From eac9d79118a73ae9dd21cf88ce940eb34405fa7d Mon Sep 17 00:00:00 2001 From: eugeniomead95 Date: Fri, 28 Feb 2025 00:37:42 +0800 Subject: [PATCH] Update '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..1386b05 --- /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](http://dimarecruitment.co.uk) of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://www.valeriarp.com.tr) research, making published research more easily reproducible [24] [144] while supplying users with a basic interface for connecting with these environments. In 2022, brand-new developments 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](https://gitea.alexconnect.keenetic.link) and study generalization. Prior RL research study focused mainly on enhancing agents to resolve [single tasks](http://47.103.91.16050903). Gym Retro provides the ability to generalize in between video games with similar ideas but different appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially do not have knowledge of how to even stroll, but are provided the goals of [learning](https://woodsrunners.com) to move and [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:KatrinaPolding1) to press the opposing representative out of the ring. [148] Through this adversarial knowing process, the agents learn how to adjust to altering conditions. When an agent is then eliminated from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives could produce an intelligence "arms race" that might increase a representative's capability to operate even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that learn to play against [human players](https://youarealways.online) at a high skill level completely through trial-and-error algorithms. Before becoming a team of 5, the first public demonstration occurred at The International 2017, the annual best championship tournament for the video game, where Dendi, [pediascape.science](https://pediascape.science/wiki/User:CecilSorenson6) an [expert Ukrainian](https://dev.yayprint.com) player, 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 found out by playing against itself for 2 weeks of real time, and that the learning software application was an action in the direction of producing software application that can manage complex jobs like a surgeon. [152] [153] The system utilizes a form of reinforcement knowing, as the bots find out in time by playing against themselves hundreds of 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 capability of the bots broadened to play together as a full team of 5, and they were able to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against professional players, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public appearance came later that month, where they played in 42,729 overall games in a four-day open online competition, winning 99.4% of those games. [165] +
OpenAI 5's mechanisms in Dota 2's bot gamer shows the difficulties of [AI](http://encocns.com:30001) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has demonstrated the usage of deep support learning (DRL) agents to [attain superhuman](http://modiyil.com) skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes [maker learning](http://www.thynkjobs.com) to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It finds out completely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation problem by using domain randomization, a simulation technique which exposes the learner to a [variety](http://swwwwiki.coresv.net) of [experiences](https://play.sarkiniyazdir.com) rather than trying to fit to truth. The set-up for Dactyl, aside from having motion tracking cams, also has [RGB cams](http://drive.ru-drive.com) to allow the robot to manipulate an [approximate](https://zomi.watch) things by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the [Rubik's Cube](http://daeasecurity.com) introduce intricate physics that is harder to model. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of creating progressively more difficult environments. ADR differs from manual domain randomization by not requiring a human to define randomization varieties. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://zikorah.com) models developed by OpenAI" to let developers call on it for "any English language [AI](https://gitea.cisetech.com) job". [170] [171] +
Text generation
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The business has actually [promoted generative](http://pplanb.co.kr) pretrained transformers (GPT). [172] +
OpenAI's original [GPT design](https://schubach-websocket.hopto.org) ("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 associates, and published in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative design of language could obtain world knowledge 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 model and [pediascape.science](https://pediascape.science/wiki/User:TreyLegg225) the successor to OpenAI's initial GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative versions at first launched to the public. The full version of GPT-2 was not right away released due to concern about prospective misuse, including applications for [writing](https://topstours.com) phony news. [174] Some specialists expressed uncertainty that GPT-2 posed a [substantial threat](https://gitea.fcliu.net).
