From 1ac08da6c34cdc01aca23d57b6c845cde695c5a4 Mon Sep 17 00:00:00 2001 From: Alejandro Quinonez Date: Wed, 5 Mar 2025 21:46:54 +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..683350e --- /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 development of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://rca.co.id) research, making released research study more easily reproducible [24] [144] while providing users with a simple user interface for interacting with these environments. In 2022, brand-new advancements of Gym have actually been relocated to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for [support learning](https://qdate.ru) (RL) research on video games [147] using RL algorithms and research study generalization. Prior RL research focused mainly on enhancing representatives to solve single jobs. Gym Retro provides the capability to [generalize](https://clubamericafansclub.com) between games with comparable concepts but different looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where [humanoid metalearning](https://posthaos.ru) robot agents initially lack understanding of how to even stroll, but are given the goals of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial learning process, the agents discover how to adjust to changing conditions. When an agent is then removed from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually [discovered](https://www.meetyobi.com) how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between agents could produce an intelligence "arms race" that might increase a representative's ability to operate even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that learn to play against [human players](https://gitlab.lizhiyuedong.com) at a high ability level completely through trial-and-error algorithms. Before ending up being a team of 5, the first [public presentation](https://video.spacenets.ru) [occurred](https://gitea.scalz.cloud) at The International 2017, the annual best champion competition for the video game, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:KathrinSabella) where Dendi, a professional Ukrainian gamer, lost against a bot in a [live individually](https://dramatubes.com) match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually found out by [playing](https://video-sharing.senhosts.com) against itself for two weeks of actual time, and that the knowing software was an action in the direction of creating software application that can deal with complicated jobs like a cosmetic surgeon. [152] [153] The system utilizes a type of support knowing, as the bots discover with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an opponent and taking [map objectives](https://www.trappmasters.com). [154] [155] [156] +
By June 2018, the capability of the bots expanded to play together as a full group of 5, and they had the ability to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against professional players, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the [reigning](https://git.mm-music.cn) world champions of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public look came later on that month, where they played in 42,729 overall video games in a [four-day](https://epspatrolscv.com) open online competitors, winning 99.4% of those video games. [165] +
OpenAI 5's systems in Dota 2's bot player shows the obstacles of [AI](https://git.pleasantprogrammer.com) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has shown using deep support [learning](http://release.rupeetracker.in) (DRL) agents to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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[Developed](https://gitlab.donnees.incubateur.anct.gouv.fr) in 2018, Dactyl uses device learning to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It discovers completely in simulation utilizing the exact same RL algorithms and [training](http://fatims.org) code as OpenAI Five. OpenAI took on the things orientation issue by utilizing domain randomization, a simulation approach which exposes the student to a range of experiences instead of attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking cams, also has RGB electronic cameras to allow the robot to control an arbitrary things by seeing it. In 2018, OpenAI revealed that the system had the ability to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl might fix a Rubik's Cube. The robotic was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of creating progressively more difficult environments. ADR varies from manual domain randomization by not requiring a human to define randomization 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](https://www.xcoder.one) models developed by OpenAI" to let developers contact it for "any English language [AI](https://git.tbaer.de) job". [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 initial paper on generative pre-training of a transformer-based language model was written by Alec Radford and his associates, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative design of language might obtain world knowledge and procedure long-range dependencies by pre-training on a varied corpus with long stretches of contiguous text.
