From 3890ca502e7270bd5f499265003efac38e61f6bf Mon Sep 17 00:00:00 2001 From: georgianaflore Date: Sat, 15 Feb 2025 18:15:50 +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..db88521 --- /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](https://git.gilgoldman.com) to help with the development of reinforcement learning algorithms. It aimed to standardize how environments are specified in [AI](https://gitlab.ccc.org.co) research study, making released research study more easily reproducible [24] [144] while supplying users with a basic interface for connecting with these environments. In 2022, new developments of Gym have been moved to the library Gymnasium. [145] [146] +
Gym Retro
+
Released in 2018, Gym Retro is a platform for [pediascape.science](https://pediascape.science/wiki/User:StevieSimos301) support knowing (RL) research study on video games [147] using RL algorithms and research study generalization. Prior [larsaluarna.se](http://www.larsaluarna.se/index.php/User:Arturo0965) RL research study focused mainly on enhancing representatives to solve single jobs. Gym Retro provides the capability to generalize between games with similar ideas however various looks.
+
RoboSumo
+
Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially do not have knowledge of how to even stroll, but are given the goals of [discovering](http://121.40.234.1308899) to move and to push the [opposing representative](https://cielexpertise.ma) out of the ring. [148] Through this adversarial knowing process, the representatives discover how to adjust to altering conditions. When an agent is then eliminated from this virtual environment and placed in a brand-new virtual environment with high winds, the representative braces to remain upright, recommending it had actually discovered how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives could produce an intelligence "arms race" that could increase a representative's ability to work even outside the context of the competitors. [148] +
OpenAI 5
+
OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that discover to play against human players at a high ability level entirely through experimental algorithms. Before becoming a group of 5, the first public presentation occurred at The International 2017, the annual premiere championship competition for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for two weeks of genuine time, which the knowing software application was a step in the instructions of creating software that can handle complicated tasks like a cosmetic surgeon. [152] [153] The system utilizes a type of reinforcement knowing, 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 killing an opponent and taking map goals. [154] [155] [156] +
By June 2018, the capability of the [bots expanded](http://gitlab.qu-in.com) to play together as a complete group of 5, and they had the ability to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The [International](http://101.36.160.14021044) 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 beat OG, the reigning world champs of the video game at the time, 2:0 in a live exhibit match in [San Francisco](https://beta.hoofpick.tv). [163] [164] The bots' final public look came later on that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games. [165] +
OpenAI 5's mechanisms in Dota 2's bot [gamer reveals](http://kanghexin.work3000) the challenges of [AI](https://careerconnect.mmu.edu.my) systems in multiplayer online battle arena (MOBA) [video games](https://eurosynapses.giannistriantafyllou.gr) and how OpenAI Five has actually demonstrated using deep reinforcement learning (DRL) representatives to [attain superhuman](https://forum.elaivizh.eu) skills in Dota 2 matches. [166] +
Dactyl
+
Developed in 2018, Dactyl utilizes device discovering to train a Shadow Hand, a human-like robotic hand, to control physical objects. [167] It discovers entirely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation issue by utilizing domain randomization, a simulation method which exposes the learner to a range of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having movement tracking cameras, likewise has RGB cameras to permit the robot to manipulate an [arbitrary](https://empregos.acheigrandevix.com.br) things by seeing it. In 2018, OpenAI showed that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robotic had the ability 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 improving the toughness of Dactyl to perturbations by utilizing Automatic [Domain Randomization](https://git.nullstate.net) (ADR), a simulation method of producing progressively more challenging environments. ADR differs from manual [domain randomization](https://clubamericafansclub.com) by not needing a human to specify randomization varieties. [169] +
API
+
In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://basedwa.re) models developed by OpenAI" to let [designers](https://git.xhkjedu.com) get in touch with it for "any English language [AI](https://gitlab.ui.ac.id) task". [170] [171] +
Text generation
+
The company has promoted generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("GPT-1")
+
The original paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his coworkers, and released in [preprint](https://www.virfans.com) on [OpenAI's site](https://arbeitswerk-premium.de) on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world understanding and procedure long-range dependences by pre-training on a [varied corpus](http://www.pygrower.cn58081) with long stretches of adjoining text.
+
GPT-2
+
Generative [Pre-trained Transformer](http://travelandfood.ru) 2 ("GPT-2") is an unsupervised transformer language model and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative variations initially launched to the public. The full variation of GPT-2 was not right away released due to concern about potential misuse, including applications for writing phony news. [174] Some experts revealed uncertainty that GPT-2 posed a substantial danger.
+
In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to find "neural fake news". [175] Other researchers, such as Jeremy Howard, alerted of "the technology to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the total variation of the GPT-2 language design. [177] Several websites host interactive demonstrations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue unsupervised language models to be general-purpose learners, shown by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not further trained on any task-specific input-output examples).
