From b15468d77beb783fb2e9f26cc672c1312202c1dd Mon Sep 17 00:00:00 2001 From: Bernadine Lindsey Date: Fri, 7 Feb 2025 03:03:48 +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..61d19c5 --- /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 created to help with the advancement of support learning algorithms. It aimed to standardize how environments are defined in [AI](http://www.gz-jj.com) research study, making released research more quickly reproducible [24] [144] while providing users with an easy user interface for engaging 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 reinforcement learning (RL) research on video games [147] using RL algorithms and [study generalization](https://truthbook.social). Prior RL research study focused mainly on optimizing representatives to resolve single tasks. Gym Retro provides the ability to generalize in between games with similar concepts but different appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives [initially](https://git.nullstate.net) do not have knowledge of how to even stroll, however are provided the goals of learning to move and to push the [opposing representative](https://www.jobspk.pro) out of the ring. [148] Through this adversarial knowing procedure, the representatives find out how to adapt to altering conditions. When a [representative](http://koreaeducation.co.kr) is then removed from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had discovered how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between agents might develop an intelligence "arms race" that could increase a representative's capability to function 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 learn to play against [human gamers](https://cello.cnu.ac.kr) at a high skill level completely through trial-and-error algorithms. Before becoming a team of 5, the very first public presentation occurred at The International 2017, the [annual premiere](https://195.216.35.156) champion competition for the video game, where Dendi, an [expert Ukrainian](http://git.attnserver.com) player, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had learned by playing against itself for 2 weeks of actual time, and that the learning software was a step in the direction of creating software application that can deal with intricate tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of reinforcement knowing, as the bots learn with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156] +
By June 2018, the ability of the bots broadened to play together as a full team of 5, and they were able to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert players, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public appearance came later that month, where they played in 42,729 overall 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 shows the challenges of [AI](http://111.35.141.5:3000) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has shown using deep reinforcement learning (DRL) representatives to [attain superhuman](https://estekhdam.in) skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses maker finding out to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It finds out totally in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation issue by utilizing domain randomization, a simulation approach which exposes the to a variety of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking cameras, likewise has RGB cams to enable the robot to control an arbitrary things by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might solve a Rubik's Cube. The robotic had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to model. OpenAI did this by improving the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of producing progressively harder environments. ADR differs from manual domain randomization by not requiring a human to [define randomization](https://hireforeignworkers.ca) ranges. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://peoplesmedia.co) models developed by OpenAI" to let developers call on it for "any English language [AI](http://43.136.17.142:3000) task". [170] [171] +
Text generation
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The company has actually popularized generative [pretrained transformers](https://topdubaijobs.ae) (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 colleagues, and published in [preprint](https://ukcarers.co.uk) on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world knowledge and process long-range [dependencies](https://gogs.fytlun.com) 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 a not being watched transformer language design and the successor to [OpenAI's initial](http://sujongsa.net) GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative variations initially released to the public. The complete variation of GPT-2 was not [instantly released](http://123.56.193.1823000) due to concern about possible misuse, including applications for composing fake news. [174] Some professionals revealed uncertainty that GPT-2 postured a considerable risk.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "neural fake news". [175] Other researchers, such as Jeremy Howard, warned of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush 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 demonstrations of various instances of GPT-2 and other [transformer designs](http://www.origtek.com2999). [178] [179] [180] +
GPT-2's authors argue not being watched language models to be general-purpose students, illustrated by GPT-2 attaining state-of-the-art accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not further 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 at least 3 upvotes. It prevents certain issues 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](http://119.167.221.1460000) [a] Transformer 3 (GPT-3) is a without supervision transformer language model and the successor to GPT-2. [182] [183] [184] [OpenAI stated](https://gitea.potatox.net) that the complete variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as few as 125 million specifications were also trained). [186] +
OpenAI stated that GPT-3 was successful at certain "meta-learning" tasks and could generalize the purpose 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 in between English and German. [184] +
GPT-3 drastically improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or coming across the fundamental ability constraints of [predictive language](https://employme.app) models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly launched to the general public for concerns of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month complimentary [personal](https://lpzsurvival.com) beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified exclusively to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.arztstellen.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [personal](https://hub.tkgamestudios.com) beta. [194] According to OpenAI, the model can create working code in over a dozen shows languages, many efficiently in Python. [192] +