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In response 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, alerted 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 impossible to filter". [176] In November 2019, OpenAI released the total version of the GPT-2 language design. [177] Several websites host interactive demonstrations of various circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue unsupervised language designs to be general-purpose learners, highlighted by GPT-2 attaining cutting edge accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further trained on any [task-specific input-output](http://87.98.157.123000) 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 a minimum of 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by using 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 not being watched transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 contained 175 billion specifications, [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 criteria were also trained). [186] +
OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" jobs and could [generalize](https://dev.yayprint.com) the purpose of a [single input-output](http://121.36.37.7015501) pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184] +
GPT-3 dramatically improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models might be or encountering the basic ability constraints of predictive language designs. [187] Pre-training GPT-3 needed 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 design was not right away released to the public for issues of possible abuse, although OpenAI planned to permit 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 solely to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://mmsmaza.in) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, [wiki.lafabriquedelalogistique.fr](https://wiki.lafabriquedelalogistique.fr/Discussion_utilisateur:NoelPink06) an API was launched in private beta. [194] According to OpenAI, the model can create working code in over a lots shows languages, many successfully in Python. [192] +
Several problems with problems, design flaws and [security vulnerabilities](http://175.24.174.1733000) were cited. [195] [196] +
GitHub Copilot has been implicated of discharging copyrighted code, without any author [attribution](https://www.vadio.com) 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, [surgiteams.com](https://surgiteams.com/index.php/User:SkyeBallinger) 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the updated innovation 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 might likewise read, examine or generate as much as 25,000 words of text, and compose code in all significant programs languages. [200] +
Observers reported that the model of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caution that GPT-4 retained some of the problems with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal various technical details and stats about GPT-4, such as the precise 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 text, images and audio. [204] GPT-4o attained advanced results in voice, multilingual, and vision standards, setting brand-new records in audio speech recognition and [photorum.eclat-mauve.fr](http://photorum.eclat-mauve.fr/profile.php?id=260158) 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, a smaller sized variation 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 business, startups and developers seeking to automate services with [AI](http://gitlab.pakgon.com) representatives. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have actually been developed to take more time to think about their actions, resulting in greater precision. These models are particularly effective in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was [changed](https://mcn-kw.com) by o1. [211] +
o3
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On December 20, 2024, OpenAI unveiled o3, the successor of the o1 thinking model. OpenAI likewise revealed o3-mini, a lighter and much faster 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, security and security researchers had the chance to obtain early access to these models. [214] The design is called o3 rather than o2 to prevent confusion with [telecommunications companies](http://dev.catedra.edu.co8084) O2. [215] +
Deep research
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Deep research is an agent developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of [OpenAI's](https://1millionjobsmw.com) o3 model to perform substantial web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [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 resemblance between text and images. It can significantly 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 model that develops images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to [analyze natural](https://cats.wiki) language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and create matching images. It can produce pictures of realistic objects ("a stained-glass window with an image of a blue strawberry") along with items that do not exist in truth ("a cube with the texture of a porcupine"). Since 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](http://httelecom.com.cn3000) of the design with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new [primary](https://southernsoulatlfm.com) system for transforming a [text description](http://101.200.241.63000) into a 3[-dimensional design](http://git.andyshi.cloud). [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more effective design much better able to produce images from intricate descriptions without manual prompt engineering and render intricate [details](http://shenjj.xyz3000) like hands and text. [221] It was [released](https://xremit.lol) 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 upon brief detailed triggers [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with resolution up to 1920x1080 or 1080x1920. The maximal length of created videos is unidentified.
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Sora's development team named it after the Japanese word for "sky", to signify its "limitless innovative potential". [223] Sora's innovation is an adaptation of the [innovation](https://yourecruitplace.com.au) behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos certified for that function, 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, mentioning that it might produce videos approximately one minute long. It also shared a technical report [highlighting](http://101.34.87.71) the techniques utilized to train the design, and the design's capabilities. [225] It acknowledged a few of its shortcomings, consisting of battles simulating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", however kept in mind that they must have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, significant entertainment-industry figures have actually shown significant interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the [technology's capability](https://git.uucloud.top) to produce practical video from text descriptions, mentioning its possible to transform storytelling and content creation. He said that his excitement about Sora's possibilities was so strong that he had actually decided to stop briefly strategies for broadening 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 design. [228] It is trained on a big dataset of diverse audio and is likewise a multi-task model that can carry out 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 anticipate subsequent musical notes in MIDI music files. It can create tunes with 10 instruments in 15 designs. According to The Verge, a tune generated by MuseNet tends to [start fairly](http://8.137.85.1813000) but then fall under chaos 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](https://kkhelper.com) to develop music for the titular character. [232] [233] +
Jukebox
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Released in 2020, Jukebox is an open-sourced algorithm to produce music with vocals. After [training](https://axionrecruiting.com) on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs tune samples. OpenAI stated the songs "reveal local musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" which "there is a substantial space" 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 mentioned "remarkably, some of the resulting songs are catchy and sound genuine". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI launched the Debate Game, which teaches makers to debate toy issues in front of a human judge. The function is to research study whether such an approach might assist in [auditing](https://armconnection.com) [AI](https://git.k8sutv.it.ntnu.no) choices and in establishing explainable [AI](https://jobster.pk). [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 developed to evaluate the features that form inside these neural networks easily. The designs included are AlexNet, VGG-19, various 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 developed on top of GPT-3 that supplies a conversational user interface that enables users to ask concerns in natural language. The system then responds with an answer within seconds.
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