From 14f6fb364be9d4a6e69d8ddae43a8742e4646825 Mon Sep 17 00:00:00 2001 From: leroy71j410001 Date: Fri, 11 Apr 2025 09:32:53 +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..7c279cd --- /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 the advancement of support learning algorithms. It aimed to standardize how environments are defined in [AI](http://47.104.65.214:19206) research study, making [released](https://www.cittamondoagency.it) research study more quickly reproducible [24] [144] while offering users with a [simple interface](https://gitea.ruwii.com) for engaging 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 is a platform for reinforcement knowing (RL) research study on computer game [147] utilizing RL algorithms and [study generalization](https://talentocentroamerica.com). Prior RL research study focused mainly on enhancing agents to resolve single jobs. Gym Retro offers the ability to [generalize](http://t93717yl.bget.ru) between video games with similar principles but various looks.
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RoboSumo
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Released in 2017, [RoboSumo](https://git.lolilove.rs) is a virtual world where humanoid metalearning robot agents initially lack understanding of how to even stroll, however are provided the objectives of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the representatives learn how to adapt to altering conditions. When an agent is then removed from this virtual environment and placed in a new [virtual](https://www.p3r.app) environment with high winds, the agent braces to remain upright, suggesting it had actually discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors in between agents might create an intelligence "arms race" that might increase a representative's ability to function even outside the context of the [competition](http://www.xn--739an41crlc.kr). [148] +
OpenAI 5
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OpenAI Five is a team of 5 OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that learn to play against human players at a high skill level entirely through [trial-and-error algorithms](http://git.kdan.cc8865). Before ending up being a team of 5, the first public presentation occurred at The International 2017, the annual premiere champion competition for the video game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually learned by playing against itself for two weeks of genuine time, which the knowing software application was a step in the direction of creating software application that can handle intricate tasks like a cosmetic surgeon. [152] [153] The system uses a type of reinforcement knowing, as the bots discover gradually by playing against themselves hundreds of times a day for months, [demo.qkseo.in](http://demo.qkseo.in/profile.php?id=1096576) and are rewarded for actions such as eliminating an opponent and taking map goals. [154] [155] [156] +
By June 2018, the capability of the [bots expanded](https://src.dziura.cloud) to play together as a full team of 5, and they were able to defeat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against expert players, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five [defeated](https://fcschalke04fansclub.com) OG, the ruling world champs of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public appearance 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 systems in Dota 2's bot gamer reveals the challenges of [AI](http://120.77.240.215:9701) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated the use of deep support learning (DRL) agents to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes device learning to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It discovers entirely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation problem by utilizing domain randomization, a simulation method which exposes the [student](https://www.aspira24.com) to a variety of experiences rather than attempting to fit to truth. The set-up for Dactyl, [wiki.myamens.com](http://wiki.myamens.com/index.php/User:MarylynEsmond) aside from having movement tracking video cameras, also has RGB cams to permit the robotic to control an approximate object by seeing it. In 2018, OpenAI revealed that the system had the ability to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl could fix a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating [progressively](https://kronfeldgit.org) more [difficult environments](http://expertsay.blog). ADR differs 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 which it said was "for accessing brand-new [AI](http://globalnursingcareers.com) models established by OpenAI" to let developers call on it for "any English language [AI](http://218.201.25.104:3000) task". [170] [171] +
Text generation
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The company has popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT model ("GPT-1")
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The initial paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his associates, and released in [preprint](https://ofalltime.net) on OpenAI's site on June 11, [surgiteams.com](https://surgiteams.com/index.php/User:JamieBingaman8) 2018. [173] It showed how a generative model of language could obtain world knowledge and procedure long-range reliances 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 an unsupervised transformer language model and the follower to OpenAI's initial GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just restricted demonstrative versions at first released to the public. The complete variation of GPT-2 was not immediately launched due to concern about prospective abuse, consisting of applications for writing fake news. [174] Some specialists expressed uncertainty that GPT-2 posed a substantial threat.
