From 0fa1d7887d881d36d5a0d1c94adf1229c4100873 Mon Sep 17 00:00:00 2001 From: Benjamin Franks Date: Fri, 7 Feb 2025 22:15:29 +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..e6f237a --- /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 designed to help with the [development](https://thunder-consulting.net) of support knowing algorithms. It aimed to standardize how environments are specified in [AI](https://gogs.greta.wywiwyg.net) research, making published research more quickly reproducible [24] [144] while providing users with a simple user interface for connecting with these environments. In 2022, new advancements of Gym have been moved to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support knowing (RL) research study on video games [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on optimizing representatives to fix single jobs. Gym Retro offers the capability to generalize 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 robotic representatives at first do not have understanding of how to even walk, however are given the objectives of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the agents discover how to adapt to altering conditions. When an agent is then gotten rid of from this virtual environment and put in a new virtual environment with high winds, the agent braces to remain upright, recommending it had actually found out how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives might create an intelligence "arms race" that could increase a representative's ability to work even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a group of 5 OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that discover to play against human players at a high skill level completely through [trial-and-error algorithms](https://thedatingpage.com). Before becoming a team of 5, the first public demonstration took place at The International 2017, the yearly best championship tournament for the game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for two weeks of actual time, and that the knowing software was a step in the direction of developing software that can manage intricate jobs like a surgeon. [152] [153] The system uses a type of support knowing, as the [bots learn](https://gantnews.com) in time by playing against themselves numerous 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 capability of the [bots expanded](https://gitea.belanjaparts.com) to play together as a full group of 5, and they had the ability to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert gamers, however wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs 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 total games in a four-day open online competition, winning 99.4% of those games. [165] +
OpenAI 5's systems in Dota 2's bot gamer shows the difficulties of [AI](https://goalsshow.com) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has shown using deep support learning (DRL) agents to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes machine finding out to train a Shadow Hand, a human-like robot hand, to control physical objects. [167] It finds out totally in simulation using the same RL algorithms and [training code](https://www.eruptz.com) as OpenAI Five. OpenAI dealt with the object orientation problem by utilizing domain randomization, a simulation approach which exposes the student to a range of [experiences](https://it-storm.ru3000) rather than trying to fit to truth. The set-up for Dactyl, aside from having motion tracking cams, also has RGB video cameras to permit the robotic to manipulate an arbitrary object 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 had the [ability](https://dev.nebulun.com) to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce [complicated physics](https://git.flyfish.dev) 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 generating progressively harder environments. ADR differs from manual domain randomization by not needing a human to define randomization varieties. [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://www.worlddiary.co) models established by OpenAI" to let designers get in touch with it for "any English language [AI](http://120.79.94.122:3000) job". [170] [171] +
Text generation
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The [business](https://nujob.ch) has popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT model ("GPT-1")
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The initial paper on [generative pre-training](http://git.szchuanxia.cn) of a transformer-based language design was written by Alec Radford and his colleagues, and published in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative design of language could obtain world understanding and process long-range reliances by pre-training on a varied corpus with long stretches of contiguous text.
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GPT-2
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[Generative](https://aaalabourhire.com) Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language design and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:Alexandria39G) with just limited demonstrative variations at first released to the general public. The complete version of GPT-2 was not right away released due to issue about possible abuse, consisting of applications for composing fake news. [174] Some professionals revealed uncertainty that GPT-2 postured a significant danger.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to find "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned 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 sites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue without supervision language models to be general-purpose students, shown by GPT-2 attaining cutting edge precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further trained on any task-specific input-output examples).