+
The corpus it was trained on, called WebText, contains somewhat 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This allows [representing](http://repo.fusi24.com3000) any string of characters by encoding both specific characters and multiple-character tokens. [181] +
GPT-3
+
First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 contained 175 billion criteria, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were also trained). [186] +
that GPT-3 prospered at certain "meta-learning" tasks and could generalize the function of a single input-output pair. The GPT-3 release paper offered examples of translation and [pipewiki.org](https://pipewiki.org/wiki/index.php/User:EsperanzaHopson) cross-linguistic transfer knowing between English and Romanian, and in between English and German. [184] +
GPT-3 drastically improved benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or experiencing the fundamental capability constraints of predictive language [designs](https://gitlab.wah.ph). [187] Pre-training GPT-3 required numerous 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 immediately released to the public for concerns of possible abuse, although OpenAI prepared to enable gain access to through a paid cloud API after a two-month free personal beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified solely to Microsoft. [190] [191] +
Codex
+
Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been [trained](https://pipewiki.org) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://quierochance.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [personal](http://5.34.202.1993000) beta. [194] According to OpenAI, the design can create working code in over a lots programming languages, a lot of effectively in Python. [192] +
Several problems with problems, design flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been accused of producing copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would discontinue assistance for Codex API on March 23, 2023. [198] +
GPT-4
+
On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the upgraded innovation passed a simulated law school bar exam 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 could likewise check out, examine or [generate](https://vlabs.synology.me45) up to 25,000 words of text, and write code in all major programs 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 caution that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has declined to expose various technical details and data about GPT-4, such as the precise size of the design. [203] +
GPT-4o
+
On May 13, 2024, OpenAI revealed and released GPT-4o, which can process and create 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) criteria compared to 86.5% by GPT-4. [207] +
On July 18, [wiki.asexuality.org](https://wiki.asexuality.org/w/index.php?title=User_talk:GonzaloVue84412) 2024, OpenAI launched 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](https://redefineworksllc.com) to $5 and $15 respectively for GPT-4o. OpenAI expects it to be particularly useful for business, startups and designers seeking to automate services with [AI](http://www.xn--he5bi2aboq18a.com) agents. [208] +
o1
+
On September 12, 2024, OpenAI launched the o1[-preview](https://careers.tu-varna.bg) and o1-mini models, which have been developed to take more time to believe about their actions, causing higher precision. These designs are especially efficient in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1[-preview](https://swahilihome.tv) was changed by o1. [211] +
o3
+
On December 20, 2024, OpenAI unveiled o3, the follower of the o1 reasoning design. OpenAI also revealed o3-mini, a lighter and quicker variation of OpenAI o3. Since 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](https://abalone-emploi.ch) and security scientists had the chance to obtain early access to these designs. [214] The model is called o3 rather than o2 to avoid confusion with telecommunications companies O2. [215] +
Deep research study
+
Deep research is an agent developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform extensive web 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 an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] +
Image category
+
CLIP
+
Revealed in 2021, CLIP ([Contrastive Language-Image](https://swaggspot.com) Pre-training) is a design that is trained to evaluate the semantic resemblance between text and images. It can significantly be utilized for image classification. [217] +
Text-to-image
+
DALL-E
+
Revealed in 2021, DALL-E is a Transformer design that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and create matching images. It can develop pictures of realistic objects ("a stained-glass window with a picture of a blue strawberry") as well as 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.
+
DALL-E 2
+
In April 2022, OpenAI revealed DALL-E 2, an updated version of the design with more sensible outcomes. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a new simple system for converting a text description into a 3-dimensional design. [220] +
DALL-E 3
+
In September 2023, OpenAI revealed DALL-E 3, a more powerful model better able to create images from complex descriptions without manual timely engineering and render complicated [details](https://gitea.alaindee.net) like hands and text. [221] It was launched to the general public as a ChatGPT Plus [function](https://git-web.phomecoming.com) in October. [222] +
Text-to-video
+
Sora
+
Sora is a text-to-video design that can generate videos based on short detailed triggers [223] as well as extend existing videos forwards or backwards in time. [224] It can generate videos with resolution up to 1920x1080 or 1080x1920. The maximal length of generated videos is unidentified.
+
Sora's development team named it after the Japanese word for "sky", [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:LindaIsenberg91) to symbolize its "endless innovative capacity". [223] Sora's innovation is an adaptation of the technology behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos accredited for that function, but did not reveal the number or the precise sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, mentioning that it could create videos as much as one minute long. It also shared a technical report highlighting the [methods utilized](https://thesecurityexchange.com) to train the design, and the model's capabilities. [225] It acknowledged some of its drawbacks, consisting of struggles replicating complex 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 may not represent Sora's normal output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, noteworthy entertainment-industry figures have actually shown considerable interest in the innovation's potential. In an interview, actor/[filmmaker Tyler](https://ezworkers.com) Perry expressed his astonishment at the innovation's capability to generate reasonable video from text descriptions, citing its possible to reinvent storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had decided to pause prepare for expanding his Atlanta-based movie studio. [227] +
Speech-to-text
+
Whisper
+
Released in 2022, Whisper is a general-purpose speech acknowledgment design. [228] It is trained on a big dataset of diverse audio and is also a multi-task model that can perform multilingual speech acknowledgment along with speech translation and language identification. [229] +
Music generation
+
MuseNet
+
Released in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in MIDI music files. It can create songs with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to start fairly but then fall under turmoil the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were used as early as 2020 for the internet mental thriller Ben Drowned to develop music for the titular character. [232] [233] +
Jukebox
+
Released in 2020, Jukebox is an open-sourced algorithm to produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI stated the tunes "reveal local musical coherence [and] follow conventional chord patterns" however acknowledged that the songs lack "familiar larger musical structures such as choruses that repeat" which "there is a substantial space" in between Jukebox and human-generated music. The Verge specified "It's technologically excellent, even if the results seem like mushy versions of songs that might feel familiar", while Business Insider specified "surprisingly, a few of the resulting tunes are catchy and sound legitimate". [234] [235] [236] +
User interfaces
+
Debate Game
+
In 2018, OpenAI launched the Debate Game, which teaches machines to discuss toy problems in front of a human judge. The function is to research study whether such a technique may assist in auditing [AI](http://8.141.155.183:3000) decisions and in establishing explainable [AI](https://namesdev.com). [237] [238] +
Microscope
+
Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of 8 neural network models which are often studied in interpretability. [240] Microscope was produced to examine the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, different versions of Inception, and various [versions](http://106.52.215.1523000) of CLIP Resnet. [241] +
ChatGPT
+
Launched in November 2022, ChatGPT is an expert system tool built 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 an answer within seconds.
\ No newline at end of file