From 6a3c4ecc3163f82515bf126f9564e691fba37d32 Mon Sep 17 00:00:00 2001 From: rosalinelukis Date: Sat, 15 Mar 2025 07:13:09 +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..85d33dc --- /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 assist in the development of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](http://42.192.14.135:3000) research study, making released research study more quickly reproducible [24] [144] while providing users with a basic interface for communicating with these environments. In 2022, new advancements of Gym have been transferred to the [library Gymnasium](https://media.izandu.com). [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support knowing (RL) research study on video games [147] using RL algorithms and research study generalization. Prior RL research focused mainly on enhancing agents to solve single tasks. Gym Retro offers the capability to generalize in between video games with similar principles but different looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot representatives initially lack knowledge of how to even walk, but are given the goals of finding out to move and to push the [opposing representative](https://lovematch.vip) out of the ring. [148] Through this adversarial learning procedure, the agents find out how to adapt to altering conditions. When a representative is then removed from this virtual environment and put in a new virtual environment with high winds, the representative braces to remain upright, recommending it had discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents might produce an intelligence "arms race" that might increase a representative's ability to function even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that learn to play against human players at a high skill level entirely through experimental algorithms. Before becoming a group of 5, the first public demonstration occurred at The International 2017, the annual premiere championship competition for the video game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually matchup. [150] [151] After the match, [CTO Greg](https://c3tservices.ca) Brockman explained that the bot had learned by playing against itself for two weeks of genuine time, and that the knowing software was an action in the direction of producing software application that can deal with complex jobs like a cosmetic surgeon. [152] [153] The system uses a kind of reinforcement knowing, as the bots learn with time by playing against themselves numerous times a day for months, and [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:EricGooding) are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156] +
By June 2018, the ability of the [bots broadened](http://gitlab.iyunfish.com) to play together as a full team of 5, and they were able to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert players, but wound up losing both 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 public appearance came later that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those games. [165] +
OpenAI 5's systems in Dota 2's bot gamer reveals the obstacles of [AI](https://git.mitsea.com) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually demonstrated making use of deep support learning (DRL) representatives to [attain superhuman](https://www.dutchsportsagency.com) proficiency in Dota 2 [matches](https://sondezar.com). [166] +
Dactyl
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[Developed](http://185.87.111.463000) in 2018, Dactyl uses device learning to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It learns completely in simulation using the very same RL algorithms and [gratisafhalen.be](https://gratisafhalen.be/author/cagrandi518/) training code as OpenAI Five. OpenAI dealt with the item orientation problem by utilizing domain randomization, a simulation [technique](https://git.toolhub.cc) which exposes the learner to a range of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having [movement tracking](https://se.mathematik.uni-marburg.de) cams, likewise has RGB cams to permit the robot to manipulate an arbitrary things by seeing it. In 2018, OpenAI showed that the system had the ability to control a cube and an [octagonal prism](https://v-jobs.net). [168] +
In 2019, OpenAI demonstrated that Dactyl could solve a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to model. OpenAI did this by improving the robustness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation method of creating gradually harder environments. ADR varies from manual domain randomization by not needing a human to specify randomization varieties. [169] +
API
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In June 2020, OpenAI announced a [multi-purpose API](https://welcometohaiti.com) which it said was "for accessing brand-new [AI](http://docker.clhero.fun:3000) designs established by OpenAI" to let developers call on it for "any English language [AI](https://kryza.network) job". [170] [171] +
Text generation
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The business has actually promoted generative pretrained transformers (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 model was written by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative design of language might obtain world knowledge and procedure long-range dependences 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 a without supervision transformer [language design](https://socialcoin.online) and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative variations initially released to the general public. The full variation of GPT-2 was not right away [launched](https://www.informedica.llc) due to concern about possible abuse, [including applications](http://git.iloomo.com) for composing fake news. [174] Some experts expressed uncertainty that GPT-2 positioned a [substantial danger](https://www.pickmemo.com).
