From 27b6fb08f9a16bea06fe13e9d4ad3bc1d87ab3d0 Mon Sep 17 00:00:00 2001 From: merrisingleton Date: Wed, 5 Mar 2025 20:38:20 +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..e39866b --- /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 knowing algorithms. It aimed to standardize how environments are specified in [AI](https://wheeoo.com) research, making released research more easily reproducible [24] [144] while offering users with a simple user interface for communicating with these environments. In 2022, new [developments](https://ixoye.do) of Gym have been relocated to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research on computer game [147] using RL algorithms and research [study generalization](http://47.95.167.2493000). Prior RL research study focused mainly on enhancing representatives to solve single tasks. Gym Retro provides the capability to generalize between video games with comparable concepts however various [appearances](https://uniondaocoop.com).
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first lack understanding of how to even stroll, but are offered the objectives of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing process, the representatives discover how to adapt to altering conditions. When an agent is then eliminated from this virtual environment and placed in a brand-new virtual environment with high winds, the representative braces to remain upright, recommending it had actually learned how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between agents might create an intelligence "arms race" that might increase an agent's ability 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 utilized in the competitive five-on-five computer game Dota 2, that discover to play against human players at a high [skill level](https://holisticrecruiters.uk) entirely through experimental algorithms. Before ending up being a team of 5, the very first public demonstration happened at The International 2017, the yearly best champion competition for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually found out by playing against itself for 2 weeks of actual time, which the [knowing software](https://littlebigempire.com) application was a step in the instructions of developing software that can manage complicated jobs like a surgeon. [152] [153] The system utilizes a type of reinforcement learning, as the bots discover in time by playing against themselves numerous times a day for months, and are rewarded for actions such as [killing](https://www.hirerightskills.com) an enemy and taking map goals. [154] [155] [156] +
By June 2018, the capability of the bots broadened to play together as a complete group of 5, and they were able to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against expert players, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world [champions](https://diskret-mote-nodeland.jimmyb.nl) of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final 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 video games. [165] +
OpenAI 5's mechanisms in Dota 2's bot gamer shows the obstacles of [AI](https://jobspage.ca) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated the usage of deep reinforcement knowing (DRL) agents to [attain superhuman](https://forum.batman.gainedge.org) skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes device discovering to train a Shadow Hand, a human-like robotic hand, to manipulate physical items. [167] It finds out totally in simulation utilizing the same RL algorithms and [training code](https://www.hijob.ca) as OpenAI Five. OpenAI took on the item orientation issue by using domain randomization, a simulation method which exposes the student to a range of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking video cameras, also has RGB video cameras to enable the robot to manipulate an arbitrary things by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl might fix a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to model. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating gradually harder environments. ADR differs from manual domain randomization by not needing 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 brand-new [AI](https://www.ch-valence-pro.fr) models developed by OpenAI" to let developers contact it for "any English language [AI](https://www.ssecretcoslab.com) job". [170] [171] +
Text generation
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The business has popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT design ("GPT-1")
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The original paper on [generative pre-training](http://47.120.20.1583000) of a transformer-based language model was [composed](https://www.pkjobshub.store) by Alec Radford and his colleagues, and released in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative model of language might obtain world understanding and process long-range reliances by [pre-training](https://izibiz.pl) on a diverse 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 not being watched transformer language model and the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative variations initially released to the general public. The full variation of GPT-2 was not right away released due to issue about possible abuse, consisting of applications for composing fake news. [174] Some specialists expressed uncertainty that GPT-2 posed a substantial threat.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to find "neural fake news". [175] Other researchers, such as Jeremy Howard, alerted of "the technology to completely 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 released the complete variation of the GPT-2 language design. [177] Several sites host interactive demonstrations of various instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being [watched language](https://www.suntool.top) models to be general-purpose students, shown by GPT-2 attaining advanced accuracy 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 a little 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It [prevents](https://www.arztstellen.com) certain problems encoding vocabulary with word tokens by utilizing 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 a without [supervision transformer](https://geoffroy-berry.fr) language design and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full variation of GPT-3 contained 175 billion parameters, [184] 2 orders of [magnitude larger](http://repo.jd-mall.cn8048) than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 designs with as few as 125 million criteria were likewise trained). [186] +
[OpenAI mentioned](https://code.thintz.com) that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the function of a [single input-output](http://39.101.134.269800) pair. The GPT-3 release paper gave examples of [translation](https://mulaybusiness.com) and cross-linguistic transfer knowing between English and Romanian, and in between English and German. [184] +
GPT-3 significantly enhanced benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or coming across the [basic ability](http://adbux.shop) constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not right away launched 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 complimentary personal beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed exclusively to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has actually furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://abcdsuppermarket.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [personal](http://fangding.picp.vip6060) beta. [194] According to OpenAI, the design can produce working code in over a lots programs languages, the majority of successfully in Python. [192] +
