From 895ef0d38f3bdecf70defc3f6d61047536202210 Mon Sep 17 00:00:00 2001 From: marshahurley15 Date: Sun, 6 Apr 2025 07:40:18 +0300 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..f1fd605 --- /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](http://hmind.kr) to help with the development of reinforcement learning algorithms. It aimed to standardize how environments are specified in [AI](http://dev.nextreal.cn) research, [larsaluarna.se](http://www.larsaluarna.se/index.php/User:Josef06S8821379) making released research study more easily reproducible [24] [144] while supplying users with a basic interface for engaging with these environments. In 2022, [brand-new developments](https://agapeplus.sg) 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 reinforcement learning (RL) research on video games [147] using RL [algorithms](https://sapjobsindia.com) and study generalization. Prior RL research focused mainly on enhancing representatives to resolve single jobs. [Gym Retro](https://uwzzp.nl) provides the ability to generalize between games with similar concepts but different looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents initially do not have understanding of how to even stroll, however are [offered](https://strimsocial.net) the objectives of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial learning process, the agents discover how to adjust to changing conditions. When a representative 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 actually learned how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might produce an intelligence "arms race" that could increase an agent's capability to operate even outside the context of the [competition](https://gitea.taimedimg.com). [148] +
OpenAI 5
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OpenAI Five is a team of 5 OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that learn to play against human gamers at a high skill level completely through experimental algorithms. Before becoming a team of 5, the first public presentation took place at The International 2017, the annual premiere championship tournament for the game, where Dendi, a professional Ukrainian 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 two weeks of actual time, and that the knowing software application was an action in the direction of creating software that can manage complex jobs like a surgeon. [152] [153] The system utilizes a kind of support knowing, as the bots find out over time by playing against themselves hundreds of times a day for months, and are rewarded for [actions](https://git.palagov.tv) such as eliminating an [opponent](http://adbux.shop) and taking map goals. [154] [155] [156] +
By June 2018, the capability of the [bots expanded](http://forum.ffmc59.fr) 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 professional gamers, but ended 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 exhibit match in [San Francisco](https://sistemagent.com8081). [163] [164] The bots' final public look 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 mechanisms in Dota 2's bot gamer reveals the challenges of [AI](https://www.menacopt.com) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually demonstrated making use of knowing (DRL) agents to attain superhuman competence 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 control physical things. [167] It learns completely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation issue by using domain randomization, a simulation technique which exposes the learner to a range of experiences rather than attempting to fit to truth. The set-up for [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11860868) Dactyl, aside from having motion tracking cameras, likewise has RGB electronic cameras to allow the robot to manipulate an approximate object by seeing it. In 2018, OpenAI showed that the system was able to [manipulate](http://connect.lankung.com) a cube and an [octagonal prism](http://git2.guwu121.com). [168] +
In 2019, OpenAI showed that Dactyl could fix a Rubik's Cube. The robotic had the ability to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to design. OpenAI did this by enhancing the robustness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation technique of creating progressively more tough environments. ADR varies from manual domain randomization by not requiring a human to specify randomization ranges. [169] +
API
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In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://planetdump.com) models established by OpenAI" to let developers call on it for "any English language [AI](https://git.selfmade.ninja) task". [170] [171] +
Text generation
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The business has popularized generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("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 in preprint on OpenAI's site on June 11, 2018. [173] It [demonstrated](https://www.jobmarket.ae) how a generative design of language could obtain world knowledge and procedure long-range reliances 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 an unsupervised [transformer language](http://mao2000.com3000) model and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative variations initially launched to the public. The complete variation of GPT-2 was not right away released due to issue about potential abuse, consisting of applications for writing phony news. [174] Some specialists revealed uncertainty that GPT-2 presented a considerable risk.