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In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to identify "neural phony news". [175] Other researchers, such as Jeremy Howard, warned of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI released the complete variation of the GPT-2 language model. [177] Several sites host interactive demonstrations of different instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue unsupervised language models to be general-purpose learners, shown by GPT-2 attaining advanced accuracy and perplexity on 7 of 8 zero-shot jobs (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 a little 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](https://insta.tel). This [permits representing](https://video.clicktruths.com) 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 without supervision transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 designs with as couple of as 125 million parameters were likewise trained). [186] +
OpenAI stated that GPT-3 succeeded at certain "meta-learning" tasks and could generalize the function of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing in between English and Romanian, and in between English and German. [184] +
GPT-3 [drastically improved](https://git.getmind.cn) benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or experiencing the essential ability constraints of predictive language models. [187] Pre-training GPT-3 required several 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 model was not immediately launched to the public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month complimentary private beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified specifically to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has furthermore been [trained](https://git.randomstar.io) on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://47.119.160.181:3000) 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 create working code in over a lots programming languages, the majority of efficiently in Python. [192] +
Several problems with problems, design defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been implicated of emitting copyrighted code, with no author attribution or license. [197] +
OpenAI announced 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 of Generative Pre-trained Transformer 4 (GPT-4), [efficient](https://git.guaranteedstruggle.host) in [accepting text](https://abalone-emploi.ch) or image inputs. [199] They [revealed](https://git.goatwu.com) that the upgraded technology passed a simulated law school bar exam with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise read, examine or generate approximately 25,000 words of text, and write code in all significant shows languages. [200] +
Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the problems with earlier revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has actually declined to expose different technical details and data about GPT-4, such as the accurate size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and [generate](https://noaisocial.pro) text, images and audio. [204] GPT-4o attained modern lead to voice, [gratisafhalen.be](https://gratisafhalen.be/author/mistydohert/) multilingual, and vision standards, setting brand-new records in audio speech [acknowledgment](http://git.techwx.com) 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 released GPT-4o mini, a smaller sized version of GPT-4o changing GPT-3.5 Turbo on the ChatGPT user interface. Its API costs $0.15 per million [input tokens](https://git.jackbondpreston.me) and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI expects it to be especially useful for business, startups and designers seeking to [automate services](https://bpx.world) with [AI](https://www.aspira24.com) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have actually been created to take more time to think about their reactions, causing greater [accuracy](https://jmusic.me). These models are particularly efficient in science, coding, and thinking tasks, and were made available to ChatGPT Plus and . [209] [210] In December 2024, o1-preview was replaced by o1. [211] +
o3
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On December 20, 2024, OpenAI revealed o3, the follower of the o1 reasoning model. OpenAI likewise revealed o3-mini, a lighter and quicker variation 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 scientists had the chance to obtain early access to these designs. [214] The design is called o3 instead of o2 to avoid confusion with telecommunications providers O2. [215] +
Deep research study
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Deep research study is an agent developed by OpenAI, unveiled on February 2, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=12029182) 2025. It leverages the abilities of OpenAI's o3 model to perform substantial web surfing, information 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 evaluate the [semantic similarity](http://81.71.148.578080) in between text and images. It can notably be used for image classification. [217] +
Text-to-image
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DALL-E
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Revealed in 2021, DALL-E is a Transformer design that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and create matching images. It can develop images of realistic items ("a stained-glass window with a picture of a blue strawberry") as well as items that do not exist in truth ("a cube with the texture of a porcupine"). As of March 2021, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/3099171) 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 version of the design with more sensible results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new fundamental system for transforming a text description into a 3[-dimensional](https://astonvillafansclub.com) model. [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more powerful design much better able to generate images from complicated descriptions without manual prompt engineering and [wiki.eqoarevival.com](https://wiki.eqoarevival.com/index.php/User:LeonieTremblay6) render complex details like hands and text. [221] It was released to the 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 model that can generate videos based upon short detailed triggers [223] as well as extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of generated videos is unidentified.
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Sora's development team called it after the Japanese word for "sky", to symbolize its "endless creative capacity". [223] Sora's innovation is an adaptation of the innovation behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos licensed for that purpose, 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 create videos up to one minute long. It likewise shared a technical report highlighting the approaches utilized to train the design, and the model's abilities. [225] It acknowledged some of its imperfections, including struggles mimicing complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "remarkable", but noted that they should have been cherry-picked and might not represent Sora's typical output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, noteworthy entertainment-industry figures have actually revealed considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry [revealed](http://git.befish.com) his astonishment at the innovation's capability to create [realistic video](https://3.223.126.156) from text descriptions, mentioning its prospective to revolutionize storytelling and material production. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to pause prepare for broadening 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 acknowledgment model. [228] It is trained on a big dataset of varied audio and is likewise a multi-task model that can perform 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 tunes with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to begin fairly however then fall into mayhem the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the internet 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 specified the tunes "reveal regional musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that duplicate" which "there is a significant space" in between Jukebox and human-generated music. The Verge specified "It's technologically excellent, even if the outcomes sound like mushy variations of songs that might feel familiar", while Business Insider stated "remarkably, a few of the resulting tunes are appealing 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 whether such an approach might help in auditing [AI](http://8.137.54.213:9000) decisions and in establishing explainable [AI](https://meetpit.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of [visualizations](http://kiwoori.com) of every considerable layer and nerve cell of 8 neural network models which are often studied in interpretability. [240] Microscope was created to analyze the features that form inside these neural networks easily. The models included are AlexNet, VGG-19, different versions of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that offers a conversational user interface that permits users to ask concerns in natural language. The system then responds with a response within seconds.
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