From 465cfdc7cf05d268c4d93469f8bc1be30d088f61 Mon Sep 17 00:00:00 2001 From: Candra Wurst Date: Sun, 9 Feb 2025 11:26:37 +0000 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..6cd5a0d --- /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 developed to facilitate the advancement of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](https://wiki.kkg.org) research, making released research more quickly reproducible [24] [144] while providing users with a simple interface for communicating with these environments. In 2022, new developments of Gym have been transferred to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support knowing (RL) research study on video games [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on optimizing agents to fix single tasks. Gym Retro offers the ability to generalize between video games with comparable concepts but various appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially lack understanding of how to even stroll, but are given the objectives of finding out to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the representatives discover how to adapt to changing conditions. When an agent is then eliminated from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, recommending it had actually discovered how to stabilize in a generalized way. [148] [149] [OpenAI's Igor](http://39.104.23.773000) Mordatch argued that competition in between agents could produce an intelligence "arms race" that might increase a representative's capability to operate 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](https://www.yourtalentvisa.com) five-on-five computer game Dota 2, that find out to play against human gamers at a high ability level totally through experimental algorithms. Before ending up being a group of 5, the very first public demonstration occurred at The International 2017, the annual best champion competition for the game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually 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, and that the knowing software was a step in the instructions of developing software application that can manage complicated tasks like a cosmetic surgeon. [152] [153] The system utilizes a kind of reinforcement knowing, [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:LindaIsenberg91) as the [bots learn](http://154.209.4.103001) with time by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an opponent and taking map objectives. [154] [155] [156] +
By June 2018, the capability of the [bots expanded](http://47.103.91.16050903) to play together as a complete team of 5, and they had the ability to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The [International](https://gitea.winet.space) 2018, OpenAI Five played in two [exhibition matches](http://124.222.85.1393000) against [professional](https://unitenplay.ca) players, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public look came later that month, where they played in 42,729 overall video games in a four-day open online competitors, winning 99.4% of those [video games](http://git.oksei.ru). [165] +
OpenAI 5['s mechanisms](https://youtoosocialnetwork.com) in Dota 2's bot player shows the challenges of [AI](https://friendfairs.com) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually shown using deep reinforcement knowing (DRL) agents to [attain superhuman](https://vhembedirect.co.za) skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses maker learning to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It learns completely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation issue by utilizing domain randomization, a simulation approach which exposes the learner to a [variety](https://joinwood.co.kr) of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having movement tracking electronic cameras, likewise has RGB electronic cameras to permit the robot to [control](https://git.home.lubui.com8443) an arbitrary item by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI [demonstrated](https://jobs.fabumama.com) that Dactyl might resolve a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present [intricate physics](http://yanghaoran.space6003) that is harder to model. OpenAI did this by improving the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of generating gradually harder environments. ADR varies from manual domain randomization by not needing a human to specify randomization ranges. [169] +
API
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In June 2020, [OpenAI revealed](https://sublimejobs.co.za) a multi-purpose API which it said was "for accessing new [AI](http://forum.altaycoins.com) designs established by OpenAI" to let developers contact it for "any English language [AI](https://zikorah.com) task". [170] [171] +
Text generation
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The company has actually 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 design was written by Alec Radford and his coworkers, and released in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world understanding and [process long-range](https://git.joystreamstats.live) dependences by pre-training on a diverse 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 a without supervision transformer language model and [raovatonline.org](https://raovatonline.org/author/giagannon42/) the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only minimal demonstrative variations at first released to the general public. The full version of GPT-2 was not immediately launched due to concern about prospective misuse, consisting of applications for composing phony news. [174] Some experts revealed uncertainty that GPT-2 postured a considerable risk.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned of "the innovation to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be difficult to filter". [176] In November 2019, OpenAI released the total version of the GPT-2 language model. [177] Several sites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue without supervision language models to be general-purpose students, illustrated by GPT-2 attaining advanced precision and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not further [trained](http://175.24.176.23000) on any task-specific input-output examples).
