From d869690f14fca7750804ff40d3b7aa3cc6d596b3 Mon Sep 17 00:00:00 2001 From: mikelscoggins Date: Sat, 15 Feb 2025 19:44:47 +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..fdc697a --- /dev/null +++ b/The-Verge-Stated-It%27s-Technologically-Impressive.md @@ -0,0 +1,76 @@ +
Announced in 2016, Gym is an [open-source Python](https://git.mitsea.com) library designed to facilitate the advancement of support learning algorithms. It aimed to standardize how environments are specified in [AI](https://axeplex.com) research, making [released](http://www.jacksonhampton.com3000) research more quickly reproducible [24] [144] while offering users with an easy interface for engaging with these environments. In 2022, new developments of Gym have actually been transferred to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support learning (RL) research study on video games [147] utilizing RL algorithms and study generalization. Prior RL research study focused mainly on enhancing agents to solve [single tasks](http://154.9.255.1983000). Gym Retro provides the ability to generalize in between games with similar principles however 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 do not have knowledge of how to even walk, but are provided the goals of finding out to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the agents learn how to adjust to changing conditions. When a representative is then removed from this virtual environment and placed in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had discovered how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents might create an intelligence "arms race" that could increase an agent's capability to function even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that learn to play against human gamers at a high ability level totally through [trial-and-error algorithms](https://vidhiveapp.com). Before ending up being a group of 5, the first public demonstration happened at The International 2017, the annual best champion tournament for the video game, where Dendi, a professional Ukrainian player, lost against a bot in a live one-on-one matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by [playing](https://careerjunction.org.in) against itself for 2 weeks of actual time, and that the learning software was a step in the instructions of creating software that can manage intricate jobs like a cosmetic surgeon. [152] [153] The system utilizes a form of [reinforcement](https://git.mitsea.com) learning, as the bots discover in 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 broadened to play together as a complete group of 5, and they had the [ability](http://168.100.224.793000) to beat groups of amateur and [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1085161) semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against professional players, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public look came later on that month, where they played in 42,729 total video games in a four-day open online competitors, winning 99.4% of those games. [165] +
OpenAI 5's systems in Dota 2's bot player shows the obstacles of [AI](https://git.smartenergi.org) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has shown the usage of deep reinforcement knowing (DRL) agents to attain superhuman proficiency 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 items. [167] It finds out entirely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI dealt with the item orientation problem by utilizing domain randomization, a simulation method which exposes the student to a range of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking electronic cameras, also has RGB cameras to allow the robot to control an approximate item by seeing it. In 2018, OpenAI revealed that the system was able to [control](http://221.239.90.673000) a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by improving the toughness of Dactyl to perturbations by [utilizing Automatic](https://89.22.113.100) Domain Randomization (ADR), a simulation approach of [producing gradually](https://code.webpro.ltd) more tough environments. ADR differs from manual domain randomization by not needing a human to [define randomization](https://git.bloade.com) ranges. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](http://115.238.48.210:9015) models established by OpenAI" to let developers contact it for "any English language [AI](https://git.trov.ar) task". [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 model was composed by Alec Radford and his associates, and [published](https://usvs.ms) in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a [generative design](http://git.risi.fun) of language could obtain world knowledge and process 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 a without supervision transformer language model and the successor to OpenAI's initial GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just restricted demonstrative variations at first launched to the public. The full variation of GPT-2 was not instantly launched due to concern about prospective misuse, including applications for writing phony news. [174] Some professionals revealed uncertainty that GPT-2 posed a substantial hazard.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to find "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned of "the technology to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out 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 sites host interactive presentations of different instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue unsupervised language designs to be learners, shown by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not additional 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](https://www.kenpoguy.com) with at least 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This allows [representing](http://82.156.24.19310098) 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 model and the follower to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as couple of as 125 million [parameters](http://175.27.189.803000) were likewise trained). [186] +
OpenAI specified that GPT-3 succeeded at certain "meta-learning" tasks and might 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 significantly improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or coming across 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 full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly [released](https://git.cloud.krotovic.com) to the public for issues of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a [two-month free](https://soundfy.ebamix.com.br) private 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](http://zhandj.top:3000) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the model can create working code in over a dozen programming languages, [demo.qkseo.in](http://demo.qkseo.in/profile.php?id=995449) many effectively in Python. [192] +
Several problems with problems, style defects and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has actually been accused of emitting copyrighted code, without any author attribution or license. [197] +