Several concerns with glitches, style flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been implicated of emitting copyrighted code, with no [author attribution](https://livesports808.biz) 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 revealed the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They revealed that the upgraded innovation passed a simulated law school bar examination with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, analyze or [generate](https://emplealista.com) as much as 25,000 words of text, and write code in all major programming languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained some of the issues with earlier [modifications](https://woodsrunners.com). [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to reveal different technical details and data about GPT-4, such as the exact 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 create text, images and audio. [204] GPT-4o attained advanced outcomes in voice, multilingual, and vision benchmarks, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the [Massive Multitask](http://115.236.37.10530011) Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI launched GPT-4o mini, [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:Bettina5096) a smaller sized variation of GPT-4o changing GPT-3.5 Turbo on the ChatGPT 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 enterprises, start-ups and developers seeking to automate services with [AI](https://git.palagov.tv) 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 about their responses, leading to higher accuracy. These models are especially effective in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was [changed](http://haiji.qnoddns.org.cn3000) by o1. [211] +
o3
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On December 20, 2024, OpenAI revealed o3, the successor of the o1 thinking design. OpenAI also [unveiled](https://git.intellect-labs.com) o3-mini, a lighter and quicker variation of OpenAI o3. Since December 21, 2024, this model is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the opportunity to obtain early access to these designs. [214] The design is called o3 rather than o2 to avoid confusion with telecoms providers O2. [215] +
Deep research study
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Deep research study is an agent developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out extensive web browsing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) standard. [120] +
Image category
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CLIP
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[Revealed](http://forum.pinoo.com.tr) in 2021, CLIP (Contrastive Language-Image Pre-training) is a design 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 in 2021, DALL-E is a Transformer design that creates 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 handbag formed like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images. It can produce pictures of realistic objects ("a stained-glass window with an image of a blue strawberry") as well as objects 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, an updated version of the design with more sensible outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new simple system for transforming a text description into a 3[-dimensional](http://39.108.93.0) design. [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more powerful model better able to create images from [complicated descriptions](https://watch-wiki.org) without manual timely engineering and render complicated 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 design that can produce videos based upon brief detailed prompts [223] in addition to extend existing videos forwards or in reverse in time. [224] It can [generate videos](https://careers.jabenefits.com) with resolution as much as 1920x1080 or [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:EricGooding) 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](http://140.143.208.1273000) its "unlimited innovative potential". [223] Sora's technology is an adaptation of the technology behind the DALL ยท E 3 text-to-image design. [225] [OpenAI trained](https://source.lug.org.cn) the system using publicly-available videos along with copyrighted videos accredited for that function, but did not reveal the number or the specific sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, stating that it could create videos approximately one minute long. It likewise shared a technical report highlighting the techniques used to train the design, and the design's capabilities. [225] It acknowledged some of its drawbacks, consisting of struggles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "excellent", [larsaluarna.se](http://www.larsaluarna.se/index.php/User:DominiqueCurmi) but noted that they need to have been cherry-picked and may not represent Sora's common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have revealed significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to [generate realistic](https://sahabatcasn.com) video from text descriptions, citing its potential to change storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to pause plans for broadening 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 varied audio and is also a multi-task model that can perform multilingual speech acknowledgment 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 generate tunes with 10 instruments in 15 designs. According to The Verge, a song generated by MuseNet tends to start fairly but then fall under [turmoil](https://git.boergmann.it) the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were utilized as early as 2020 for the web psychological 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 produce music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs song samples. OpenAI mentioned the songs "reveal local musical coherence [and] follow conventional chord patterns" however acknowledged that the tunes lack "familiar larger musical structures such as choruses that repeat" which "there is a substantial gap" between [Jukebox](http://shenjj.xyz3000) and human-generated music. The Verge specified "It's highly outstanding, even if the results seem like mushy versions of songs that may feel familiar", while [Business Insider](http://123.249.20.259080) stated "surprisingly, some of the resulting tunes are catchy 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 whether such a method may assist in auditing [AI](http://60.250.156.230:3000) choices and in establishing explainable [AI](https://git.rell.ru). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and nerve cell of 8 neural network designs which are typically studied in interpretability. [240] Microscope was created to analyze the functions that form inside these neural networks easily. The designs consisted of are AlexNet, VGG-19, various variations of Inception, and various [versions](https://mediawiki1263.00web.net) of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system [tool built](https://watch-wiki.org) on top of GPT-3 that offers a conversational user interface that permits users to ask questions in natural language. The system then responds with a response within seconds.
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