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The corpus it was trained on, called WebText, contains a little 40 [gigabytes](http://39.101.160.118099) of text from [URLs shared](https://git.gz.internal.jumaiyx.cn) in Reddit submissions with at least 3 [upvotes](https://git.the-kn.com). It avoids certain problems encoding vocabulary with word tokens by using byte pair encoding. This permits representing any string of characters by encoding both private characters and multiple-character tokens. [181] +
GPT-3
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First explained in May 2020, Generative Pre-trained [a] [Transformer](https://dev.clikviewstorage.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 parameters, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 designs with as couple of as 125 million parameters were also trained). [186] +
OpenAI stated that GPT-3 prospered at certain "meta-learning" tasks and could generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning in between English and Romanian, and in between [English](https://wiki.armello.com) and German. [184] +
GPT-3 dramatically enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or encountering the fundamental ability constraints of predictive language models. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of compute, [compared](https://223.130.175.1476501) to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not right away launched to the general public for concerns of possible abuse, although [OpenAI prepared](https://git.prayujt.com) to permit gain access to through a paid cloud API after a two-month free personal 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 actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://39.98.194.76:3000) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in [private](https://www.globaltubedaddy.com) beta. [194] According to OpenAI, the design can create working code in over a dozen programs languages, a lot of successfully in Python. [192] +
Several concerns with glitches, [style flaws](https://customerscomm.com) and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has been implicated of discharging copyrighted code, with no [author attribution](http://47.111.72.13001) or license. [197] +
OpenAI revealed that they would terminate support for [larsaluarna.se](http://www.larsaluarna.se/index.php/User:HelenTennyson48) 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 innovation passed a simulated law school bar test 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 likewise read, examine or generate up to 25,000 words of text, and write code in all significant shows languages. [200] +
Observers reported that the version of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has actually declined to expose different technical details and stats 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 generate text, images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision benchmarks, setting new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized version 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 anticipates it to be particularly helpful for business, startups and developers seeking to automate services with [AI](https://freelyhelp.com) representatives. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have actually been created to take more time to think of their actions, causing greater precision. These designs are particularly efficient in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was changed by o1. [211] +
o3
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On December 20, 2024, OpenAI revealed o3, the follower of the o1 reasoning design. OpenAI also revealed o3-mini, a lighter and quicker 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, safety and security researchers had the opportunity to obtain early access to these models. [214] The model is called o3 instead of o2 to avoid confusion with telecoms companies O2. [215] +
Deep research
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Deep research is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the [abilities](https://squishmallowswiki.com) of OpenAI's o3 design to carry out substantial web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools enabled, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) standard. [120] +
Image category
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CLIP
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Revealed in 2021, CLIP ([Contrastive Language-Image](http://171.244.15.683000) Pre-training) is a model that is trained to evaluate the semantic similarity 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 creates 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 formed like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can produce pictures of practical things ("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 revealed DALL-E 2, an upgraded variation of the design with more realistic results. [219] In December 2022, [OpenAI published](https://www.jungmile.com) on GitHub software application for [yewiki.org](https://www.yewiki.org/User:ElenaGrenda45) Point-E, a 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 generate images from complex descriptions without manual prompt engineering and render intricate details like hands and text. [221] It was launched to the general public as a ChatGPT Plus feature in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video model that can produce videos based on short detailed prompts [223] along with extend existing videos forwards or [surgiteams.com](https://surgiteams.com/index.php/User:CathleenMadison) backwards in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The [optimum length](https://www.rozgar.site) of generated videos is unknown.
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Sora's development group called it after the Japanese word for "sky", to represent its "unlimited innovative potential". [223] Sora's innovation is an adjustment of the technology behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos as well as [copyrighted videos](https://223.130.175.1476501) licensed for that purpose, however did not expose the number or the specific sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, specifying that it could generate videos approximately one minute long. It also shared a technical report highlighting the methods used to train the design, and the model's abilities. [225] It acknowledged some of its shortcomings, consisting of struggles replicating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", however noted that they should have been cherry-picked and might 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 considerable interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his [astonishment](https://gitlab.keysmith.bz) at the technology's capability to produce sensible video from text descriptions, mentioning its possible to change storytelling and content development. He said that his enjoyment about Sora's possibilities was so strong that he had decided to pause 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](https://jimsusefultools.com) on a large dataset of diverse audio and is also a multi-task model 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 anticipate subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 designs. According to The Verge, a song generated by MuseNet tends to start fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the web 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 category, artist, and a snippet of lyrics and outputs tune samples. OpenAI stated the tunes "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the songs do not have "familiar bigger musical structures such as choruses that duplicate" and that "there is a substantial space" between Jukebox and human-generated music. The Verge mentioned "It's highly excellent, even if the outcomes seem like mushy variations of tunes that may feel familiar", while Business Insider specified "remarkably, a few of the resulting songs are memorable and sound genuine". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, OpenAI released the Debate Game, which teaches machines to discuss toy issues in front of a human judge. The function is to research study whether such an approach may assist in auditing [AI](https://4kwavemedia.com) decisions and in [establishing explainable](https://semtleware.com) [AI](https://myclassictv.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and neuron of 8 neural network models which are often studied in interpretability. [240] Microscope was created to evaluate the features that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various versions of Inception, and different variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is a tool developed on top of GPT-3 that provides a conversational interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.
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