From 946e81708719b8fa5cdd571423ca78fb36872e4e Mon Sep 17 00:00:00 2001 From: Angeline Murtagh Date: Sat, 15 Feb 2025 17:12:28 +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..fb8e7c2 --- /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 of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](http://appleacademy.kr) research, making released research study more easily reproducible [24] [144] while providing users with a simple user interface for interacting with these environments. In 2022, 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 [support knowing](https://followgrown.com) (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on optimizing agents to fix single tasks. Gym Retro gives the ability to [generalize](https://git.andreaswittke.de) between video games with similar concepts but different appearances.
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RoboSumo
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[Released](https://powerstack.co.in) in 2017, RoboSumo is a virtual world where humanoid metalearning robot representatives initially do not have understanding of how to even walk, however are provided the goals of learning to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the agents find out how to adjust to changing conditions. When an agent is then gotten rid of from this virtual environment and positioned in a brand-new virtual environment with high winds, the representative braces to remain upright, recommending it had discovered how to stabilize in a generalized way. [148] [149] [OpenAI's Igor](https://iuridictum.pecina.cz) Mordatch argued that competitors in between representatives might develop an intelligence "arms race" that could increase a representative's ability 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](http://www.jimtangyh.xyz7002) used in the competitive five-on-five computer game Dota 2, that learn to play against human gamers at a high skill level completely through trial-and-error algorithms. Before ending up being a team of 5, the very first public presentation occurred at The International 2017, the yearly premiere champion tournament for the game, where Dendi, a professional Ukrainian gamer, 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 discovered by playing against itself for 2 weeks of genuine time, which the learning software was a step in the instructions of creating software application that can deal with complicated jobs like a surgeon. [152] [153] The system uses a form of reinforcement learning, as the bots discover 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 capability of the bots expanded to play together as a complete group of 5, and [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:ElmaAfford18621) they were able to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, [yewiki.org](https://www.yewiki.org/User:Nichol9618) OpenAI Five played in two exhibit matches against expert gamers, however wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five [defeated](http://47.103.108.263000) OG, the ruling world champions of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public look came later that month, where they played in 42,729 overall video games in a four-day open online competition, winning 99.4% of those video games. [165] +
OpenAI 5's mechanisms in Dota 2's bot player reveals the [challenges](http://106.52.215.1523000) of [AI](https://src.dziura.cloud) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated the usage of deep reinforcement learning (DRL) representatives to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes machine learning to train a Shadow Hand, a human-like robot hand, to control physical things. [167] It discovers completely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI tackled the object orientation issue by using domain randomization, a simulation method which exposes the student to a range of experiences instead of attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking video cameras, likewise has [RGB cameras](http://hmind.kr) to enable the robotic to manipulate an arbitrary item by seeing it. In 2018, OpenAI revealed that the system had the ability 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 fix the puzzle 60% of the time. Objects like the [Rubik's Cube](http://123.111.146.2359070) introduce complicated 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 technique of creating progressively harder environments. ADR differs from manual domain randomization by not requiring 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 brand-new [AI](https://82.65.204.63) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](http://huaang6688.gnway.cc:3000) job". [170] [171] +
Text generation
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The has popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT model ("GPT-1")
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The initial paper on generative pre-training of a [transformer-based language](http://47.105.104.2043000) model was composed by Alec Radford and his colleagues, and released in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative design of language might 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 model and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just limited demonstrative variations initially released to the public. The complete version of GPT-2 was not right away launched due to issue about [prospective](http://wdz.imix7.com13131) abuse, consisting of [applications](https://visorus.com.mx) for writing phony news. [174] Some specialists revealed uncertainty that GPT-2 postured a substantial danger.
