From ee3e34c94ba9fa20b7bc728edc1fdaa96cab6f21 Mon Sep 17 00:00:00 2001 From: meljessup8482 Date: Fri, 28 Feb 2025 22:39:49 +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..15ebab1 --- /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 help with the advancement of reinforcement knowing [algorithms](https://lifefriendsurance.com). It aimed to standardize how environments are defined in [AI](https://git.corp.xiangcms.net) research study, making released research study more easily reproducible [24] [144] while providing users with a simple user interface for connecting with these environments. In 2022, new advancements of Gym have been transferred to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support knowing (RL) research on computer game [147] using RL algorithms and research study [generalization](http://47.101.207.1233000). Prior RL research focused mainly on optimizing representatives to resolve single tasks. Gym Retro offers the ability to generalize in between games with comparable 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 offered the goals of learning to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the representatives discover how to adjust to changing conditions. When a representative is then gotten rid of from this virtual environment and positioned in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had learned how to [stabilize](https://proputube.com) in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives could create an intelligence "arms race" that might increase an agent's ability to function even outside the context of the [competition](http://47.100.81.115). [148] +
OpenAI 5
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OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that find out to play against human players at a high ability level completely through experimental algorithms. Before becoming a team of 5, the first public demonstration happened at The International 2017, the yearly premiere champion tournament for the game, where Dendi, [wiki.lafabriquedelalogistique.fr](https://wiki.lafabriquedelalogistique.fr/Utilisateur:GiuseppeGlenelg) a professional Ukrainian player, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for two weeks of actual time, and that the knowing software was a step in the direction of creating software that can deal with complex tasks like a surgeon. [152] [153] The system utilizes a kind of support learning, as the bots learn with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an opponent and taking map goals. [154] [155] [156] +
By June 2018, the ability of the bots expanded to play together as a full team of 5, and they had the ability to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against professional players, but ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final [public appearance](http://globalnursingcareers.com) came later on that month, where they played in 42,729 total 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 player reveals the obstacles of [AI](http://120.26.108.239:9188) systems in multiplayer online [fight arena](http://112.74.102.696688) (MOBA) games and how OpenAI Five has actually shown the usage of deep support learning (DRL) agents to [attain superhuman](https://git.toolhub.cc) skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses [maker learning](https://careers.synergywirelineequipment.com) to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It discovers entirely in [simulation](http://58.34.54.469092) using the exact same RL algorithms and training code as OpenAI Five. OpenAI took on the things orientation issue by utilizing domain randomization, a simulation method which exposes the student to a range of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking electronic cameras, also has RGB video cameras to allow the robotic to manipulate an approximate things by seeing it. In 2018, OpenAI showed that the system had the ability to [manipulate](https://hrvatskinogomet.com) a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl could fix a Rubik's Cube. The robot had the ability to solve the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to [perturbations](http://40th.jiuzhai.com) by utilizing Automatic Domain Randomization (ADR), a simulation technique of producing gradually more difficult environments. 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 revealed a multi-purpose API which it said was "for accessing new [AI](http://113.177.27.200:2033) designs established by OpenAI" to let developers contact it for "any English language [AI](https://aladin.social) task". [170] [171] +
Text generation
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The company has popularized generative pretrained transformers (GPT). [172] +
OpenAI's original 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 associates, and published in preprint on OpenAI's website on June 11, 2018. [173] It [demonstrated](https://globalabout.com) how a generative model of language could obtain world knowledge and process long-range dependences 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](http://202.90.141.173000) 2 ("GPT-2") is an unsupervised transformer language model and the follower to [OpenAI's initial](https://video.spacenets.ru) GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative variations at first released to the general public. The full version of GPT-2 was not instantly released due to issue about possible misuse, [including applications](http://114.132.230.24180) for writing fake news. [174] Some professionals revealed uncertainty that GPT-2 positioned a [substantial hazard](http://stockzero.net).
