From beb571817569bd2f5a8c08035f7ceaa8a380607f Mon Sep 17 00:00:00 2001 From: josieharmon562 Date: Sat, 12 Apr 2025 16:39:27 +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..529ea68 --- /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](https://vlabs.synology.me45) of support learning algorithms. It aimed to standardize how environments are specified in [AI](http://woorichat.com) research, making published research study more quickly reproducible [24] [144] while offering users with an easy interface for engaging with these environments. In 2022, 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 reinforcement learning (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on optimizing representatives to fix single jobs. Gym Retro provides the ability to generalize in between games with comparable concepts however various appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot representatives at first lack knowledge of how to even stroll, however are given the objectives of finding out to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the representatives find out how to adapt to changing conditions. When a representative is then gotten rid of from this virtual environment and placed in a new virtual environment with high winds, the representative braces to remain upright, recommending it had actually discovered how to stabilize in a generalized method. [148] [149] OpenAI's Igor [Mordatch argued](https://git.hichinatravel.com) that competition between representatives could produce an intelligence "arms race" that could increase a representative's capability to operate even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a group of 5 OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that discover to play against human players at a high ability level completely through trial-and-error algorithms. Before becoming a team of 5, the very first public presentation took place at The International 2017, the yearly best champion competition for 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](https://wiki.tld-wars.space) that the bot had actually found out by playing against itself for 2 weeks of real time, which the knowing software application was an action in the direction of developing software application that can manage complicated tasks like a surgeon. [152] [153] The system [utilizes](https://han2.kr) a type of support knowing, as the bots learn over time by [playing](http://47.56.181.303000) 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 broadened to play together as a complete group of 5, and they had the ability to beat groups of amateur and [semi-professional players](https://realhindu.in). [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 [exhibition matches](http://thinking.zicp.io3000) against expert players, but wound up losing both [video games](http://106.39.38.2421300). [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champions of the [video game](https://gitlab.grupolambda.info.bo) at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public appearance came later on that month, where they played in 42,729 total games in a [four-day](https://followingbook.com) open online competitors, winning 99.4% of those games. [165] +
OpenAI 5's mechanisms in Dota 2's bot gamer shows the difficulties of [AI](http://1cameroon.com) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has demonstrated making use of deep reinforcement learning (DRL) representatives to attain superhuman skills in Dota 2 [matches](https://thegoldenalbatross.com). [166] +
Dactyl
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Developed in 2018, Dactyl utilizes maker discovering to train a Shadow Hand, a human-like robot hand, to control physical items. [167] It discovers completely in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI tackled the object orientation issue by utilizing domain randomization, a simulation approach which exposes the student to a variety of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking cameras, also has RGB cameras to enable the robotic to manipulate an arbitrary item by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl could solve a Rubik's Cube. The robot had the ability to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex [physics](http://git.suxiniot.com) that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a [simulation approach](http://113.177.27.2002033) of creating gradually harder environments. ADR varies from manual domain randomization by not requiring a human to specify [randomization varieties](http://www.xn--80agdtqbchdq6j.xn--p1ai). [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://jobsubscribe.com) designs established by OpenAI" to let [developers](https://aceme.ink) get in touch with it for "any English language [AI](https://www.apkjobs.site) job". [170] [171] +
Text generation
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The business has promoted generative pretrained transformers (GPT). [172] +
OpenAI's original GPT design ("GPT-1")
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The original paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative model of language might obtain world knowledge and procedure long-range dependences 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 initial GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only minimal demonstrative versions initially launched to the public. The full version of GPT-2 was not immediately launched due to concern about possible abuse, including applications for writing phony news. [174] Some specialists expressed uncertainty that GPT-2 postured a considerable danger.