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In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "neural fake news". [175] Other scientists, 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 muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the complete version of the GPT-2 language model. [177] Several sites host interactive demonstrations of various 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, 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 more 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 a minimum of 3 upvotes. It avoids certain problems 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 without supervision transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion specifications, [184] two orders of magnitude bigger 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 stated that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the function of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning between English and Romanian, and in between English and German. [184] +
GPT-3 considerably improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or [experiencing](http://www.kotlinx.com3000) the essential capability constraints of predictive language designs. [187] Pre-training GPT-3 required 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 [instantly released](https://www.loupanvideos.com) to the general public for concerns of possible abuse, although [OpenAI prepared](https://flexychat.com) to permit gain access to through a paid cloud API after a two-month totally free personal beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed exclusively 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](http://git.ningdatech.com) on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://58.87.67.124:20080) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was [released](https://younetwork.app) in personal beta. [194] According to OpenAI, the design can create working code in over a lots programming languages, many successfully in Python. [192] +
Several problems with glitches, design defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been accused of releasing copyrighted code, with no author attribution or license. [197] +
OpenAI announced 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), efficient in accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar exam with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, evaluate or produce approximately 25,000 words of text, and write code in all significant programming languages. [200] +
Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to reveal numerous 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](http://gitlab.flyingmonkey.cn8929) and create text, images and audio. [204] GPT-4o attained cutting edge results in voice, multilingual, and vision criteria, setting brand-new records in audio speech recognition 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 released GPT-4o mini, a smaller version 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 expects it to be especially helpful for enterprises, start-ups and designers seeking to automate services with [AI](https://www.roednetwork.com) representatives. [208] +
o1
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On September 12, 2024, [OpenAI released](http://121.5.25.2463000) the o1-preview and o1-mini designs, which have been developed to take more time to believe about their actions, causing higher precision. These designs are especially effective in science, coding, and reasoning tasks, 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 revealed o3, the successor of the o1 reasoning design. OpenAI also revealed o3-mini, a lighter and faster version of OpenAI o3. As of December 21, 2024, this model 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 scientists had the chance to obtain early access to these designs. [214] The model is called o3 rather than o2 to prevent confusion with telecommunications companies 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 o3 model to [perform comprehensive](https://medatube.ru) web browsing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools allowed, it reached a [precision](https://socialpix.club) of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] +
Image classification
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CLIP
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[Revealed](http://118.190.88.238888) in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to examine the semantic similarity in 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 design that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images. It can develop images of realistic items ("a stained-glass window with a picture of a blue strawberry") in addition to objects that do not exist in [reality](https://git-web.phomecoming.com) ("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 version of the model with more sensible results. [219] In December 2022, OpenAI released 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 better able to generate images from complicated descriptions without manual timely engineering and [it-viking.ch](http://it-viking.ch/index.php/User:LillieYup4258164) render complex details like hands and text. [221] It was launched 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 produce videos based on short detailed triggers [223] along with [extend existing](https://gitea.sitelease.ca3000) videos forwards or in reverse in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of produced videos is unidentified.
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Sora's advancement team called it after the Japanese word for "sky", to signify its "limitless innovative capacity". [223] Sora's technology is an adjustment of the innovation 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, but did not reveal the number or the specific sources of the videos. [223] +
OpenAI showed some [Sora-created high-definition](http://bingbinghome.top3001) videos to the public on February 15, 2024, specifying that it might create videos approximately one minute long. It likewise shared a technical report highlighting the approaches utilized to train the design, and the design's abilities. [225] It acknowledged a few of its shortcomings, including battles mimicing intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the [presentation](https://mypetdoll.co.kr) videos "outstanding", however kept in mind that they should have been cherry-picked and may not represent Sora's normal output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, notable entertainment-industry figures have shown considerable interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's ability to create practical video from text descriptions, mentioning its potential to change storytelling and content development. He said that his enjoyment about Sora's possibilities was so strong that he had chosen to pause 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 model. [228] It is trained on a large dataset of diverse audio and is also a multi-task design that can carry out multilingual speech acknowledgment 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 net trained to forecast subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 designs. According to The Verge, a tune created by MuseNet tends to start fairly but then fall into mayhem the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for the web mental 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 bit of lyrics and outputs tune samples. OpenAI stated the songs "show local musical coherence [and] follow traditional chord patterns" but acknowledged that the songs lack "familiar larger musical structures such as choruses that repeat" which "there is a significant gap" between Jukebox and human-generated music. The Verge specified "It's technologically impressive, even if the outcomes sound like mushy versions of tunes that may feel familiar", while Business Insider mentioned "remarkably, a few of the resulting tunes are appealing and sound genuine". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI released the Debate Game, which teaches makers to debate toy problems in front of a human judge. The [purpose](http://101.34.211.1723000) is to research study whether such a method might assist in auditing [AI](https://www.lingualoc.com) choices and in establishing explainable [AI](http://t93717yl.bget.ru). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a [collection](https://notitia.tv) of visualizations of every [substantial layer](https://customerscomm.com) and [it-viking.ch](http://it-viking.ch/index.php/User:KarenSteinberger) nerve cell of 8 neural network designs which are typically studied in interpretability. [240] Microscope was developed to evaluate the functions that form inside these neural networks easily. The models included are AlexNet, VGG-19, different 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 allows users to ask concerns in natural language. The system then responds with an answer within seconds.
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