From 0885cdbed8412e1c5fc1203e60d469b95a8a3afb Mon Sep 17 00:00:00 2001 From: Aiden Parkin Date: Tue, 8 Apr 2025 09:54:32 +0900 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..b754bc1 --- /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 help with the development of support knowing algorithms. It aimed to standardize how environments are defined in [AI](https://myjobapply.com) research study, making published research more easily reproducible [24] [144] while providing users with a simple interface for [pediascape.science](https://pediascape.science/wiki/User:BarrettMacNeil5) communicating with these environments. In 2022, new developments of Gym have actually been relocated to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support learning (RL) research on computer game [147] using [RL algorithms](http://120.78.74.943000) and research study generalization. Prior RL research focused mainly on enhancing representatives to resolve single tasks. Gym Retro gives the ability to generalize between [video games](http://cgi3.bekkoame.ne.jp) with similar ideas but various appearances.
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RoboSumo
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Released in 2017, RoboSumo is a [virtual](https://git.juxiong.net) world where humanoid metalearning robotic agents initially lack knowledge of how to even walk, however are offered the objectives of discovering to move and to push the [opposing representative](https://asw.alma.cl) out of the ring. [148] Through this adversarial learning procedure, the representatives find out how to adapt to altering conditions. When an agent is then eliminated from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, recommending it had learned how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could [produce](http://111.47.11.703000) an intelligence "arms race" that might increase an agent's capability to function even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that find out to play against human players at a high ability level completely through trial-and-error algorithms. Before becoming a group of 5, the first public presentation occurred at The International 2017, the annual best championship tournament for the game, where Dendi, a professional [Ukrainian](http://www.yasunli.co.id) player, lost against a bot in a live individually matchup. [150] [151] After the match, [wavedream.wiki](https://wavedream.wiki/index.php/User:Willie7094) CTO Greg Brockman explained that the bot had actually learned by playing against itself for two weeks of actual time, and that the knowing software was a step in the instructions of developing software application that can deal with complicated tasks like a cosmetic surgeon. [152] [153] The system [utilizes](https://gitea.qianking.xyz3443) a kind of reinforcement learning, as the bots find out gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an opponent and taking map objectives. [154] [155] [156] +
By June 2018, the ability of the bots expanded to play together as a full group of 5, and [wiki-tb-service.com](http://wiki-tb-service.com/index.php?title=Benutzer:TobiasChristison) they were able to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against expert gamers, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champions of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public look came later on that month, where they played in 42,729 total video 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 shows the difficulties of [AI](https://picturegram.app) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually shown using deep reinforcement knowing (DRL) representatives to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses machine learning to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It discovers entirely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the things [orientation](https://thefreedommovement.ca) issue by using domain randomization, a simulation technique which exposes the learner to a range of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having movement tracking electronic cameras, also has RGB video cameras to permit the robot to [manipulate](http://wiki.iurium.cz) an approximate object by seeing it. In 2018, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:TrishaIcely6405) OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl might resolve a Rubik's Cube. The robot had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex 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 technique](https://rhcstaffing.com) of generating gradually harder 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, [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1099517) OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](https://gitea.masenam.com) models established by OpenAI" to let developers contact it for "any English language [AI](https://git.riomhaire.com) task". [170] [171] +
Text generation
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The business has promoted generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("GPT-1")
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The [initial](https://gl.vlabs.knu.ua) paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his coworkers, and published in preprint on OpenAI's site on June 11, 2018. [173] It showed how a generative model of language could obtain world knowledge and procedure long-range reliances 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 a without supervision transformer language design and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative versions initially launched to the public. The full version of GPT-2 was not instantly launched due to issue about prospective abuse, consisting of applications for writing fake news. [174] Some experts expressed uncertainty that GPT-2 presented a substantial threat.
