howard, warned 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 complete version of the GPT-2 language design. [177] Several websites host interactive presentations of different instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue unsupervised language designs to be [general-purpose](http://git.mutouyun.com3005) students, illustrated by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further 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 prevents certain concerns encoding [vocabulary](http://gitlab.ds-s.cn30000) with word tokens by utilizing byte pair encoding. This allows [representing](http://93.104.210.1003000) 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 without supervision transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete version of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as few as 125 million criteria were likewise trained). [186] +
OpenAI specified 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 dramatically improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the essential capability 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 design was not right away released to the general public for issues of possible abuse, although OpenAI planned to allow 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 certified solely to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.hmmr.ru) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was [launched](https://sharingopportunities.com) in private beta. [194] According to OpenAI, the design can produce working code in over a lots shows languages, many effectively in Python. [192] +
Several concerns with problems, style defects and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has actually been accused of releasing copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would terminate assistance for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI revealed the [release](http://git.itlym.cn) of Generative Pre-trained Transformer 4 (GPT-4), capable of [accepting text](http://copyvance.com) or image inputs. [199] They [revealed](https://incomash.com) that the [upgraded innovation](https://git.gilgoldman.com) passed a simulated law school bar test 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 might also read, examine or generate approximately 25,000 words of text, and write code in all major shows languages. [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 a few of the issues with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on [ChatGPT](http://gitlab.signalbip.fr). [202] OpenAI has actually decreased to expose various technical details and data about GPT-4, such as the accurate size of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and create 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) standard 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 interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, [compared](https://www.dailynaukri.pk) to $5 and $15 respectively for GPT-4o. OpenAI expects it to be especially useful for business, start-ups and developers seeking to automate services with [AI](https://jobs.sudburychamber.ca) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been designed to take more time to think of their reactions, leading to greater precision. These designs are especially efficient in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Team members. [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 follower of the o1 thinking design. OpenAI also revealed o3-mini, a lighter and faster version of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the opportunity to obtain early access to these [designs](https://www.hyxjzh.cn13000). [214] The model is called o3 rather than o2 to prevent confusion with telecoms providers O2. [215] +
Deep research study
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Deep research study is an [agent established](https://nextjobnepal.com) by OpenAI, revealed on February 2, 2025. It leverages the [capabilities](http://113.45.225.2193000) of OpenAI's o3 design to perform comprehensive web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools made it possible for, 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 design that is [trained](https://galgbtqhistoryproject.org) to analyze the [semantic similarity](https://yezidicommunity.com) between text and images. It can especially 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 version of GPT-3 to translate natural language inputs (such as "a green leather purse formed like a pentagon" or "an isometric view of a sad capybara") and create matching images. It can develop images of practical things ("a stained-glass window with a picture of a blue strawberry") in addition to objects that do not exist in reality ("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 revealed DALL-E 2, an updated variation of the model with more reasonable outcomes. [219] In December 2022, OpenAI [published](http://60.204.229.15120080) on GitHub software application for Point-E, a brand-new basic system for converting a text description into a 3-dimensional model. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, [garagesale.es](https://www.garagesale.es/author/lucamcrae20/) a more powerful design much better able to create images from complex descriptions without manual prompt engineering and [render intricate](http://120.36.2.2179095) 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 design that can [produce](https://noblessevip.com) videos based upon brief detailed triggers [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of created videos is unidentified.
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Sora's development group called it after the Japanese word for "sky", to represent its "endless innovative potential". [223] Sora's technology is an adjustment of the technology behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos accredited for that function, however did not reveal the number or the precise sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:LindseyWalstab9) 2024, stating that it could produce videos as much as one minute long. It likewise shared a technical report highlighting the approaches utilized to train the model, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2769752) and the design's capabilities. [225] It acknowledged some of its imperfections, including struggles imitating complicated 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 [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:Homer93G479471) might not [represent Sora's](https://git.goatwu.com) normal output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, noteworthy entertainment-industry figures have actually shown considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's ability to produce practical video from text descriptions, citing its possible to change storytelling and content development. He said that his excitement about Sora's possibilities was so strong that he had actually decided to pause 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](https://jktechnohub.com) design that can [perform](http://116.198.225.843000) multilingual speech acknowledgment in addition to 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 predict subsequent musical notes in MIDI music files. It can create 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 popular culture, [preliminary applications](http://47.99.37.638099) of this tool were used as early as 2020 for the web psychological thriller Ben Drowned to create 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 genre, artist, and a bit of lyrics and outputs song samples. OpenAI mentioned the songs "show local musical coherence [and] follow standard chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" and that "there is a significant space" between Jukebox and [human-generated music](https://tintinger.org). The Verge mentioned "It's technologically outstanding, even if the results sound like mushy versions of tunes that might feel familiar", while Business Insider specified "remarkably, a few of the resulting songs are appealing and sound genuine". [234] [235] [236] +
User user interfaces
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Debate Game
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In 2018, OpenAI released the Debate Game, which teaches makers to discuss toy problems in front of a human judge. The purpose is to research whether such a technique may assist in auditing [AI](http://lesstagiaires.com) decisions and in developing explainable [AI](https://git.vincents.cn). [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 designs which are frequently studied in interpretability. [240] Microscope was developed to analyze the functions that form inside these neural networks easily. 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, ChatGPT is an expert system tool developed on top of GPT-3 that provides a conversational user interface that allows users to ask questions in natural language. The system then responds with an answer within seconds.
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