Several concerns with glitches, style defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been implicated of releasing copyrighted code, without any 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 revealed the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the [updated technology](http://60.209.125.23820010) passed a simulated law school bar exam with a rating around the top 10% of [test takers](https://chefandcookjobs.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise read, evaluate or produce as much as 25,000 words of text, and write code in all major programming languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an [improvement](http://62.210.71.92) on the previous GPT-3.5-based iteration, with the caveat that GPT-4 [retained](http://demo.qkseo.in) some of the issues with earlier modifications. [201] GPT-4 is likewise [efficient](https://code.oriolgomez.com) in taking images as input on ChatGPT. [202] OpenAI has actually declined to reveal numerous technical details and data about GPT-4, such as the accurate size of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained cutting edge results in voice, multilingual, and vision benchmarks, setting brand-new records in audio speech acknowledgment 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 particularly helpful for business, startups and designers seeking to automate services with [AI](https://kohentv.flixsterz.com) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and [it-viking.ch](http://it-viking.ch/index.php/User:RosieGilliland) o1-mini designs, which have actually been designed to take more time to think of their reactions, resulting in greater precision. These designs are particularly efficient in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Team members. [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 thinking design. OpenAI also unveiled o3-mini, a lighter and much faster version of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the chance to obtain early access to these designs. [214] The design is called o3 instead of o2 to prevent confusion with telecoms companies O2. [215] +
Deep research study
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Deep research is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to carry out substantial web surfing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With searching 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 model that is trained to examine the semantic resemblance between text and images. It can significantly be utilized for image classification. [217] +
Text-to-image
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DALL-E
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[Revealed](https://gitea.chenbingyuan.com) in 2021, DALL-E is a Transformer design that creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can produce images of realistic things ("a stained-glass window with a picture of a blue strawberry") along with objects that do not exist in [reality](https://jobstaffs.com) ("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 updated version of the model with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new rudimentary system for converting a text description into a 3-dimensional model. [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 complex descriptions without manual timely engineering and render [intricate details](https://git.cloudtui.com) like hands and text. [221] It was launched 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 produce videos based upon brief detailed triggers [223] as well as extend existing videos forwards or backwards in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.
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Sora's development group called it after the Japanese word for "sky", to signify its "endless creative capacity". [223] Sora's innovation is an adjustment of the innovation behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos certified for that function, however 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, mentioning that it could generate videos up to one minute long. It likewise shared a technical report highlighting the approaches used to train the model, and the design's capabilities. [225] It acknowledged a few of its imperfections, consisting of battles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", however kept in mind that they need to have been cherry-picked and may not [represent Sora's](https://thematragroup.in) common output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have revealed significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's capability to create reasonable video from text descriptions, mentioning its prospective to revolutionize storytelling and content creation. He said that his excitement about Sora's possibilities was so strong that he had decided to stop briefly strategies 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 on a large [dataset](https://www.lightchen.info) of varied audio and is likewise a multi-task design that can perform multilingual speech recognition along with 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 net [trained](http://git.aimslab.cn3000) to forecast subsequent musical notes in MIDI music files. It can create songs with 10 instruments in 15 styles. According to The Verge, a tune generated by MuseNet tends to begin fairly however then fall into turmoil the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for the internet mental thriller Ben Drowned to create 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 genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI specified the songs "reveal regional musical coherence [and] follow standard chord patterns" but acknowledged that the songs lack "familiar bigger musical structures such as choruses that repeat" which "there is a significant gap" in between Jukebox and human-generated music. The Verge specified "It's highly outstanding, even if the outcomes seem like mushy variations of tunes that might feel familiar", while Business Insider stated "remarkably, a few of the resulting songs are catchy and sound legitimate". [234] [235] [236] +
User user interfaces
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Debate Game
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In 2018, OpenAI introduced the Debate Game, which teaches machines to dispute toy problems in front of a human judge. The [purpose](https://vagyonor.hu) is to research study whether such a method may assist in auditing [AI](https://gitlab.minet.net) choices and in developing explainable [AI](http://ieye.xyz:5080). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of eight designs which are frequently studied in [interpretability](http://social.redemaxxi.com.br). [240] Microscope was developed to examine the functions that form inside these neural networks quickly. The models included are AlexNet, VGG-19, various 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 built on top of GPT-3 that offers 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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