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In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural phony news". [175] Other scientists, such as Jeremy Howard, [alerted](https://lifestagescs.com) of "the technology to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the complete version 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 unsupervised language models to be general-purpose students, shown by GPT-2 attaining advanced 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 slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids 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](http://www.zjzhcn.com) 3 (GPT-3) is a not being watched transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete version of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as few as 125 million specifications were also trained). [186] +
OpenAI specified that GPT-3 was successful at certain "meta-learning" jobs and might generalize the function of a [single input-output](http://worldwidefoodsupplyinc.com) pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer knowing between English and Romanian, and between English and German. [184] +
GPT-3 drastically improved benchmark outcomes over GPT-2. OpenAI cautioned that such [scaling-up](http://59.56.92.3413000) of language models might be approaching or experiencing the basic ability constraints of [predictive language](https://www.ukdemolitionjobs.co.uk) designs. [187] Pre-training GPT-3 required a number of 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 model was not right away released to the public for concerns of possible abuse, although OpenAI prepared 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 in addition been [trained](http://www.forwardmotiontx.com) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://teba.timbaktuu.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the model can develop working code in over a lots programming languages, the majority of [efficiently](http://git.idiosys.co.uk) in Python. [192] +
Several concerns with problems, design defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been implicated of [releasing copyrighted](http://135.181.29.1743001) code, with no author [attribution](https://happylife1004.co.kr) or license. [197] +
OpenAI revealed that they would terminate 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), efficient in accepting text or image inputs. [199] They revealed that the updated technology passed a simulated law school bar exam 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 read, analyze or produce up to 25,000 words of text, and compose code in all significant shows languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an [enhancement](https://gitea.oio.cat) on the previous GPT-3.5-based model, with the caveat that GPT-4 retained some of the problems with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has decreased to reveal numerous technical details and stats about GPT-4, such as the [precise size](https://www.buzzgate.net) of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI announced and released GPT-4o, which can process and [produce](https://medicalrecruitersusa.com) text, images and audio. [204] GPT-4o attained state-of-the-art outcomes in voice, multilingual, and vision criteria, setting 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 released GPT-4o mini, a smaller variation 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 $15 respectively for GPT-4o. OpenAI expects it to be especially helpful for enterprises, start-ups and [developers](https://cozwo.com) looking for to [automate services](http://120.55.164.2343000) with [AI](https://git.wisptales.org) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been designed to take more time to think of their responses, causing greater accuracy. These designs are especially reliable in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was [changed](http://141.98.197.226000) by o1. [211] +
o3
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On December 20, 2024, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) OpenAI unveiled o3, the successor of the o1 reasoning model. OpenAI likewise revealed o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this design 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 chance to obtain early access to these designs. [214] The design is called o3 rather than o2 to prevent confusion with telecoms services provider O2. [215] +
Deep research
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Deep research study is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform substantial web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools made it possible for, 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 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 model that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of an unfortunate capybara") and produce corresponding images. It can create [pictures](http://revoltsoft.ru3000) of [practical items](http://42.194.159.649981) ("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 outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11860868) a brand-new basic system for converting a text description into a 3[-dimensional](https://jobstoapply.com) model. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, a more powerful design much better able to produce images from complex descriptions without manual prompt engineering and render complicated details like hands and text. [221] It was released 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 on brief detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of produced videos is unknown.
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Sora's advancement team called it after the Japanese word for "sky", to signify its "endless creative 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 along with copyrighted videos certified for that function, however did not reveal 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 could generate videos approximately one minute long. It also shared a technical report highlighting the approaches used to train the design, and the design's abilities. [225] It acknowledged a few of its drawbacks, consisting of battles mimicing complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", however kept in mind that they should have been cherry-picked and may not represent Sora's typical output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, noteworthy entertainment-industry figures have actually shown significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to generate reasonable video from text descriptions, citing its possible to change storytelling and content development. He said that his excitement about Sora's possibilities was so strong that he had chosen to stop briefly plans for broadening his Atlanta-based motion picture 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 large dataset of varied audio and is likewise a multi-task design 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](https://gantnews.com) notes in MIDI music files. It can create tunes with 10 instruments in 15 designs. According to The Verge, a song generated by MuseNet tends to begin fairly however then fall under mayhem the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized as early as 2020 for the internet psychological [thriller](https://www.jangsuori.com) 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 [generate music](http://195.58.37.180) with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs song samples. OpenAI stated the tunes "show local 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 gap" in between Jukebox and human-generated music. The Verge mentioned "It's highly impressive, even if the results seem like mushy variations of songs that may feel familiar", while Business Insider mentioned "surprisingly, a few of the resulting songs are appealing and sound genuine". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, [OpenAI launched](https://www.meetgr.com) the Debate Game, which teaches devices to debate toy issues in front of a human judge. The purpose is to research study whether such an approach may assist in auditing [AI](http://117.50.100.234:10080) choices and in developing explainable [AI](https://freakish.life). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and neuron of eight neural network models which are frequently studied in [interpretability](https://sistemagent.com8081). [240] Microscope was produced to analyze the features that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various variations of Inception, and various variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is a synthetic intelligence tool built on top of GPT-3 that provides a [conversational interface](https://www.cbmedics.com) that allows users to ask questions in natural language. The system then reacts with an answer within seconds.
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