From c5980b918a28b7ed3f06422c7b5d3e2b85f578d3 Mon Sep 17 00:00:00 2001 From: Carlo Dickson Date: Sun, 9 Feb 2025 04:15:07 +0800 Subject: [PATCH] Update '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..239f781 --- /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 assist in the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://wiki.rolandradio.net) research study, making published research more easily reproducible [24] [144] while offering users with a basic user interface for interacting with these environments. In 2022, of Gym have been moved to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, [gratisafhalen.be](https://gratisafhalen.be/author/danarawson/) Gym Retro is a platform for support learning (RL) research on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on enhancing representatives to resolve single tasks. Gym Retro gives the ability to generalize in between video games with comparable principles however various appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first do not have understanding of how to even stroll, however are provided the objectives of discovering to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing procedure, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:MariaKuehner) the agents discover how to adjust to altering conditions. When a representative is then removed from this virtual environment and positioned in a brand-new virtual environment with high winds, the representative 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 between agents could develop an intelligence "arms race" that might increase a representative's ability to [operate](http://wiki.pokemonspeedruns.com) even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that discover to play against human players at a high skill level totally through experimental algorithms. Before becoming a team of 5, the first public presentation happened at The International 2017, the annual premiere champion tournament for the game, where Dendi, an expert Ukrainian player, lost against a bot in a live individually matchup. [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, [surgiteams.com](https://surgiteams.com/index.php/User:KelleeKinsey) and that the knowing software application was an action in the direction of developing software that can manage complicated jobs like a surgeon. [152] [153] The system utilizes a form of support knowing, as the bots learn with time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an opponent and taking map objectives. [154] [155] [156] +
By June 2018, the capability of the bots broadened to play together as a full group of 5, and they were able to defeat teams 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 champions of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public appearance came later that month, where they played in 42,729 total video games in a four-day open online competitors, winning 99.4% of those video games. [165] +
OpenAI 5's systems in Dota 2's bot gamer reveals the challenges of [AI](https://napolifansclub.com) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has shown making use of deep reinforcement knowing (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes [maker finding](http://120.46.139.31) out to train a Shadow Hand, a human-like robot hand, to control physical items. [167] It discovers totally in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation issue by using domain randomization, a simulation approach which exposes the student 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](https://granthers.com) to allow the robot to manipulate an arbitrary things by seeing it. In 2018, OpenAI showed that the system had the ability to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl could resolve a Rubik's Cube. The robot had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present intricate 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 approach of producing progressively more challenging environments. ADR varies from manual domain randomization by not requiring a human to specify 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.smfsimple.com) designs developed by OpenAI" to let developers call on it for "any English language [AI](https://altaqm.nl) task". [170] [171] +
Text generation
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The company has promoted generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT model ("GPT-1")
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The original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his coworkers, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:SoonWinfrey7778) and published in preprint on OpenAI's site on June 11, 2018. [173] It showed how a generative model of language could obtain world understanding and procedure long-range reliances by pre-training on a varied corpus with long stretches of [contiguous text](http://internetjo.iwinv.net).
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GPT-2
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[Generative Pre-trained](https://gitea.blubeacon.com) Transformer 2 ("GPT-2") is an unsupervised transformer language design and the follower to [OpenAI's initial](https://gitlab.optitable.com) GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative variations initially launched to the public. The complete variation of GPT-2 was not right away launched due to concern about prospective abuse, consisting of applications for composing phony news. [174] Some specialists revealed uncertainty that GPT-2 presented a significant threat.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural phony news". [175] Other researchers, 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 hush all other speech and be impossible to filter". [176] In November 2019, OpenAI released the total version of the GPT-2 language design. [177] Several [sites host](https://sjee.online) 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 general-purpose learners, highlighted by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot tasks (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 slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain concerns encoding [vocabulary](https://namoshkar.com) with word tokens by using byte pair encoding. This allows 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 an unsupervised transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion specifications, [184] two orders of magnitude larger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 designs with as few as 125 million parameters were likewise trained). [186] +
OpenAI mentioned that GPT-3 was successful at certain "meta-learning" jobs and might generalize the function of a [single input-output](https://jimsusefultools.com) pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer knowing between English and Romanian, and between [English](https://cagit.cacode.net) and German. [184] +
GPT-3 significantly enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs could be approaching or encountering the essential capability constraints of predictive language models. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately launched to the general public for issues of possible abuse, although OpenAI prepared to permit gain access to through a paid cloud API after a two-month totally free personal beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was [certified](https://www.linkedaut.it) exclusively to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a [descendant](http://1.13.246.1913000) of GPT-3 that has in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://47.106.228.113:3000) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the design can produce working code in over a dozen programming languages, many successfully in Python. [192] +