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The corpus it was trained on, called WebText, contains somewhat 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both individual 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 successor to GPT-2. [182] [183] [184] OpenAI stated that the complete version of GPT-3 contained 175 billion criteria, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 [designs](https://socialeconomy4ces-wiki.auth.gr) with as couple of as 125 million specifications were also trained). [186] +
OpenAI stated that GPT-3 was successful at certain "meta-learning" jobs and could generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer knowing in between English and Romanian, and between English and German. [184] +
GPT-3 drastically enhanced [benchmark](https://repo.maum.in) results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or coming across the basic capability constraints of predictive language models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly launched to the public for issues of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month free personal beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified specifically to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, [wiki.rolandradio.net](https://wiki.rolandradio.net/index.php?title=User:RYUDarell4) Codex is a descendant of GPT-3 that has actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://dreamtube.congero.club) [powering](https://git.programming.dev) the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in [personal](http://www.andreagorini.it) beta. [194] According to OpenAI, the design can create working code in over a lots programming languages, a lot of successfully in Python. [192] +
Several problems with problems, design defects and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has been implicated of releasing copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would discontinue 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), [capable](http://101.43.151.1913000) of accepting text or image inputs. [199] They revealed that the updated innovation passed a simulated law school bar test 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 could likewise check out, analyze or create approximately 25,000 words of text, and compose code in all major programming languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based model, with the caution that GPT-4 retained some of the problems with earlier modifications. [201] GPT-4 is also [efficient](https://24cyber.ru) in taking images as input on ChatGPT. [202] OpenAI has declined to reveal numerous technical details and statistics 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 released GPT-4o, which can [process](https://live.gitawonk.com) and [generate](http://git.7doc.com.cn) text, images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision standards, setting brand-new records in audio speech [recognition](https://bdstarter.com) 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 released GPT-4o mini, a smaller sized version of GPT-4o replacing 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 expects it to be particularly useful for enterprises, startups and [garagesale.es](https://www.garagesale.es/author/toshahammon/) designers seeking to automate services with [AI](https://git.fafadiatech.com) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been developed to take more time to consider their reactions, causing greater accuracy. These models are especially efficient in science, coding, and [reasoning](https://sneakerxp.com) jobs, and were made available to ChatGPT Plus and Staff member. [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 successor of the o1 reasoning design. OpenAI also revealed o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, they are [testing](https://wiki.idealirc.org) o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these designs. [214] The design is called o3 instead of o2 to prevent confusion with telecoms providers O2. [215] +
Deep research study
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Deep research study is a [representative established](https://www.ayuujk.com) by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to carry out comprehensive web surfing, data analysis, and synthesis, [providing detailed](https://git.boergmann.it) reports within a timeframe of 5 to thirty minutes. [216] With browsing and [Python tools](http://admin.youngsang-tech.com) made it possible for, 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 ( Pre-training) is a design that is trained to analyze the semantic resemblance in between text and images. It can especially 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 model that produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and create corresponding images. It can develop pictures of sensible items ("a stained-glass window with a picture of a blue strawberry") in addition to things that do not exist in [reality](http://123.60.173.133000) ("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](https://neoshop365.com) version of the model with more realistic results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new basic 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 effective design better able to produce images from intricate descriptions without manual prompt engineering and render intricate details like hands and text. [221] It was released to the general 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 design that can generate videos based on brief detailed prompts [223] in addition to extend existing videos forwards or in [reverse](https://devfarm.it) in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of generated videos is [unidentified](http://git.hiweixiu.com3000).
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Sora's development group named it after the Japanese word for "sky", to symbolize its "unlimited innovative capacity". [223] Sora's innovation is an adaptation of the technology behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos certified for that purpose, but did not expose the number or the exact sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, stating that it might produce videos approximately one minute long. It likewise shared a technical report highlighting the approaches used to train the model, and the model's abilities. [225] It acknowledged a few of its drawbacks, consisting of struggles replicating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", but kept in mind that they must have been cherry-picked and may not represent Sora's normal output. [225] +
Despite uncertainty from some academic leaders following [Sora's public](http://git.hiweixiu.com3000) demonstration, noteworthy entertainment-industry figures have revealed considerable interest in the innovation's [capacity](https://suomalaistajalkapalloa.com). In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's ability to generate realistic video from text descriptions, citing its potential to change storytelling and content development. He said that his excitement about [Sora's possibilities](https://happylife1004.co.kr) was so strong that he had chosen to stop briefly prepare for expanding 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 acknowledgment model. [228] It is trained on a big dataset of varied audio and is also a multi-task design that can carry out multilingual speech recognition in addition to speech translation and [language](http://git.jihengcc.cn) identification. [229] +
Music generation
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MuseNet
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Released in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a tune created by MuseNet tends to start fairly however then fall into mayhem the longer it plays. [230] [231] In popular culture, initial applications of this tool were used as early as 2020 for the internet psychological thriller Ben Drowned to develop music for the titular character. [232] [233] +
Jukebox
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[Released](https://git.xxb.lttc.cn) 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](https://video.igor-kostelac.com). OpenAI mentioned the tunes "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that duplicate" and that "there is a substantial space" in between Jukebox and human-generated music. The Verge stated "It's highly excellent, even if the results seem like mushy variations of songs that might feel familiar", [35.237.164.2](https://35.237.164.2/wiki/User:BessieFitzRoy) while Business Insider mentioned "remarkably, some of the resulting tunes are memorable and sound legitimate". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI launched the Debate Game, which teaches makers to dispute toy issues in front of a human judge. The [purpose](https://loveyou.az) is to research whether such a technique may assist in auditing [AI](https://pittsburghpenguinsclub.com) decisions and in developing explainable [AI](https://one2train.net). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every [considerable layer](https://www.pkjobshub.store) and neuron of eight neural network designs which are often 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, different versions of Inception, and various variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an artificial intelligence tool developed 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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