From 93cedc6c6f86dda6ac3e50693ad3e8e8e00f6efc Mon Sep 17 00:00:00 2001 From: hueyabell6596 Date: Fri, 7 Feb 2025 17:00:28 +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..27ca19a --- /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 advancement of reinforcement learning algorithms. It aimed to standardize how environments are specified in [AI](https://janhelp.co.in) research study, making released research study more easily reproducible [24] [144] while offering users with a simple user interface for interacting with these environments. In 2022, brand-new advancements 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 [support knowing](https://www.oscommerce.com) (RL) research study on computer game [147] using RL algorithms and research study generalization. Prior RL research focused mainly on enhancing representatives to resolve single jobs. Gym Retro offers the capability to generalize in between games with similar principles however different looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially lack knowledge of how to even walk, but are given the objectives of finding out to move and to push the opposing representative out of the ring. [148] Through this adversarial learning procedure, the agents discover how to adjust to changing conditions. When a representative is then gotten rid of from this virtual environment and positioned in a brand-new virtual [environment](https://git.snaile.de) with high winds, the representative 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 in between agents might develop an intelligence "arms race" that might increase a representative's capability to function even outside the context of the competition. [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 learn to play against human gamers at a high skill level completely through experimental algorithms. Before becoming a group of 5, the very first public presentation took place at The International 2017, the annual best champion tournament for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for two weeks of real time, and that the knowing software was a step in the direction of creating software that can manage complex tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of support learning, as the bots learn over time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an enemy and taking map goals. [154] [155] [156] +
By June 2018, the [ability](https://blog.giveup.vip) of the bots broadened to play together as a full group of 5, and they were able to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 [exhibit matches](https://tartar.app) against expert gamers, however ended up losing both 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 exhibit match in [San Francisco](https://snowboardwiki.net). [163] [164] The bots' final public look came later that month, where they played in 42,729 total video games in a four-day open online competitors, winning 99.4% of those video games. [165] +
OpenAI 5's systems in Dota 2's bot gamer reveals the obstacles of [AI](http://git.risi.fun) systems in multiplayer online [battle arena](https://i-medconsults.com) (MOBA) games and how OpenAI Five has actually demonstrated using [deep reinforcement](http://demo.ynrd.com8899) knowing (DRL) agents to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses machine finding out to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It discovers entirely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI took on the things [orientation](https://web.zqsender.com) problem by utilizing domain randomization, a simulation method which exposes the learner to a variety of [experiences](http://47.76.210.1863000) instead of trying to fit to truth. The set-up for Dactyl, aside from having motion tracking cameras, likewise has RGB electronic cameras to enable the robotic to manipulate an approximate object by seeing it. In 2018, OpenAI [revealed](http://fangding.picp.vip6060) that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl might fix a Rubik's Cube. The robot had the ability 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 improving the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of creating progressively more hard environments. ADR differs from manual domain randomization by not needing a human to [define randomization](https://coptr.digipres.org) ranges. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://git.berezowski.de) designs developed by OpenAI" to let developers call on it for "any English language [AI](https://gogs.xinziying.com) job". [170] [171] +
Text generation
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The business has actually promoted generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("GPT-1")
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The original paper on [generative pre-training](https://git.lewd.wtf) of a transformer-based language model was written by Alec Radford and his colleagues, and released in preprint on [OpenAI's site](https://git.gday.express) on June 11, 2018. [173] It demonstrated how a generative design of language might obtain world knowledge and process long-range dependencies 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 an unsupervised transformer language model and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just limited demonstrative versions initially released to the general public. The full version of GPT-2 was not [instantly released](http://111.230.115.1083000) due to issue about potential abuse, consisting of applications for writing phony news. [174] Some professionals expressed [uncertainty](https://git.easytelecoms.fr) that GPT-2 presented a significant threat.
