From b082977666c4b419b4e035109074f541630e5936 Mon Sep 17 00:00:00 2001 From: rodolfoorosco Date: Fri, 7 Feb 2025 06:43:44 +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..71b62a7 --- /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 facilitate the advancement of support knowing algorithms. It aimed to standardize how environments are specified in [AI](http://49.234.213.44) research, making released research more quickly reproducible [24] [144] while providing users with a basic user interface for interacting with these environments. In 2022, brand-new advancements of Gym have been relocated 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 study on computer game [147] using RL algorithms and study generalization. Prior RL research study focused mainly on optimizing representatives to resolve single jobs. Gym Retro gives the capability to [generalize](https://www.kmginseng.com) between video games with similar ideas but various appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first lack understanding of how to even walk, however are offered the goals of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial [learning](https://git.esc-plus.com) process, the agents find out how to adjust to changing conditions. When a representative is then removed from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, recommending it had discovered how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition in between agents might create an intelligence "arms race" that could increase a representative'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 used in the competitive five-on-five computer game Dota 2, that find out to play against human gamers at a high skill level entirely through experimental algorithms. Before becoming a team of 5, the very first public demonstration occurred at The International 2017, the annual best champion competition for [fishtanklive.wiki](https://fishtanklive.wiki/User:DouglasWhitney) the video game, where Dendi, an expert 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 2 weeks of real time, and that the learning software was a step in the direction of creating software that can deal with [complicated jobs](https://thisglobe.com) like a surgeon. [152] [153] The system utilizes a form of learning, as the bots find out with 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 ability of the bots broadened to play together as a complete team of 5, and they had the ability to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against professional gamers, but ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champions 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 overall games in a four-day open online competition, winning 99.4% of those video games. [165] +
OpenAI 5's systems in Dota 2's bot player reveals the difficulties of [AI](http://busforsale.ae) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has demonstrated the usage of deep reinforcement learning (DRL) agents to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses maker learning to train a Shadow Hand, a human-like robot hand, to control physical items. [167] It finds out entirely in [simulation](https://ofebo.com) using the exact same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation issue by utilizing domain randomization, a [simulation](https://51.75.215.219) technique which exposes the [learner](https://gitea.neoaria.io) to a variety of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having movement tracking video cameras, likewise has RGB electronic [cameras](https://955x.com) to enable the robot to control an arbitrary things by seeing it. In 2018, OpenAI showed that the system had the ability to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl might solve a Rubik's Cube. The robotic had the ability to fix the puzzle 60% of the time. Objects like the [Rubik's Cube](https://asicwiki.org) introduce complex physics that is harder to model. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of creating gradually harder environments. ADR varies from manual domain randomization by not needing a human to define randomization ranges. [169] +
API
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In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](http://119.29.81.51) models developed by OpenAI" to let developers get in touch with it for "any English language [AI](https://git.jzmoon.com) job". [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 colleagues, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world knowledge and process long-range reliances 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 an unsupervised transformer language design and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only minimal demonstrative versions initially launched to the public. The complete version of GPT-2 was not instantly launched due to concern about potential abuse, including applications for writing phony news. [174] Some specialists expressed uncertainty that GPT-2 positioned a significant danger.
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In response to GPT-2, the Allen [Institute](http://125.ps-lessons.ru) for Artificial Intelligence reacted with a tool to spot "neural phony news". [175] Other researchers, 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 hush all other speech and be difficult to filter". [176] In November 2019, OpenAI released the total [variation](https://nujob.ch) of the GPT-2 language model. [177] Several sites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue without supervision language designs to be general-purpose learners, shown by GPT-2 attaining modern accuracy and [perplexity](https://powerstack.co.in) on 7 of 8 zero-shot jobs (i.e. the model was not additional trained on any task-specific input-output examples).
