From d34c49f9d6756ac4e328c01b381e56f866a066f9 Mon Sep 17 00:00:00 2001 From: melinda44c9606 Date: Sat, 22 Feb 2025 16:39:33 +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..9a79463 --- /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 support knowing algorithms. It aimed to standardize how environments are defined in [AI](http://elektro.jobsgt.ch) research, making published research more quickly reproducible [24] [144] while [supplying](http://devhub.dost.gov.ph) users with a basic interface for engaging with these environments. In 2022, brand-new developments 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 reinforcement knowing (RL) research 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 provides the ability to generalize between games with similar ideas but various looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents initially lack understanding of how to even stroll, however are provided the objectives of discovering to move and to push the opposing agent out of the ring. [148] Through this [adversarial learning](https://epspatrolscv.com) procedure, the agents find out how to adapt to changing conditions. When an agent is then eliminated from this virtual environment and put in a brand-new virtual environment with high winds, the agent braces to remain upright, recommending it had actually discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could develop 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 group of 5 OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that discover to play against human players at a high skill level entirely through trial-and-error algorithms. Before ending up being a team of 5, the first public presentation took place at The International 2017, the annual best championship competition for the video game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually matchup. [150] [151] After the match, [CTO Greg](https://sss.ung.si) Brockman explained that the bot had discovered by playing against itself for 2 weeks of actual time, which the learning software application was an action in the instructions of creating software that can manage intricate jobs like a surgeon. [152] [153] The system uses a kind of support knowing, as the bots learn gradually by playing against themselves numerous 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 broadened to play together as a complete group 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 2 exhibition matches against professional players, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champions 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 competitors, [surgiteams.com](https://surgiteams.com/index.php/User:FlynnBrinker) winning 99.4% of those games. [165] +
OpenAI 5's systems in Dota 2's bot player shows the challenges of [AI](https://git.goolink.org) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has demonstrated making use of deep reinforcement [learning](http://5.34.202.1993000) (DRL) agents to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes [device finding](http://121.40.81.1163000) out to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It learns entirely in simulation using the exact same RL algorithms and training code as OpenAI Five. [OpenAI tackled](https://wiki.cemu.info) the object orientation problem by utilizing domain randomization, a simulation method which exposes the learner to a variety of experiences instead of [attempting](https://copyright-demand-letter.com) to fit to reality. The set-up for Dactyl, aside from having movement tracking electronic cameras, likewise has RGB cams to enable the robotic to manipulate an approximate item by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl could solve a [Rubik's Cube](http://122.51.51.353000). The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce intricate physics that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a [simulation method](https://stationeers-wiki.com) of generating progressively harder environments. ADR varies from manual domain randomization by not needing 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 brand-new [AI](https://youarealways.online) models established by OpenAI" to let developers get in touch with it for "any English language [AI](https://git.logicloop.io) job". [170] [171] +
Text generation
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The business has actually popularized generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("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 website on June 11, 2018. [173] It revealed how a generative model of language could obtain world understanding and procedure long-range dependences by pre-training on a varied corpus with long stretches of contiguous text.
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GPT-2
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Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer [language](https://tricityfriends.com) design and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, [garagesale.es](https://www.garagesale.es/author/trenapridha/) with just restricted demonstrative versions initially released to the general public. The complete variation of GPT-2 was not immediately launched due to concern about prospective abuse, consisting of applications for composing phony news. [174] Some professionals revealed uncertainty that GPT-2 presented a considerable risk.
