From e63d9584fd1603b32604c0af20dc2241870f89a9 Mon Sep 17 00:00:00 2001 From: manualhamel688 Date: Sat, 12 Apr 2025 18:49:15 +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..9e40df8 --- /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](https://yeetube.com) of support learning algorithms. It aimed to standardize how environments are specified in [AI](http://8.139.7.166:10880) research study, making released research more quickly reproducible [24] [144] while offering users with an easy interface for interacting with these environments. In 2022, 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 reinforcement learning (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on optimizing agents to solve single tasks. Gym Retro provides the capability to generalize in between video games with similar principles however various appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives at first lack knowledge of how to even walk, but are given the objectives of discovering to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the [representatives](https://clickcareerpro.com) find out how to adapt to changing conditions. When a [representative](https://gitea.ravianand.me) is then gotten rid of from this virtual environment and put in a brand-new virtual environment with high winds, the representative braces to remain upright, recommending it had learned how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that [competition](https://www.pkjobs.store) between representatives could produce an intelligence "arms race" that could increase an agent's ability 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 learn to play against human players at a high ability level completely through trial-and-error algorithms. Before ending up being a group of 5, the very first public demonstration occurred at The International 2017, the yearly best championship competition for the video game, where Dendi, an [expert Ukrainian](http://103.77.166.1983000) gamer, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually found out by playing against itself for two weeks of actual time, which the knowing software application was a step in the instructions of developing software that can deal with complicated 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 hundreds of times a day for months, and are rewarded for actions such as killing an enemy and taking map goals. [154] [155] [156] +
By June 2018, the ability of the bots expanded to play together as a complete 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 two exhibit matches against professional players, but wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world [champions](http://getthejob.ma) of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games. [165] +
OpenAI 5['s mechanisms](https://napvibe.com) in Dota 2's bot player reveals the challenges of [AI](https://chatgay.webcria.com.br) [systems](https://jobspage.ca) in [multiplayer online](https://wiki.contextgarden.net) fight arena (MOBA) games and how OpenAI Five has demonstrated the usage of deep reinforcement knowing (DRL) representatives to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses device finding out to train a Shadow Hand, a human-like robot hand, to control physical things. [167] It finds out completely in [simulation](https://localglobal.in) using the very same RL algorithms and training code as OpenAI Five. OpenAI took on the things orientation problem by using domain randomization, a simulation method which exposes the learner to a variety of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having motion tracking cams, also has [RGB cams](https://wavedream.wiki) to enable the robotic to manipulate an approximate object by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, [pediascape.science](https://pediascape.science/wiki/User:JosephCreswick1) OpenAI demonstrated that Dactyl might fix a Rubik's Cube. The robotic had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of creating gradually more difficult environments. ADR differs from manual domain randomization by not needing a human to define 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](https://www.celest-interim.fr) designs developed by OpenAI" to let designers call on it for "any English language [AI](http://www.boutique.maxisujets.net) task". [170] [171] +
Text generation
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The business has popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT design ("GPT-1")
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The original paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his coworkers, and released in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative model of language might obtain world understanding and process long-range dependencies 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 not being watched transformer language design and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative [variations](https://yourecruitplace.com.au) at first released to the public. The full version of GPT-2 was not instantly launched due to concern about prospective abuse, consisting of applications for writing phony news. [174] Some experts expressed uncertainty that GPT-2 posed a considerable danger.
