From 3b1609d1d84ad030d8738fc3fc7f15a53a671830 Mon Sep 17 00:00:00 2001 From: Anya O'Dowd Date: Sat, 22 Feb 2025 03:40:04 +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..5b3788e --- /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](https://allcallpro.com) created to [facilitate](https://git.blinkpay.vn) the development of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://aji.ghar.ku.jaldi.nai.aana.ba.tume.dont.tach.me) research, making published research study more quickly reproducible [24] [144] while providing users with an easy user interface for interacting with these environments. In 2022, new 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 study on video games [147] using RL algorithms and research study generalization. Prior RL research study focused mainly on enhancing representatives to solve single jobs. 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 robot agents at first do not have understanding of how to even walk, however are given the objectives of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial [knowing](https://www.mk-yun.cn) procedure, the [representatives discover](http://212.64.10.1627030) how to adapt to altering conditions. When a representative is then eliminated from this virtual environment and positioned in a new [virtual environment](https://wiki.awkshare.com) with high winds, the agent braces to remain upright, recommending it had actually discovered how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents could create an intelligence "arms race" that could increase an agent's capability to operate even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a team of 5 OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that learn to play against human players at a high skill level completely through experimental algorithms. Before becoming a team of 5, the very first public demonstration happened at The International 2017, the yearly best championship competition for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had found out by playing against itself for 2 weeks of genuine time, which the knowing software was an action in the direction of developing software that can handle complex tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of support knowing, as the bots find out over time by playing against themselves [hundreds](https://git.tool.dwoodauto.com) of times a day for months, and are rewarded for [fishtanklive.wiki](https://fishtanklive.wiki/User:KentonR156) actions such as killing an enemy and taking map goals. [154] [155] [156] +
By June 2018, the ability of the bots expanded to play together as a full team of 5, and they had the [ability](https://www.ojohome.listatto.ca) 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 [professional](https://nextodate.com) players, however wound up losing both [video games](https://remnantstreet.com). [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](http://8.142.36.793000) 99.4% of those games. [165] +
OpenAI 5's mechanisms in Dota 2's bot gamer reveals the [obstacles](https://rhabits.io) of [AI](http://116.62.115.84:3000) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually shown the use of deep support knowing (DRL) representatives to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes device learning to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It learns completely in simulation utilizing the very same RL algorithms and [training](https://uconnect.ae) code as OpenAI Five. OpenAI tackled the object orientation issue by utilizing domain randomization, a simulation method which exposes the student to a range of experiences rather than trying to fit to truth. The set-up for Dactyl, aside from having movement tracking video cameras, also has RGB electronic [cameras](http://193.30.123.1883500) to allow the robot to manipulate an approximate object by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might solve a Rubik's Cube. The robotic was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present complicated physics that is harder to model. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of producing gradually more difficult 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 announced a multi-purpose API which it said was "for accessing new [AI](http://code.snapstream.com) designs developed by OpenAI" to let designers get in touch with it for "any English language [AI](https://git.jackbondpreston.me) job". [170] [171] +
Text generation
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The business has popularized 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](https://onthewaytohell.com) design was composed by Alec Radford and his associates, and released in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative model of language might obtain world understanding and process long-range dependencies 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 model and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative variations initially released to the public. The complete version of GPT-2 was not immediately launched due to concern about prospective misuse, [including applications](http://music.afrixis.com) for writing phony news. [174] Some professionals revealed uncertainty that GPT-2 presented a substantial risk.