OpenAI announced that they would stop 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 innovation passed a simulated law school bar test 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 also read, analyze or create up to 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 version, with the caution that GPT-4 retained some of the issues with earlier modifications. [201] GPT-4 is likewise [capable](http://47.108.182.667777) of taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal numerous technical details and data 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 released GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained advanced lead to voice, multilingual, and vision standards, setting new records in audio speech acknowledgment and [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:FidelBatt531106) translation. [205] [206] It scored 88.7% on the [Massive Multitask](https://allcallpro.com) Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized 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 [raovatonline.org](https://raovatonline.org/author/giagannon42/) $15 respectively for GPT-4o. OpenAI expects it to be particularly useful for enterprises, startups and developers seeking to automate services with [AI](https://sunriji.com) [representatives](http://42.192.14.1353000). [208] +
o1
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On September 12, 2024, OpenAI launched the o1[-preview](https://lokilocker.com) and o1-mini designs, which have been designed to take more time to believe about their responses, leading to greater accuracy. These designs are particularly efficient in science, coding, and reasoning tasks, and [wavedream.wiki](https://wavedream.wiki/index.php/User:AdriannaBranch) were made available to ChatGPT Plus and Staff member. [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 quicker variation of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are testing 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 design is called o3 instead of o2 to avoid confusion with telecoms companies O2. [215] +
Deep research
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Deep research study is an agent developed by OpenAI, revealed on February 2, 2025. It [leverages](http://tktko.com3000) the abilities of OpenAI's o3 model to carry out substantial web browsing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools enabled, it reached a precision 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 examine the semantic similarity between text and images. It can especially 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 produces 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 handbag formed like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can produce pictures of reasonable items ("a stained-glass window with a picture of a blue strawberry") along with 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 revealed DALL-E 2, an upgraded version of the design with more reasonable outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new primary system for converting 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 effective model much better able to create images from complicated descriptions without manual prompt engineering and render intricate details like hands and text. [221] It was launched to the general public as a ChatGPT Plus [feature](https://app.theremoteinternship.com) 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 videos based upon short detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of produced videos is unidentified.
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Sora's advancement group named it after the [Japanese](http://git.z-lucky.com90) word for "sky", to represent its "limitless innovative capacity". [223] Sora's innovation is an adjustment of the innovation behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos certified for that function, but did not expose the number or the precise sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:ChiquitaVeilleux) 2024, [mentioning](http://1.92.66.293000) that it could generate videos approximately one minute long. It likewise shared a technical report highlighting the techniques used to train the model, and the model's abilities. [225] It acknowledged a few of its drawbacks, including battles [mimicing](https://elmerbits.com) complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "excellent", [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11862161) however 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](https://www.workinternational-df.com) demo, noteworthy entertainment-industry figures have shown substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to produce realistic video from text descriptions, mentioning its prospective to revolutionize storytelling and material development. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to pause 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 recognition model. [228] It is trained on a large dataset of varied audio and is likewise a multi-task design that can carry out multilingual speech recognition as well as 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](https://hafrikplay.com) to forecast subsequent musical notes in MIDI music files. It can create tunes with 10 instruments in 15 styles. According to The Verge, a tune produced by MuseNet tends to [start fairly](https://seedvertexnetwork.co.ke) however then fall into turmoil 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 produce music for the [titular](https://just-entry.com) 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 genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI mentioned the songs "reveal local musical coherence [and] follow standard chord patterns" but acknowledged that the songs do not have "familiar bigger musical structures such as choruses that duplicate" and that "there is a substantial gap" in between Jukebox and human-generated music. The Verge specified "It's technically outstanding, even if the outcomes seem like mushy variations of songs that may feel familiar", while Business Insider specified "surprisingly, a few of the resulting tunes are appealing and sound legitimate". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI released the Debate Game, which teaches devices to dispute toy problems in front of a human judge. The purpose is to research whether such a method might help in auditing [AI](http://e-kou.jp) decisions and in establishing explainable [AI](http://stackhub.co.kr). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of 8 neural network designs which are typically studied in interpretability. [240] Microscope was created to evaluate the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, various versions of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is a synthetic intelligence tool constructed on top of GPT-3 that supplies a conversational interface that permits users to ask questions in natural language. The system then reacts with an answer within seconds.
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