Several issues with problems, style flaws and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has actually been implicated of [releasing copyrighted](https://www.linkedaut.it) code, with no author attribution or license. [197] +
OpenAI announced that they would stop assistance 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 announced that the upgraded innovation passed a simulated law school bar exam 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 could also check out, [evaluate](https://git.sitenevis.com) or produce as much as 25,000 words of text, and compose code in all significant programming languages. [200] +
Observers reported that the model of ChatGPT using 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 of taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal numerous [technical details](https://projobfind.com) 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 create text, images and audio. [204] GPT-4o attained cutting edge results in voice, multilingual, and vision criteria, setting new records in audio speech [acknowledgment](https://git.nosharpdistinction.com) and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) [standard compared](http://47.108.69.3310888) to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI launched GPT-4o mini, a smaller sized 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 anticipates it to be especially beneficial for business, startups and designers looking for to automate services with [AI](https://collegejobportal.in) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been [developed](https://projobfind.com) to take more time to think about their responses, causing greater precision. These designs are especially effective in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was replaced by o1. [211] +
o3
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On December 20, 2024, [OpenAI revealed](http://106.55.61.1283000) o3, the follower of the o1 thinking design. OpenAI likewise unveiled o3-mini, a lighter and faster 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 and [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:Laverne38A) security researchers had the opportunity to obtain early access to these models. [214] The design is called o3 instead of o2 to avoid confusion with telecommunications providers O2. [215] +
Deep research study
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Deep research is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform comprehensive web surfing, information analysis, and synthesis, providing detailed [reports](https://dash.bss.nz) 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) criteria. [120] +
Image category
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CLIP
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Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the semantic similarity between text and images. It can especially be utilized 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 model that develops images from textual descriptions. [218] DALL-E utilizes a 12[-billion-parameter variation](https://meta.mactan.com.br) of GPT-3 to interpret natural language inputs (such as "a green leather purse formed like a pentagon" or "an isometric view of a sad capybara") and create [matching images](https://tocgitlab.laiye.com). It can [develop images](http://101.43.129.2610880) of [reasonable](http://207.180.250.1143000) things ("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"). Since March 2021, no API or code is available.
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DALL-E 2
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In April 2022, OpenAI announced DALL-E 2, an updated variation of the model with more sensible results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new rudimentary system for converting a text description into a 3-dimensional design. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, a more effective model better able to produce images from complicated descriptions without manual prompt engineering and render complex details like hands and text. [221] It was launched to the 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 upon short detailed prompts [223] in addition to extend existing videos forwards or backwards in time. [224] It can generate videos with [resolution](https://www.myad.live) approximately 1920x1080 or 1080x1920. The maximal length of created videos is unidentified.
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Sora's development group named it after the Japanese word for "sky", to represent its "limitless innovative capacity". [223] Sora's innovation is an [adjustment](https://gitea.adminakademia.pl) of the technology behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos certified for that function, but did not expose the number or the exact sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the public on February 15, 2024, stating that it might produce videos as much as one minute long. It also shared a technical report highlighting the approaches utilized to train the model, and the design's abilities. [225] It acknowledged some of its shortcomings, consisting of battles simulating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", but noted that they need to have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, notable entertainment-industry figures have actually shown significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to produce sensible video from text descriptions, mentioning its possible to change storytelling and material creation. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to stop briefly prepare for expanding his Atlanta-based motion [picture](https://git.paaschburg.info) studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, Whisper is a [general-purpose speech](https://i-medconsults.com) [recognition design](http://fggn.kr). [228] It is trained on a large dataset of diverse audio and is likewise a multi-task design that can perform multilingual speech acknowledgment in addition to 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](https://git.cooqie.ch) net trained to predict subsequent musical notes in MIDI music files. It can create songs with 10 instruments in 15 designs. According to The Verge, a tune created by MuseNet tends to begin fairly however then fall under chaos the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for the web psychological [thriller](https://sjee.online) 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 specified the songs "reveal regional musical coherence [and] follow conventional chord patterns" but acknowledged that the songs lack "familiar larger musical structures such as choruses that repeat" and that "there is a substantial space" in between Jukebox and human-generated music. The Verge mentioned "It's technically remarkable, even if the outcomes seem like mushy variations of tunes that may feel familiar", while Business Insider stated "remarkably, some of the resulting tunes are appealing and sound genuine". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI introduced the Debate Game, which teaches makers to debate toy problems in front of a human judge. The function is to research whether such a method might help in auditing [AI](https://radi8tv.com) choices and in establishing explainable [AI](https://www.freeadzforum.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of [visualizations](https://hireblitz.com) of every significant layer and neuron of eight neural network models which are typically studied in interpretability. [240] Microscope was created to analyze the features that form inside these neural networks easily. The designs consisted of are AlexNet, VGG-19, various variations of Inception, and different variations 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 user interface that permits users to ask concerns in natural language. The system then reacts with an answer within seconds.
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