From fc053000b7c1a3b717e7d3b5ba790975fab27d54 Mon Sep 17 00:00:00 2001 From: nevillegill754 Date: Fri, 7 Feb 2025 03:56:22 +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..7fc8942 --- /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 facilitate the advancement of support knowing algorithms. It aimed to standardize how environments are defined in [AI](http://git.zhongjie51.com) research study, making published research study more quickly reproducible [24] [144] while offering users with a simple user interface for communicating with these environments. In 2022, new advancements 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 reinforcement knowing (RL) research on computer game [147] utilizing RL algorithms and study generalization. Prior [mediawiki.hcah.in](https://mediawiki.hcah.in/index.php?title=User:RandellKenney) RL research focused mainly on enhancing representatives to fix single tasks. Gym Retro offers the ability to [generalize](http://114.115.138.988900) between games with comparable principles however different looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents at first do not have knowledge of how to even stroll, but are offered the goals of learning to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the agents find out how to adapt to changing conditions. When an agent is then removed from this virtual environment and put in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had learned how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives could produce an intelligence "arms race" that could increase a representative's ability to work even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a team of 5 [OpenAI-curated bots](http://39.108.87.1793000) used in the competitive five-on-five computer game Dota 2, that discover to play against [human gamers](https://wiki.openwater.health) at a high skill level entirely through trial-and-error algorithms. Before ending up being a team of 5, the first public demonstration occurred at The International 2017, the annual premiere championship competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had found out by playing against itself for two weeks of actual time, which the learning software was an action in the direction of creating software that can manage complex jobs like a surgeon. [152] [153] The system uses a type of reinforcement learning, as the bots discover with time by playing against themselves numerous 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 broadened to play together as a complete team of 5, and they were able to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against [professional](http://dev.zenith.sh.cn) players, 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 exhibition match in San [Francisco](http://www.xyais.cn). [163] [164] The bots' last public look came later on that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those video games. [165] +
OpenAI 5['s systems](https://kewesocial.site) in Dota 2's bot gamer shows the difficulties of [AI](http://docker.clhero.fun:3000) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually demonstrated using deep reinforcement knowing (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses [maker learning](http://113.98.201.1408888) to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It discovers completely in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI tackled the things orientation issue by utilizing domain randomization, a simulation method which exposes the learner to a variety of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having motion tracking video cameras, also has RGB electronic cameras to permit the robotic to control an arbitrary item 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 demonstrated that Dactyl might fix a Rubik's Cube. The robot was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present complex 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 method of producing progressively harder environments. ADR varies from manual domain randomization by not requiring a human to define randomization varieties. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](https://www.designxri.com) designs established by OpenAI" to let [designers](https://pandatube.de) get in touch with it for "any English language [AI](https://git.wyling.cn) job". [170] [171] +
Text generation
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The business 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 model was written by Alec Radford and his associates, and published in preprint on OpenAI's website on June 11, 2018. [173] It [revealed](http://dgzyt.xyz3000) how a generative design of language could obtain world knowledge and [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:FlorianHoutz6) process long-range dependences by pre-training on a diverse 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 a without supervision transformer language model and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative variations [initially released](http://www.stardustpray.top30009) to the public. The full version of GPT-2 was not immediately launched due to issue about potential misuse, consisting of applications for writing fake news. [174] Some experts expressed uncertainty that GPT-2 posed 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 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 released the total variation of the GPT-2 language model. [177] Several sites host interactive demonstrations of different instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue without supervision language models to be general-purpose learners, highlighted by GPT-2 attaining cutting edge precision and perplexity on 7 of 8 [zero-shot tasks](https://1samdigitalvision.com) (i.e. the model was not more 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 prevents certain problems encoding 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 in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being watched transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were likewise trained). [186] +
OpenAI specified that GPT-3 was successful at certain "meta-learning" jobs and could generalize the function of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning in between English and Romanian, and between English and German. [184] +
GPT-3 significantly enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or [encountering](https://jobs.web4y.online) the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of compute, [compared](http://jsuntec.cn3000) to 10s of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not right away released to the general public for issues of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a two-month free private beta that began 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](https://music.michaelmknight.com) powering the code autocompletion tool [GitHub Copilot](https://thunder-consulting.net). [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the design can [develop](http://122.112.209.52) working code in over a lots programming languages, a lot of successfully in Python. [192] +