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In response to GPT-2, the Allen Institute for Artificial Intelligence [responded](https://picturegram.app) with a tool to find "neural fake news". [175] Other researchers, such as Jeremy Howard, alerted of "the technology to completely 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 complete version of the GPT-2 language design. [177] Several websites host interactive demonstrations of different circumstances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue without supervision language designs to be general-purpose learners, illustrated by GPT-2 attaining state-of-the-art precision 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 slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain concerns encoding vocabulary with word tokens by [utilizing byte](https://git.cocorolife.tw) 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, [wakewiki.de](https://www.wakewiki.de/index.php?title=The_Verge_Stated_It_s_Technologically_Impressive) Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language design 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 full variation of GPT-2 (although GPT-3 designs with as couple of as 125 million specifications were also trained). [186] +
OpenAI mentioned that GPT-3 was successful at certain "meta-learning" jobs and might generalize the purpose 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 between [English](https://iadgroup.co.uk) and German. [184] +
GPT-3 dramatically enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or coming across the essential capability constraints of predictive language models. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly released to the public for issues of possible abuse, [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:BettyJarnagin) although OpenAI planned 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 licensed solely to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://savico.com.br) 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 programming languages, most successfully in Python. [192] +
Several issues with glitches, design flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been implicated of releasing copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would stop 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 in accepting text or image inputs. [199] They revealed that the updated technology 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 also check out, examine or generate up to 25,000 words of text, and write code in all major programming languages. [200] +
Observers reported that the version 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](https://starttrainingfirstaid.com.au) to reveal different 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 announced and released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained cutting edge results in voice, multilingual, and vision standards, 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 to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI launched GPT-4o mini, a smaller variation 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 anticipates](https://spudz.org) it to be especially beneficial for business, start-ups and developers looking for to [automate services](https://gitlab.grupolambda.info.bo) with [AI](http://47.100.17.114) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have actually been developed to take more time to consider their responses, causing higher [precision](https://rosaparks-ci.com). These models are especially efficient in science, coding, and reasoning tasks, and were made available to [ChatGPT](https://git.goolink.org) Plus and [Employee](https://mypocket.cloud). [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 successor of the o1 reasoning design. OpenAI also unveiled o3-mini, a lighter and faster version of OpenAI o3. Since December 21, 2024, this design is not available for public usage. 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 providers O2. [215] +
Deep research study
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Deep research is an [agent established](https://retailjobacademy.com) by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out [comprehensive web](http://dkjournal.co.kr) browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools made it possible for, 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 analyze the semantic similarity in between text and images. It can especially be utilized 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 model that [develops images](https://www.9iii9.com) from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to analyze natural language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can produce pictures of [reasonable items](https://www.nairaland.com) ("a stained-glass window with a picture of a blue strawberry") in addition to objects 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 announced DALL-E 2, an updated variation of the design with more realistic outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new basic system for transforming a text description into a 3-dimensional 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 [produce](https://www.schoenerechner.de) images from intricate descriptions without manual [timely engineering](http://110.42.178.1133000) and render [intricate details](https://www.ch-valence-pro.fr) like hands and text. [221] It was launched to the general public as a [ChatGPT](http://121.43.121.1483000) Plus [feature](http://118.25.96.1183000) in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video design 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 produce videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.
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Sora's advancement group called it after the Japanese word for "sky", to symbolize its "limitless imaginative capacity". [223] Sora's technology is an adjustment of the technology behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos certified 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 also shared a technical report highlighting the methods used to train the model, and the model's capabilities. [225] It acknowledged some of its imperfections, including struggles replicating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "remarkable", but kept in mind that they should have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:MariaKuehner) noteworthy entertainment-industry figures have actually shown substantial interest in the innovation's potential. In an interview, actor/[filmmaker Tyler](http://t93717yl.bget.ru) Perry revealed his awe at the innovation's ability to create practical video from text descriptions, citing its potential to reinvent storytelling and [material production](https://karis.id). He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to stop briefly prepare for broadening his [Atlanta-based movie](https://git.progamma.com.ua) 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 large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition in addition to speech translation and [language recognition](https://platform.giftedsoulsent.com). [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 songs with 10 instruments in 15 designs. According to The Verge, a song generated by MuseNet tends to begin fairly however then fall under turmoil the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized as early as 2020 for the internet psychological thriller Ben Drowned to develop 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 bit of lyrics and outputs tune samples. OpenAI stated the songs "show regional musical coherence [and] follow standard chord patterns" but acknowledged that the songs do not have "familiar bigger musical structures such as choruses that repeat" and that "there is a substantial gap" in between Jukebox and human-generated music. The Verge stated "It's technically excellent, even if the outcomes sound like mushy variations of songs that may feel familiar", while Business Insider mentioned "remarkably, some of the resulting tunes are appealing and sound genuine". [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 dispute toy problems in front of a human judge. The purpose is to research whether such a method might help in auditing [AI](https://puzzle.thedimeland.com) decisions and in developing explainable [AI](https://video.clicktruths.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and neuron of eight neural network models which are often studied in interpretability. [240] Microscope was produced to examine the features that form inside these neural networks easily. The designs included are AlexNet, VGG-19, different versions of Inception, and different versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an [artificial intelligence](https://www.jobassembly.com) tool built on top of GPT-3 that provides a that allows users to ask concerns in natural language. The system then responds with an answer within seconds.
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