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In [response](http://git.edazone.cn) to GPT-2, the Allen [Institute](https://dronio24.com) for Artificial Intelligence responded with a tool to spot "neural phony news". [175] Other researchers, such as Jeremy Howard, warned of "the technology to absolutely 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 variation of the GPT-2 language design. [177] Several websites host interactive presentations of different instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue without supervision language designs to be general-purpose students, illustrated by GPT-2 attaining state-of-the-art precision and perplexity 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](https://git.aionnect.com) 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](https://playtube.app) in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 contained 175 billion parameters, [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 criteria were also trained). [186] +
OpenAI mentioned 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](https://www.weben.online) provided examples of translation and [cross-linguistic transfer](http://www.lebelleclinic.com) knowing in between English and Romanian, and in between English and German. [184] +
GPT-3 significantly enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or encountering the fundamental ability constraints of predictive language models. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately [released](https://xajhuang.com3100) to the general public for concerns of possible abuse, although OpenAI prepared to permit gain access to through a [paid cloud](https://body-positivity.org) API after a two-month totally free personal beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed specifically 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://my-sugar.co.il) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [private](https://gitr.pro) beta. [194] According to OpenAI, the design can develop working code in over a dozen programs languages, many effectively in Python. [192] +
Several problems with glitches, style flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been accused of discharging copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would discontinue 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), capable of [accepting text](http://www.stes.tyc.edu.tw) or image inputs. [199] They revealed that the [updated innovation](https://git.gocasts.ir) passed a simulated law school bar test 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 read, evaluate or create up to 25,000 words of text, and [compose code](http://119.3.29.1773000) in all major shows languages. [200] +
Observers reported that the iteration of ChatGPT using 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. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has declined to reveal various technical details and data about GPT-4, such as the precise size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained modern outcomes in voice, multilingual, and vision criteria, setting new records in audio speech recognition and 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 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 it to be especially beneficial for business, start-ups and developers looking for to automate services with [AI](https://git.hxps.ru) representatives. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have been designed to take more time to think of their reactions, causing greater precision. These models are especially reliable in science, coding, and [thinking](https://iinnsource.com) jobs, and were made available to ChatGPT Plus and Team members. [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 reasoning model. OpenAI also unveiled o3-mini, a lighter and faster variation of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are testing 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 design is called o3 instead of o2 to avoid confusion with telecommunications companies O2. [215] +
Deep research
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Deep research study is an [agent developed](http://120.196.85.1743000) by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to perform comprehensive web browsing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and [Python tools](https://trustemployement.com) enabled, it [reached](https://vishwakarmacommunity.org) an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [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 analyze 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](http://120.196.85.1743000) in 2021, DALL-E is a Transformer model that produces images from textual descriptions. [218] [DALL-E utilizes](https://superappsocial.com) a 12-billion-parameter variation of GPT-3 to interpret natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of an unfortunate capybara") and generate corresponding images. It can [produce images](https://viddertube.com) of sensible objects ("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 revealed DALL-E 2, an upgraded version of the model with more reasonable outcomes. [219] In December 2022, OpenAI published on GitHub software for Point-E, a brand-new primary system for converting a text description into a 3-dimensional design. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, a more powerful design better able to [generate](https://tobesmart.co.kr) images from intricate descriptions without manual timely engineering and render intricate details like hands and text. [221] It was launched 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 brief detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The optimum length of created videos is unidentified.
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Sora's advancement group named 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 as well as copyrighted videos accredited for that function, but did not expose the number or the specific sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, [raovatonline.org](https://raovatonline.org/author/giagannon42/) specifying that it might create videos up to one minute long. It also shared a technical report highlighting the approaches utilized to train the model, and the model's capabilities. [225] It acknowledged a few of its imperfections, [consisting](https://service.aicloud.fit50443) of struggles imitating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", but noted 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, notable entertainment-industry figures have actually shown substantial interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's capability to generate reasonable video from text descriptions, citing its potential to revolutionize storytelling and material development. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to pause plans for expanding his Atlanta-based motion picture 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 varied audio and is likewise a multi-task model that can carry out multilingual speech recognition in addition to 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 produce tunes with 10 instruments in 15 designs. According to The Verge, a song generated by MuseNet tends to start fairly however then fall into chaos the longer it plays. [230] [231] In pop culture, [initial applications](https://rassi.tv) of this tool were used as early as 2020 for the internet mental thriller Ben Drowned to for the titular character. [232] [233] +
Jukebox
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Released in 2020, Jukebox is an open-sourced algorithm to [generate music](http://43.138.236.39000) with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs song [samples](http://skyfffire.com3000). OpenAI specified the tunes "reveal regional musical coherence [and] follow standard chord patterns" however acknowledged that the songs lack "familiar bigger musical structures such as choruses that repeat" which "there is a substantial gap" between Jukebox and [human-generated music](http://home.rogersun.cn3000). The Verge mentioned "It's highly outstanding, even if the results sound like mushy versions of tunes that might feel familiar", while Business Insider stated "surprisingly, a few of the resulting songs are appealing and sound genuine". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, OpenAI launched the Debate Game, which teaches machines to discuss toy issues in front of a human judge. The function is to research study whether such an approach may help in [auditing](http://gitlab.ileadgame.net) [AI](https://git.joystreamstats.live) choices and in establishing explainable [AI](https://sfren.social). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of 8 neural network designs which are typically studied in interpretability. [240] Microscope was developed to analyze the functions that form inside these neural networks easily. The models included are AlexNet, VGG-19, different variations of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is a synthetic intelligence tool constructed on top of GPT-3 that provides a conversational interface that allows users to ask questions in natural language. The system then responds with an answer within seconds.
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