Several problems with problems, style flaws and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has actually been accused of releasing copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would terminate 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 4 (GPT-4), capable of accepting text or image inputs. [199] They revealed that the updated innovation passed a simulated law school bar examination with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise read, analyze or create approximately 25,000 words of text, and compose code in all significant [programming](https://git.gumoio.com) languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caution 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 actually decreased to reveal various [technical details](http://www.iway.lk) and data about GPT-4, such as the exact 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 produce text, images and audio. [204] GPT-4o attained modern lead to 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, OpenAI launched GPT-4o mini, a smaller variation of GPT-4o changing 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 useful for enterprises, [start-ups](https://talktalky.com) and developers seeking to automate services with [AI](https://asicwiki.org) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have been developed to take more time to think of their actions, [causing](https://trulymet.com) greater precision. These designs are particularly reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was changed by o1. [211] +
o3
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On December 20, 2024, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:DavidShackelford) OpenAI revealed o3, the successor of the o1 [reasoning model](https://gitea.nasilot.me). 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 use. According to OpenAI, they are [testing](http://repo.z1.mastarjeta.net) o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the opportunity to obtain early access to these designs. [214] The model is called o3 rather than o2 to prevent confusion with telecoms providers O2. [215] +
Deep research study
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Deep research is a representative established by OpenAI, revealed on February 2, 2025. It leverages the [abilities](http://39.108.87.1793000) of OpenAI's o3 model to perform extensive web surfing, 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 of 26.6 percent on HLE (Humanity's Last Exam) criteria. [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 analyze the semantic resemblance in between text and images. It can significantly 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 design that develops images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can develop images of [reasonable](https://miderde.de) things ("a stained-glass window with a picture of a blue strawberry") as well as items that do not exist in truth ("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, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2672496) an updated version of the design with more realistic results. [219] In December 2022, [OpenAI released](http://fggn.kr) on GitHub software for Point-E, a brand-new rudimentary system for converting a text description into a 3[-dimensional design](https://westzoneimmigrations.com). [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:FranklinBreillat) a more effective model better able to create images from complex descriptions without manual prompt engineering and render complicated details like hands and [links.gtanet.com.br](https://links.gtanet.com.br/nataliez4160) text. [221] It was launched to the general public as a ChatGPT Plus [function](http://114.34.163.1743333) in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video design that can create videos based upon short detailed triggers [223] as well as extend existing videos forwards or backwards in time. [224] It can produce videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.
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Sora's advancement group named it after the Japanese word for "sky", to [symbolize](https://lms.digi4equality.eu) its "endless innovative capacity". [223] Sora's technology is an adaptation of the technology behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos certified for that purpose, however 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, specifying that it might create videos approximately one minute long. It also shared a technical report highlighting the approaches used to train the design, and the model's capabilities. [225] It [acknowledged](https://video.igor-kostelac.com) a few of its drawbacks, consisting of battles replicating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", however noted that they should have been cherry-picked and [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:Homer93G479471) might not represent Sora's common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have actually revealed considerable interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to produce realistic video from text descriptions, citing its possible to reinvent storytelling and content [production](http://zaxx.co.jp). He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to pause strategies 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 recognition design. [228] It is trained on a big dataset of varied audio and is also a multi-task design that can perform multilingual speech acknowledgment as well as speech translation and language recognition. [229] +
Music generation
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MuseNet
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[Released](https://git.peaksscrm.com) in 2019, MuseNet is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 designs. According to The Verge, a tune generated by MuseNet tends to start fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, [preliminary applications](https://talktalky.com) of this tool were utilized as early as 2020 for the internet psychological 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 generate music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs song samples. OpenAI mentioned the songs "show regional musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" and that "there is a considerable gap" between Jukebox and human-generated music. The Verge stated "It's highly remarkable, even if the results seem like mushy variations of tunes that may feel familiar", while Business Insider stated "surprisingly, some 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 launched the Debate Game, which teaches machines to discuss toy problems in front of a human judge. The purpose is to research study whether such an approach might help in auditing [AI](https://truthbook.social) choices and in establishing explainable [AI](http://120.55.59.89:6023). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and nerve cell of 8 neural network models which are frequently studied in interpretability. [240] Microscope was developed to evaluate the features that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, different variations of Inception, and different versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that offers a conversational [interface](http://hybrid-forum.ru) that allows users to ask concerns in natural language. The system then responds with an answer within seconds.
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