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In action to GPT-2, the Allen Institute for [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:LettieWhipple7) Artificial Intelligence responded with a tool to detect "neural phony news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to totally 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 launched the complete variation of the GPT-2 language design. [177] Several sites host interactive demonstrations of various instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue not being watched language models to be general-purpose learners, highlighted by GPT-2 attaining cutting edge accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the model 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 with a minimum of 3 upvotes. It prevents certain issues encoding vocabulary with word tokens by using byte pair encoding. This permits representing 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 an unsupervised transformer [language model](https://quicklancer.bylancer.com) and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full version of GPT-3 contained 175 billion criteria, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as couple of as 125 million criteria were likewise trained). [186] +
OpenAI specified that GPT-3 was successful at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper [offered examples](https://bihiring.com) of translation and cross-linguistic transfer learning in between English and Romanian, and in between English and German. [184] +
GPT-3 significantly enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or experiencing the fundamental capability constraints of predictive language 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 design was not right away released to the general public for issues of possible abuse, although OpenAI planned to [enable gain](http://1.117.194.11510080) access to through a paid cloud API after a two-month totally free private beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified 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 on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://wkla.no-ip.biz) powering the [code autocompletion](https://antoinegriezmannclub.com) tool [GitHub Copilot](https://equipifieds.com). [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the model can produce working code in over a lots shows languages, most efficiently in Python. [192] +
Several problems with glitches, design defects and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has actually been accused of [discharging copyrighted](https://orka.org.rs) code, without any author attribution or license. [197] +
OpenAI announced that they would cease 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), efficient in [accepting text](https://men7ty.com) or image inputs. [199] They announced that the [updated innovation](http://git.irunthink.com) passed a [simulated law](http://povoq.moe1145) school bar examination 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 might also check out, evaluate or create up to 25,000 words of text, and compose code in all significant shows languages. [200] +
Observers reported that the model of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, 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 expose numerous technical details and data about GPT-4, such as the accurate size of the model. [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 cutting edge lead to voice, multilingual, and vision criteria, setting brand-new records in audio speech acknowledgment and [translation](https://play.hewah.com). [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) benchmark compared to 86.5% by GPT-4. [207] +
On July 18, 2024, [OpenAI launched](https://gitlog.ru) GPT-4o mini, 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 looking for to automate services with [AI](http://190.117.85.58:8095) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have actually been developed to take more time to consider their actions, [leading](http://bh-prince2.sakura.ne.jp) to higher accuracy. These models are particularly 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 by o1. [211] +
o3
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On December 20, 2024, OpenAI unveiled o3, the follower of the o1 reasoning model. OpenAI also 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 security scientists had the opportunity to obtain early access to these models. [214] The design is called o3 instead of o2 to avoid confusion with telecoms services company O2. [215] +
Deep research
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Deep research study is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of [OpenAI's](https://dvine.tv) o3 design to carry out comprehensive web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [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](http://47.103.91.16050903) to analyze the semantic resemblance in between text and images. It can notably be used for image [category](http://git2.guwu121.com). [217] +
Text-to-image
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DALL-E
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Revealed in 2021, DALL-E is a Transformer model that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation 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 create corresponding images. It can develop images of reasonable things ("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"). 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 announced DALL-E 2, an upgraded variation of the model with more sensible outcomes. [219] In December 2022, OpenAI published 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 model better able to generate images from complex descriptions without manual timely engineering and render complicated 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 on [short detailed](http://mao2000.com3000) triggers [223] as well as extend existing videos forwards or backwards in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of created videos is unidentified.
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Sora's development team called it after the Japanese word for "sky", to represent its "endless imaginative capacity". [223] Sora's innovation is an [adjustment](http://work.diqian.com3000) 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 licensed for that purpose, however did not expose the number or the exact sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, [stating](http://101.200.33.643000) that it might generate videos approximately one minute long. It also shared a technical report highlighting the approaches [utilized](https://yourgreendaily.com) to train the design, and the design's abilities. [225] It acknowledged some of its imperfections, including battles replicating intricate physics. [226] Will Douglas Heaven of the MIT [Technology](https://git.foxarmy.org) Review called the demonstration videos "remarkable", but noted that they must have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demonstration, significant entertainment-industry figures have revealed substantial interest in the [innovation's potential](http://tktko.com3000). In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's ability to create reasonable video from text descriptions, citing its possible to reinvent storytelling and content production. He said that his enjoyment about Sora's possibilities was so strong that he had chosen to stop briefly prepare 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 acknowledgment model. [228] It is [trained](https://git.kawen.site) on a big 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 identification. [229] +
Music generation
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MuseNet
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Released in 2019, MuseNet is a deep neural net [trained](https://www.dataalafrica.com) to predict subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to begin fairly but then fall into chaos 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 produce music for the titular character. [232] [233] +
Jukebox
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Released in 2020, Jukebox is an open-sourced algorithm to generate 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 stated the tunes "show regional musical coherence [and] follow conventional chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that duplicate" and that "there is a considerable gap" between Jukebox and human-generated music. The Verge specified "It's highly remarkable, even if the outcomes sound 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 launched the Debate Game, which teaches machines to discuss toy issues in front of a human judge. The function is to research study whether such a technique might assist in auditing [AI](http://music.afrixis.com) decisions and in establishing explainable [AI](https://tube.leadstrium.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every [considerable layer](https://tempjobsindia.in) and neuron of 8 neural network models which are [typically studied](https://git.bloade.com) in interpretability. [240] Microscope was produced to evaluate the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various variations of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
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[Launched](http://git.zthymaoyi.com) in November 2022, ChatGPT is a synthetic intelligence tool constructed on top of GPT-3 that provides a conversational interface that allows users to ask concerns in natural language. The system then responds with an answer within seconds.
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