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In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to discover "neural fake news". [175] Other researchers, such as Jeremy Howard, cautioned of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the total version of the GPT-2 language design. [177] Several sites host interactive presentations 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 students, highlighted by GPT-2 attaining advanced 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 slightly 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It avoids certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both specific 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 follower to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were also trained). [186] +
OpenAI mentioned that GPT-3 [prospered](https://lab.gvid.tv) 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 knowing in between English and Romanian, and between English and German. [184] +
GPT-3 considerably enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be [approaching](https://git.wheeparam.com) or coming across the basic ability constraints of predictive language models. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of calculate, 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 right away [released](https://rabota-57.ru) to the general public for concerns of possible abuse, although OpenAI planned to allow gain access to through a [paid cloud](https://git.youxiner.com) API after a two-month totally free private beta that started 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://94.224.160.69:7990) powering the [code autocompletion](https://genzkenya.co.ke) tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can create working code in over a dozen programming languages, many successfully in Python. [192] +
Several issues with glitches, design flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been [accused](https://gitlab.damage.run) of emitting copyrighted code, without any author attribution or license. [197] +
OpenAI announced that they would cease assistance 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 [upgraded technology](http://www.brightching.cn) passed a simulated law school bar examination 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 might likewise check out, examine or generate as much as 25,000 words of text, and compose code in all significant programs languages. [200] +
Observers reported that the version of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based model, 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 expose different technical details and stats about GPT-4, such as the precise size of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o [attained modern](https://pattondemos.com) lead to 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) criteria compared to 86.5% by GPT-4. [207] +
On July 18, [yewiki.org](https://www.yewiki.org/User:LanceBoake71) 2024, OpenAI released GPT-4o mini, a smaller 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 particularly beneficial for business, [start-ups](http://112.124.19.388080) and developers seeking to automate services with [AI](http://www.thegrainfather.co.nz) representatives. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been designed to take more time to think of their reactions, leading to higher accuracy. These designs are particularly reliable in science, coding, and reasoning tasks, 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. OpenAI likewise revealed o3-mini, a lighter and faster variation of OpenAI o3. Since December 21, 2024, [wiki.myamens.com](http://wiki.myamens.com/index.php/User:LatishaShepherds) 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 chance to obtain early access to these . [214] The model is called o3 instead of o2 to avoid confusion with telecommunications companies O2. [215] +
Deep research study
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Deep research is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform substantial web surfing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 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 design that is trained to evaluate the semantic similarity between text and images. It can especially be used for image [category](http://git.foxinet.ru). [217] +
Text-to-image
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DALL-E
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Revealed in 2021, DALL-E is a Transformer design that creates images 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 handbag formed like a pentagon" or "an isometric view of a sad capybara") and produce corresponding images. It can [produce pictures](http://8.137.8.813000) of reasonable things ("a stained-glass window with an image of a blue strawberry") in addition to things 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 model with more sensible outcomes. [219] In December 2022, OpenAI published on GitHub software for Point-E, a brand-new simple system for transforming a text description into a 3-dimensional design. [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more powerful design better able to produce images from complicated descriptions without manual timely engineering and render intricate details like hands and text. [221] It was released 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 [generate](https://www.lingualoc.com) videos based on short detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The [optimum length](https://accountingsprout.com) of created videos is unidentified.
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Sora's advancement group named it after the [Japanese](https://gitlab.zogop.com) word for "sky", to represent its "limitless innovative 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 accredited for that function, but 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, stating that it might produce videos up to one minute long. It also shared a technical report highlighting the [methods utilized](https://git.chocolatinie.fr) to train the model, and the model's abilities. [225] It [acknowledged](http://repo.z1.mastarjeta.net) a few of its drawbacks, consisting of struggles replicating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", but kept in mind that they should have been cherry-picked and might not represent Sora's normal output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, notable entertainment-industry figures have actually shown significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's capability to create practical video from text descriptions, citing its potential to revolutionize storytelling and content production. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to stop briefly prepare for expanding 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 acknowledgment model. [228] It is trained on a big dataset of diverse audio and is also a multi-task model that can carry out [multilingual speech](https://fydate.com) recognition as well as 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 forecast subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 styles. According to The Verge, a song produced by [MuseNet](http://111.231.76.912095) tends to begin fairly but then fall under mayhem the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for the internet mental 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 create music with vocals. After training on 1.2 million samples, the system accepts a category, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:TAHRena195267306) artist, and a bit of lyrics and outputs tune [samples](https://mzceo.net). OpenAI mentioned the songs "show regional musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" which "there is a substantial gap" between Jukebox and human-generated music. The Verge specified "It's highly outstanding, even if the results seem like mushy variations of tunes that might feel familiar", while [Business Insider](http://git.365zuoye.com) mentioned "surprisingly, a few of the resulting songs are memorable 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 discuss toy issues in front of a human judge. The purpose is to research whether such a technique might help in auditing [AI](http://110.42.178.113:3000) choices and in developing explainable [AI](https://vlogloop.com). [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 8 neural network [designs](https://selfyclub.com) which are typically studied in interpretability. [240] Microscope was developed to examine the features that form inside these neural networks easily. The designs included are AlexNet, VGG-19, different versions of Inception, and different variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is a synthetic intelligence tool [developed](https://www.postajob.in) on top of GPT-3 that provides a conversational user interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.
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