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The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by utilizing 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 model](http://povoq.moe1145) and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete version of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were also trained). [186] +
OpenAI mentioned that GPT-3 was successful at certain "meta-learning" tasks and could generalize the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer [learning](http://gitlab.xma1.de) in between English and Romanian, and between English and German. [184] +
GPT-3 dramatically enhanced benchmark [outcomes](http://119.3.29.1773000) over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or coming across the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 required 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 instantly launched to the general public for issues of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month free personal beta that started 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 furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://www.hydrionlab.com) powering the [code autocompletion](http://8.137.12.293000) tool GitHub [Copilot](https://test.manishrijal.com.np). [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the model can develop working code in over a [dozen programs](http://47.120.16.1378889) languages, a lot of successfully in Python. [192] +
Several concerns with glitches, design defects and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has been accused of discharging copyrighted code, with no author [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:JohnetteTonkin7) 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 revealed the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar exam with a score around the [leading](http://jenkins.stormindgames.com) 10% of [test takers](https://gitea.umrbotech.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, analyze or generate as much as 25,000 words of text, and compose code in all major programming languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained some of the problems with earlier [revisions](https://www.egomiliinteriors.com.ng). [201] GPT-4 is also [efficient](http://git.idiosys.co.uk) in taking images as input on ChatGPT. [202] OpenAI has actually declined to expose 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://101.132.182.1013000) and released GPT-4o, which can process and produce 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 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, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:KelleG0472) OpenAI launched GPT-4o mini, a smaller 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 expects it to be especially useful for enterprises, start-ups and [designers](https://community.cathome.pet) looking for to automate services with [AI](https://www.ataristan.com) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have actually been developed to take more time to believe about their actions, causing greater accuracy. These designs are particularly reliable in science, coding, and thinking jobs, 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 design](http://43.136.17.1423000). OpenAI likewise unveiled o3-mini, a lighter and faster variation of OpenAI o3. As of December 21, 2024, this model is not available for public usage. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the opportunity to obtain early access to these models. [214] The design is called o3 instead of o2 to prevent confusion with telecommunications services company O2. [215] +
Deep research
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Deep research is a representative established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out comprehensive web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] +
Image category
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CLIP
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[Revealed](http://git.kdan.cc8865) in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the semantic similarity in between text and images. It can notably be used 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 creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can develop pictures of sensible things ("a stained-glass window with a picture of a blue strawberry") along with items that do not exist in [reality](https://www.paradigmrecruitment.ca) ("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 of the model with more sensible results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new fundamental 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 model better able to [generate images](http://bryggeriklubben.se) from complex descriptions without manual prompt engineering and render intricate details like hands and text. [221] It was released 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 model that can create videos based on short detailed triggers [223] as well as extend existing videos forwards or backwards in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.
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Sora's development team called it after the Japanese word for "sky", to symbolize its "unlimited innovative potential". [223] Sora's innovation is an adjustment of the technology behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system using [publicly-available](https://gitlab.mnhn.lu) videos as well as copyrighted videos accredited for that purpose, however did not reveal the number or the exact sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it might generate videos up to one minute long. It also shared a technical report highlighting the approaches utilized to train the model, and the design's abilities. [225] It acknowledged a few of its imperfections, consisting of battles simulating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", however noted that they need to have been cherry-picked and may not represent Sora's typical output. [225] +
Despite uncertainty from some [academic leaders](https://talentup.asia) following Sora's public demo, significant entertainment-industry figures have revealed significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's capability to generate [realistic video](http://internetjo.iwinv.net) from text descriptions, citing its potential to change storytelling and content development. He said that his enjoyment about Sora's possibilities was so strong that he had decided to stop briefly prepare for broadening his Atlanta-based movie 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 likewise a multi-task model that can carry out multilingual speech recognition along with 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](http://47.76.141.283000) net trained to predict subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 designs. According to The Verge, a song produced by [MuseNet](https://gitea.dgov.io) tends to start fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, initial applications of this tool were used as early as 2020 for the web psychological thriller Ben Drowned to create music for the [titular character](https://chumcity.xyz). [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 of lyrics and [outputs tune](https://asixmusik.com) samples. OpenAI mentioned the tunes "reveal local musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes lack "familiar bigger musical structures such as choruses that duplicate" and that "there is a considerable gap" in between Jukebox and human-generated music. The [Verge mentioned](http://jibedotcompany.com) "It's technically excellent, even if the results seem like mushy versions of songs that may feel familiar", while Business Insider stated "remarkably, some of the resulting tunes are catchy 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 discuss toy problems in front of a human judge. The function is to research study whether such a method may help in auditing [AI](https://jobs.but.co.id) choices and in establishing explainable [AI](https://projobfind.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of [visualizations](https://suomalaistajalkapalloa.com) of every significant layer and neuron of 8 neural network designs which are frequently studied in interpretability. [240] Microscope was produced to evaluate the features that form inside these neural networks easily. The models included are AlexNet, VGG-19, various variations of Inception, and different variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that offers a conversational user interface that permits users to ask questions in natural language. The system then reacts with a response within seconds.
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