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "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 muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the total variation of the GPT-2 language design. [177] Several websites host interactive demonstrations of various circumstances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue unsupervised language models to be general-purpose students, illustrated by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 [zero-shot tasks](https://git.yqfqzmy.monster) (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 slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This allows 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](https://www.koumii.com) language design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 contained 175 billion criteria, [184] 2 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 [criteria](https://gitea.umrbotech.com) were likewise trained). [186] +
OpenAI specified that GPT-3 was successful at certain "meta-learning" tasks and might generalize the function of a 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 significantly improved benchmark results over GPT-2. OpenAI cautioned that such [scaling-up](http://zhandj.top3000) of language models could be approaching or coming across the fundamental capability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately launched to the general public for concerns of possible abuse, although OpenAI prepared to permit gain access to through a paid [cloud API](https://subemultimedia.com) 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 furthermore been [trained](https://gitlab.ui.ac.id) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://cyberbizafrica.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can create working code in over a dozen shows languages, most effectively in Python. [192] +
Several concerns with problems, design flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been implicated of discharging copyrighted code, without any author attribution or license. [197] +
OpenAI revealed 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), capable of [accepting text](https://www.heesah.com) or image inputs. [199] They announced that the updated innovation passed a simulated law school bar examination with a rating around the leading 10% of [test takers](https://git.gilgoldman.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, analyze or create up to 25,000 words of text, and write code in all significant programming languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained some of the issues with earlier modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose numerous technical details and stats about GPT-4, such as the accurate size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained advanced outcomes 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) benchmark compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI released GPT-4o mini, [wavedream.wiki](https://wavedream.wiki/index.php/User:ShaylaColton441) 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 to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be particularly helpful for enterprises, startups and designers looking for to automate services with [AI](http://demo.ynrd.com:8899) 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 actions, causing higher precision. These models are especially efficient in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was changed by o1. [211] +
o3
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On December 20, 2024, OpenAI unveiled o3, the successor [garagesale.es](https://www.garagesale.es/author/jonathanfin/) of the o1 thinking model. OpenAI likewise revealed o3-mini, a lighter and faster variation of OpenAI o3. As of December 21, 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, safety and security researchers had the chance to obtain early access to these designs. [214] The model is called o3 instead of o2 to prevent confusion with telecoms companies O2. [215] +
Deep research
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Deep research is an agent developed by OpenAI, [unveiled](http://jsuntec.cn3000) on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to perform comprehensive web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] +
Image category
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CLIP
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Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to examine the semantic similarity 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 design that develops images from textual descriptions. [218] DALL-E utilizes a 12[-billion-parameter variation](https://www.oddmate.com) of GPT-3 to translate natural language inputs (such as "a green leather purse formed like a pentagon" or "an isometric view of an unfortunate capybara") and generate corresponding images. It can create pictures of [practical](https://actsfile.com) things ("a stained-glass window with a picture of a blue strawberry") in addition to items that do not exist in truth ("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 design with more sensible outcomes. [219] In December 2022, OpenAI published on GitHub software for Point-E, a brand-new simple system for transforming a text description into a 3-dimensional model. [220] +
DALL-E 3
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In September 2023, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11983461) OpenAI announced DALL-E 3, a more powerful model better able to [generate](https://vlogloop.com) images from intricate descriptions without manual prompt engineering and render [complicated details](http://47.108.105.483000) like hands and text. [221] It was launched 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 design 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 produce videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of produced videos is unidentified.
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Sora's development group named it after the Japanese word for "sky", to represent its "unlimited innovative capacity". [223] Sora's technology is an [adjustment](http://182.230.209.608418) of the innovation behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos as well as copyrighted videos licensed for that purpose, however did not expose 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, 2024, mentioning that it could produce videos as much as one minute long. It likewise shared a technical report highlighting the approaches used to train the model, and the model's capabilities. [225] It acknowledged some of its imperfections, including struggles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", however noted that they need to have been cherry-picked and may not represent Sora's common output. [225] +
Despite uncertainty from some [scholastic leaders](https://www.sociopost.co.uk) following Sora's public demonstration, significant entertainment-industry figures have shown significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's capability to generate realistic video from text descriptions, mentioning its potential to reinvent storytelling and content creation. He said that his enjoyment about Sora's possibilities was so strong that he had actually [decided](https://gitea.lelespace.top) to pause strategies for expanding his Atlanta-based film studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, Whisper is a general-purpose speech acknowledgment design. [228] It is trained on a large dataset of varied audio and is also a [multi-task](https://job4thai.com) model that can perform multilingual speech recognition in addition to speech translation and [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:Reda5208097820) 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](https://www.wotape.com) notes in MIDI music files. It can create tunes with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to begin fairly but then fall under turmoil 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 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 category, artist, and a [snippet](http://115.238.48.2109015) of lyrics and outputs tune samples. OpenAI mentioned the songs "reveal regional musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes lack "familiar larger musical structures such as choruses that repeat" and that "there is a significant space" between Jukebox and human-generated music. The Verge mentioned "It's technically outstanding, even if the outcomes sound like mushy variations of songs that might feel familiar", while Business Insider specified "remarkably, a few of the resulting tunes are appealing and sound genuine". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI released the Debate Game, which teaches devices to debate toy issues in front of a human judge. The function is to research whether such a method might help in auditing [AI](https://media.motorsync.co.uk) choices and in establishing explainable [AI](https://www.alkhazana.net). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and neuron of 8 neural network designs which are often studied in interpretability. [240] Microscope was developed to examine the features that form inside these neural networks quickly. The designs consisted of are AlexNet, VGG-19, different versions of Inception, and various variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system tool built on top of GPT-3 that supplies a conversational user interface that enables users to ask [questions](https://nerm.club) in natural language. The system then reacts with an answer within seconds.
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