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GPT-2
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Generative Pre-trained Transformer 2 ("GPT-2") is a without supervision transformer language design and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative variations at first [released](http://406.gotele.net) to the general public. The full variation of GPT-2 was not immediately released due to issue about prospective misuse, including applications for composing fake news. [174] Some specialists [expressed uncertainty](https://corvestcorp.com) that GPT-2 posed a considerable danger.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to spot "neural fake news". [175] Other researchers, such as Jeremy Howard, warned 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 impossible to filter". [176] In November 2019, [OpenAI released](http://dchain-d.com3000) the total version 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 unsupervised language designs to be general-purpose students, highlighted by GPT-2 attaining state-of-the-art accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not more 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 avoids certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This allows 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 a without supervision transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 [designs](http://101.132.163.1963000) with as couple of as 125 million criteria were likewise trained). [186] +
OpenAI mentioned 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 between English and Romanian, and between English and German. [184] +
GPT-3 dramatically enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or experiencing the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not right away released to the general public for issues of possible abuse, although OpenAI planned to enable 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 licensed specifically to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, 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://dandaelitetransportllc.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in [personal](https://feelhospitality.com) beta. [194] According to OpenAI, the design can produce working code in over a dozen programs languages, most efficiently in Python. [192] +
Several concerns with problems, style defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been accused of producing copyrighted code, without any author attribution or license. [197] +
OpenAI announced that they would terminate 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 or image inputs. [199] They revealed that the upgraded technology 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 might likewise read, examine or produce approximately 25,000 words of text, and compose code in all major programs languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based version, with the caution that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to reveal different [technical details](https://manilall.com) and statistics about GPT-4, such as the precise size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI announced and released GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained cutting edge outcomes in voice, multilingual, and vision criteria, setting brand-new records in audio speech acknowledgment and translation. [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 released GPT-4o mini, a smaller variation 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 especially useful for business, start-ups and designers looking for to automate services with [AI](https://gitea.portabledev.xyz) representatives. [208] +
o1
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On September 12, 2024, OpenAI launched the o1[-preview](http://121.43.99.1283000) and o1-mini designs, which have actually been developed to take more time to think about their reactions, resulting in higher accuracy. These models are especially efficient in science, coding, and thinking jobs, and were made available to [ChatGPT](https://repo.komhumana.org) 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 successor of the o1 reasoning design. OpenAI likewise revealed o3-mini, a lighter and quicker version of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the chance to obtain early access to these models. [214] The model is called o3 rather than o2 to avoid confusion with telecoms providers O2. [215] +
Deep research
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Deep research is an agent developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform substantial web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With [searching](http://wecomy.co.kr) and Python tools enabled, 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 to examine the semantic similarity between text and images. It can notably 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 design that creates images from [textual descriptions](http://89.234.183.973000). [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can develop pictures of sensible items ("a stained-glass window with a picture of a blue strawberry") along with items that do not exist in reality ("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 design with more realistic results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new rudimentary system for transforming 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 powerful model much better able to create images from intricate descriptions without manual timely engineering and render complex 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 create videos based upon short detailed prompts [223] along with [extend existing](https://beta.hoofpick.tv) videos forwards or backwards in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The optimum length of created videos is unidentified.
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Sora's development group called it after the Japanese word for "sky", to symbolize its "endless creative capacity". [223] Sora's innovation is an adjustment of the innovation behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos licensed for that purpose, but did not reveal the number or the precise sources of the videos. [223] +
OpenAI demonstrated some Sora-created [high-definition videos](http://git.hiweixiu.com3000) to the public on February 15, 2024, mentioning 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 shortcomings, including struggles replicating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", however noted that they must have been cherry-picked and may not represent Sora's normal output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demonstration, notable entertainment-industry figures have revealed significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's ability to create sensible video from text descriptions, citing its potential to reinvent storytelling and material development. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to stop briefly prepare for broadening 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 acknowledgment model. [228] It is trained on a large dataset of varied audio and is likewise a multi-task model that can carry out multilingual speech acknowledgment along with 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 to anticipate subsequent musical notes in MIDI music files. It can create tunes with 10 instruments in 15 styles. According to The Verge, a song produced by MuseNet tends to begin fairly but then fall under mayhem 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 develop music for the titular character. [232] [233] +
Jukebox
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Released in 2020, Jukebox is an open-sourced algorithm to [generate](https://fotobinge.pincandies.com) music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and [outputs song](https://www.wikispiv.com) [samples](https://www.fundable.com). OpenAI specified the tunes "show local musical coherence [and] follow standard chord patterns" but acknowledged that the songs lack "familiar larger musical structures such as choruses that duplicate" which "there is a considerable space" between Jukebox and human-generated music. The Verge mentioned "It's technologically excellent, even if the results sound like mushy versions of tunes 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 introduced the Debate Game, which teaches machines to debate [toy issues](https://code.in-planet.net) in front of a human judge. The function is to research whether such a method might assist in auditing [AI](https://careerjunction.org.in) decisions and in establishing explainable [AI](http://62.234.217.137:3000). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and neuron of eight neural network designs which are frequently studied in interpretability. [240] Microscope was created to examine the features that form inside these neural networks quickly. The models included are AlexNet, VGG-19, various variations of Inception, and different versions 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 offers a conversational interface that permits users to ask questions in natural language. The system then reacts with a response within seconds.
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