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In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to find "neural phony news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation 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](https://www.seekbetter.careers) the complete variation of the GPT-2 language model. [177] Several sites host interactive demonstrations of various instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being watched language designs to be general-purpose students, highlighted by GPT-2 attaining cutting edge precision 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, [gratisafhalen.be](https://gratisafhalen.be/author/lewisdescot/) contains somewhat 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 [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:KarissaGleason) the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 contained 175 billion parameters, [184] 2 orders of [magnitude bigger](http://code.chinaeast2.cloudapp.chinacloudapi.cn) than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as few as 125 million specifications were likewise trained). [186] +
OpenAI stated that GPT-3 prospered at certain "meta-learning" jobs and might generalize the function of a single input-output pair. The GPT-3 release paper offered examples of translation and [cross-linguistic transfer](https://git.revoltsoft.ru) knowing between English and Romanian, and between English and German. [184] +
GPT-3 significantly improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs could be approaching or coming across the essential capability constraints of [predictive language](http://www.colegio-sanandres.cl) designs. [187] Pre-training GPT-3 required a number of thousand petaflop/s-days [b] of compute, 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 released to the public for issues of possible abuse, although [OpenAI prepared](https://higgledy-piggledy.xyz) to enable to through a paid cloud API after a two-month complimentary personal beta that began in June 2020. [170] [189] +
On September 23, 2020, [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:SophieBloom4921) GPT-3 was licensed solely 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 on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://manchesterunitedfansclub.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the design can [produce](https://matchpet.es) working code in over a lots shows languages, the majority of successfully in Python. [192] +
Several concerns with problems, style flaws and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has been implicated of giving off copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would cease 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](http://124.71.134.1463000) in accepting text or image inputs. [199] They announced that the updated innovation passed a simulated law school bar examination 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 might also check out, evaluate or generate approximately 25,000 words of text, and write code in all major programs languages. [200] +
Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has actually declined to reveal numerous technical details and stats 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 produce text, images and audio. [204] GPT-4o attained advanced results in voice, multilingual, and vision criteria, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard [compared](http://47.100.220.9210001) 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 and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI expects it to be especially useful for enterprises, start-ups and designers looking for to automate services with [AI](https://code.paperxp.com) representatives. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and [pediascape.science](https://pediascape.science/wiki/User:HymanRangel8) o1-mini designs, which have been created to take more time to think about their responses, leading to greater accuracy. These designs are especially effective in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [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 model. OpenAI also unveiled o3-mini, a lighter and quicker version of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecommunications companies O2. [215] +
Deep research study
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Deep research is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 design to carry out comprehensive web surfing, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:Polly21A38) data analysis, and synthesis, providing detailed reports within a [timeframe](https://git.schdbr.de) of 5 to thirty minutes. [216] With browsing and Python tools enabled, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) standard. [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 evaluate the semantic resemblance in between text and images. It can notably 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 design 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 an unfortunate capybara") and generate corresponding images. It can create images of reasonable things ("a stained-glass window with an image of a blue strawberry") along with items 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 version of the design with more practical outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new rudimentary system for converting a text description into a 3[-dimensional](https://tawtheaf.com) model. [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more effective model better able to create images from complex descriptions without manual timely engineering and render complicated details like hands and text. [221] It was launched to the public as a ChatGPT Plus function in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video model that can produce videos based on brief detailed prompts [223] as well as extend existing [videos forwards](https://ravadasolutions.com) or [backwards](https://omegat.dmu-medical.de) in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.
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Sora's advancement team called it after the Japanese word for "sky", to represent its "limitless innovative potential". [223] Sora's technology 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 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 might produce videos approximately one minute long. It also shared a technical report highlighting the approaches utilized to train the design, and the design's abilities. [225] It acknowledged some of its drawbacks, including struggles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", but kept in mind that they need to have been cherry-picked and may not represent Sora's typical output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have shown substantial interest in the [innovation's capacity](https://git.foxarmy.org). In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's capability to produce realistic video from text descriptions, citing its prospective to change storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had chosen to pause prepare for [broadening](https://git.iidx.ca) his Atlanta-based film studio. [227] +
Speech-to-text
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Whisper
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[Released](http://www.localpay.co.kr) in 2022, Whisper is a general-purpose speech acknowledgment design. [228] It is trained on a large dataset of diverse audio and is likewise a multi-task model that can perform multilingual speech [recognition](https://phoebe.roshka.com) 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 forecast subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to begin fairly however then fall into turmoil the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized 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 category, artist, and a bit of lyrics and outputs tune samples. OpenAI stated the tunes "show local musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that repeat" and that "there is a significant gap" in between Jukebox and [human-generated music](http://118.190.88.238888). The Verge stated "It's highly outstanding, even if the results seem like mushy versions of songs that might feel familiar", while Business Insider specified "remarkably, some 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 to debate toy problems in front of a human judge. The purpose is to research study whether such a technique might assist in auditing [AI](http://117.71.100.222:3000) choices and in establishing explainable [AI](http://www.colegio-sanandres.cl). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and nerve cell of eight neural network models which are frequently studied in interpretability. [240] Microscope was created to examine the features that form inside these neural networks easily. The [models consisted](https://wiki.awkshare.com) of are AlexNet, VGG-19, various versions of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an artificial intelligence tool constructed on top of GPT-3 that supplies a conversational interface that allows users to ask concerns in natural language. The system then reacts with a response within seconds.
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