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In action to GPT-2, the Allen Institute for Artificial Intelligence [reacted](https://service.lanzainc.xyz10281) with a tool to [identify](https://feelhospitality.com) "neural fake 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 drown out all other speech and be difficult to filter". [176] In November 2019, OpenAI released the total version of the GPT-2 language model. [177] Several websites host interactive demonstrations of various instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue not being watched language models to be general-purpose learners, illustrated by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot jobs (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 a little 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 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 a not being watched transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion parameters, [184] 2 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 parameters were likewise trained). [186] +
OpenAI mentioned that GPT-3 prospered at certain "meta-learning" tasks and might generalize the function of a [single input-output](http://47.107.126.1073000) pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer between [English](https://musixx.smart-und-nett.de) and Romanian, and between English and German. [184] +
GPT-3 significantly enhanced benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or coming across the basic capability constraints of predictive language designs. [187] Pre-training GPT-3 required a number of thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for [fishtanklive.wiki](https://fishtanklive.wiki/User:DouglasWhitney) the full 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 planned to allow [gain access](http://admin.youngsang-tech.com) 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 exclusively to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.com.listatto.ca) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the model can develop working code in over a lots programs languages, a lot of effectively in Python. [192] +
Several concerns with problems, style flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been [accused](https://aji.ghar.ku.jaldi.nai.aana.ba.tume.dont.tach.me) of discharging copyrighted code, without any author attribution or license. [197] +
OpenAI announced that they would discontinue support 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 revealed that the updated technology passed a simulated law school bar exam with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, evaluate or generate as much as 25,000 words of text, and write code in all major shows languages. [200] +
Observers reported that the version of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 retained some of the issues with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has actually declined 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 released GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision criteria, setting brand-new [records](https://901radio.com) in audio speech acknowledgment 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 changing GPT-3.5 Turbo on the ChatGPT interface. Its API costs $0.15 per million [input tokens](http://git.gonstack.com) and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially helpful for enterprises, start-ups and developers seeking to automate services with [AI](https://insta.tel) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been developed to take more time to consider their actions, causing greater precision. These [designs](https://sound.co.id) are particularly reliable in science, coding, and [thinking](https://akinsemployment.ca) tasks, [wavedream.wiki](https://wavedream.wiki/index.php/User:VeroniqueBernhar) and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was replaced by o1. [211] +
o3
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On December 20, 2024, [ratemywifey.com](https://ratemywifey.com/author/wilheminapu/) OpenAI unveiled o3, the successor of the o1 thinking model. OpenAI likewise unveiled o3-mini, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:JerriRabinovitch) a lighter and faster variation of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, they are [testing](https://hortpeople.com) o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the opportunity to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecoms services supplier O2. [215] +
Deep research
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Deep research is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform substantial web browsing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching 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 analyze the semantic similarity between text and images. It can significantly 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 design that creates 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 bag formed like a pentagon" or "an isometric view of an unfortunate capybara") and produce [matching images](https://kiaoragastronomiasocial.com). It can create pictures of practical objects ("a stained-glass window with an image of a blue strawberry") along with things 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 upgraded variation of the model with more sensible outcomes. [219] In December 2022, [OpenAI published](https://cheere.org) on GitHub software application for Point-E, a new rudimentary system for converting 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 design](https://www.unotravel.co.kr) better able to create images from complex descriptions without manual timely engineering and render complicated 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 create videos based on short detailed triggers [223] in addition to extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.
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[Sora's development](http://40.73.118.158) team called it after the Japanese word for "sky", to signify its "limitless 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 in addition to copyrighted videos certified for that function, however did not expose the number or the [precise sources](https://jimsusefultools.com) of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, stating that it could [produce videos](https://dvine.tv) approximately one minute long. It likewise shared a technical report highlighting the methods utilized to train the design, and the model's abilities. [225] It acknowledged some of its shortcomings, consisting of battles mimicing intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", but kept in mind that they should have been cherry-picked and might not [represent Sora's](https://remnanthouse.tv) typical output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, noteworthy entertainment-industry figures have shown significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his [astonishment](https://jobs.com.bn) at the innovation's capability to produce reasonable video from text descriptions, mentioning its possible to [reinvent storytelling](https://teengigs.fun) and material development. He said that his enjoyment about Sora's possibilities was so strong that he had chosen to pause strategies for broadening his Atlanta-based motion picture studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, [gratisafhalen.be](https://gratisafhalen.be/author/dulcie01x5/) Whisper is a general-purpose speech recognition design. [228] It is trained on a big dataset of varied audio and is likewise a [multi-task](https://etrade.co.zw) model that can perform multilingual speech acknowledgment along with 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 generate tunes with 10 instruments in 15 designs. According to The Verge, a tune produced by MuseNet tends to begin fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were utilized as early as 2020 for the internet psychological thriller Ben Drowned to produce 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 genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI specified the tunes "reveal regional musical coherence [and] follow traditional chord patterns" however acknowledged that the songs do not have "familiar bigger musical structures such as choruses that repeat" and that "there is a considerable gap" in between Jukebox and [human-generated music](http://41.111.206.1753000). The Verge specified "It's highly remarkable, even if the outcomes seem like mushy versions of songs that may feel familiar", while [Business Insider](https://aladin.social) specified "surprisingly, some of the resulting tunes 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 machines to debate toy issues in front of a human judge. The function is to research study whether such an approach may assist in auditing [AI](https://phoebe.roshka.com) choices and in establishing explainable [AI](https://daeshintravel.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](https://www.florevit.com) of eight neural network designs which are frequently studied in interpretability. [240] Microscope was developed to examine the features that form inside these neural networks easily. The models consisted of are AlexNet, [surgiteams.com](https://surgiteams.com/index.php/User:CathleenMadison) VGG-19, different variations of Inception, and different [versions](https://git.the-kn.com) of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, [larsaluarna.se](http://www.larsaluarna.se/index.php/User:NicholeCoffman) ChatGPT is an expert system tool constructed on top of GPT-3 that offers a conversational user interface that allows users to ask questions in [natural language](https://ifairy.world). The system then responds with a response within seconds.
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