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In action to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to discover "neural phony news". [175] Other researchers, 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 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 presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being watched language models to be [general-purpose](https://job-maniak.com) students, shown by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not additional 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 issues encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing 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 stated that the full version of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as few as 125 million parameters were likewise trained). [186] +
OpenAI mentioned that GPT-3 prospered at certain "meta-learning" jobs and could generalize the function of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer knowing in between English and Romanian, and in between English and German. [184] +
GPT-3 dramatically enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or experiencing the fundamental ability [constraints](http://101.42.248.1083000) of predictive language designs. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of compute, 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 public for concerns of possible abuse, although OpenAI prepared to enable 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 actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.ffho.net) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can create working code in over a dozen shows languages, the majority of effectively in Python. [192] +
Several issues with glitches, design defects and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has been implicated of emitting copyrighted code, without any author [attribution](http://plus-tube.ru) or license. [197] +
OpenAI announced that they would stop 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](https://www.celest-interim.fr) 4 (GPT-4), [capable](http://123.56.247.1933000) of [accepting](https://www.empireofember.com) text or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar test with a score around the leading 10% of [test takers](http://doosung1.co.kr). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise read, examine or generate up to 25,000 words of text, and compose code in all major programs languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained some of the issues with earlier revisions. [201] GPT-4 is also [capable](https://rrallytv.com) of taking images as input on ChatGPT. [202] OpenAI has declined to reveal different technical details and statistics about GPT-4, such as the accurate size of the model. [203] +
GPT-4o
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On May 13, 2024, [OpenAI revealed](http://47.109.30.1948888) and released GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained state-of-the-art lead to voice, multilingual, and vision benchmarks, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI released GPT-4o mini, a smaller 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, start-ups and designers seeking to automate services with [AI](http://cgi3.bekkoame.ne.jp) representatives. [208] +
o1
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On September 12, 2024, [OpenAI launched](https://warleaks.net) the o1-preview and o1-mini models, which have been created to take more time to think of their actions, resulting in higher precision. These designs 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 replaced by o1. [211] +
o3
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On December 20, 2024, OpenAI unveiled 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 model is not available for public usage. According to OpenAI, they are [checking](http://aat.or.tz) o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the [opportunity](https://iklanbaris.id) to obtain early access to these models. [214] The model is called o3 rather than o2 to avoid confusion with telecommunications services company O2. [215] +
Deep research study
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Deep research is an agent established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform comprehensive web surfing, information analysis, and synthesis, [delivering detailed](https://www.cvgods.com) reports within a timeframe of 5 to 30 minutes. [216] With browsing 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 model that is trained to analyze the semantic resemblance in between text and images. It can significantly be utilized for [wiki.myamens.com](http://wiki.myamens.com/index.php/User:LatishaShepherds) 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 utilizes a 12-billion-parameter version of GPT-3 to translate natural [language](https://abadeez.com) inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can produce images of reasonable objects ("a stained-glass window with a picture of a blue strawberry") as well as objects that do not exist in ("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 announced DALL-E 2, an upgraded version of the model with more sensible results. [219] In December 2022, [OpenAI published](http://kuzeydogu.ogo.org.tr) 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, OpenAI revealed DALL-E 3, a more powerful design much better able to create images from [intricate descriptions](https://nextodate.com) without manual [prompt engineering](http://xn--950bz9nf3c8tlxibsy9a.com) and render intricate 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 model that can generate videos based on brief detailed prompts [223] along with extend existing videos forwards or backwards in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of created videos is unidentified.
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Sora's advancement team named it after the Japanese word for "sky", to symbolize its "endless imaginative potential". [223] Sora's technology is an adaptation of the technology behind the DALL ยท E 3 [text-to-image model](https://redefineworksllc.com). [225] OpenAI trained the system utilizing publicly-available videos along with 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 public on February 15, 2024, stating that it could produce videos up to one minute long. It likewise shared a technical report highlighting the methods utilized to train the model, and the model's abilities. [225] It acknowledged a few of its drawbacks, consisting of battles mimicing complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", but kept in mind that they should have been cherry-picked and [pipewiki.org](https://pipewiki.org/wiki/index.php/User:WillardO98) may not represent Sora's typical output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, significant entertainment-industry figures have actually revealed substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's capability to produce sensible video from text descriptions, citing its possible to transform storytelling and content production. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to pause prepare 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 recognition model. [228] It is trained on a big dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition along with speech translation and language identification. [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 styles. According to The Verge, a tune produced by [MuseNet](https://gitea.b54.co) tends to start fairly however then fall into 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 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 snippet of lyrics and outputs song samples. OpenAI mentioned the tunes "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the songs lack "familiar larger musical structures such as choruses that duplicate" which "there is a substantial gap" in between Jukebox and human-generated music. The Verge stated "It's technologically impressive, even if the outcomes seem like mushy variations of tunes that may feel familiar", while Business Insider stated "remarkably, a few of the resulting songs are memorable and sound legitimate". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, OpenAI released the Debate Game, which teaches makers to debate toy issues in front of a human judge. The function is to research study whether such a method may assist in auditing [AI](https://gitea.freshbrewed.science) decisions and in establishing explainable [AI](https://usvs.ms). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of [visualizations](https://culturaitaliana.org) of every substantial layer and nerve cell of 8 neural network designs which are often studied in interpretability. [240] Microscope was created to evaluate the features that form inside these neural networks quickly. 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 interface that enables users to ask concerns in natural language. The system then responds with an answer within seconds.
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