From 4fcd02f4e2a418715f477565acd288f5350fc955 Mon Sep 17 00:00:00 2001 From: marcellanall09 Date: Thu, 20 Feb 2025 05:11:23 +0800 Subject: [PATCH] Update '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..9ac095e --- /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 created to assist in the advancement of support knowing algorithms. It aimed to standardize how environments are defined in [AI](https://origintraffic.com) research, making released research more quickly reproducible [24] [144] while providing users with a basic interface for connecting with these environments. In 2022, brand-new advancements of Gym have been moved 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 video games [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on enhancing agents to solve single tasks. Gym Retro gives the ability to generalize in between games with similar principles but various 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 knowledge of how to even walk, but are given the goals of finding out to move and to press the [opposing representative](https://code.agileum.com) out of the ring. [148] Through this [adversarial knowing](https://members.advisorist.com) process, the representatives find out how to adapt to changing conditions. When a representative is then removed from this virtual environment and put in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had discovered how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents might create an intelligence "arms race" that could increase an agent's ability to operate even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a group of 5 OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that find out to play against human players at a high ability level entirely through experimental algorithms. Before becoming a group of 5, the first public demonstration took place at The International 2017, the yearly best championship competition for the video game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually matchup. [150] [151] After the match, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) CTO Greg Brockman explained that the bot had discovered by playing against itself for 2 weeks of actual time, which the learning software [application](https://git.hxps.ru) was an action in the direction of creating software that can deal with intricate jobs like a cosmetic surgeon. [152] [153] The system uses a kind of reinforcement learning, as the bots learn 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 goals. [154] [155] [156] +
By June 2018, the ability of the bots expanded to play together as a full group of 5, and they had the ability to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against professional players, but wound up losing both video 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 appearance came later that month, where they played in 42,729 total video games in a [four-day](https://git.obo.cash) 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://sea-crew.ru) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has shown using deep reinforcement knowing (DRL) representatives to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses machine finding out to train a Shadow Hand, a human-like robot hand, to control physical objects. [167] It learns totally in simulation using the very same RL algorithms and [training code](https://sebeke.website) as OpenAI Five. OpenAI dealt with the item orientation problem by utilizing domain randomization, a simulation method which exposes the student to a range of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking cams, also has RGB cameras to allow the robot to manipulate an approximate item 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 could solve a Rubik's Cube. The robot was able to fix the puzzle 60% of the time. [Objects](https://cvmira.com) like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by improving the robustness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation method of producing progressively more difficult environments. ADR differs from manual [domain randomization](https://origintraffic.com) by not needing a human to define randomization varieties. [169] +
API
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In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://code.smolnet.org) models established by OpenAI" to let designers contact it for "any English language [AI](https://git.tedxiong.com) task". [170] [171] +
Text generation
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The business has actually promoted generative [pretrained transformers](http://118.31.167.22813000) (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](http://taesungco.net) design was composed by Alec Radford and his coworkers, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world understanding and process 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 a without supervision transformer language design and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just limited demonstrative versions initially released to the public. The complete [variation](https://copyright-demand-letter.com) of GPT-2 was not right away released due to issue about prospective misuse, consisting of applications for writing phony news. [174] Some experts revealed [uncertainty](https://git.intelgice.com) that GPT-2 presented a substantial hazard.
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In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to find "neural fake news". [175] Other researchers, such as Jeremy Howard, warned 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 total version of the GPT-2 language design. [177] Several websites host interactive presentations 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 students, shown by GPT-2 attaining advanced accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the design 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 a minimum of 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by utilizing byte pair [encoding](https://www.truckjob.ca). 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 language model and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were also trained). [186] +
OpenAI specified that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of [translation](https://elsingoteo.com) and cross-linguistic transfer knowing between English and Romanian, and between [English](https://git.obo.cash) and German. [184] +
GPT-3 considerably improved benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models might be approaching or coming across the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of compute, [compared](https://cvmira.com) to 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately released to the public for issues of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month free private 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](http://gitlab.nsenz.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [personal](https://han2.kr) beta. [194] According to OpenAI, the model can create working code in over a dozen programming languages, most efficiently in Python. [192] +
Several problems with glitches, design defects and security vulnerabilities were cited. [195] [196] +
[GitHub Copilot](https://git.i2edu.net) has actually been accused of discharging copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would discontinue support for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the upgraded innovation 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 might likewise check out, examine or [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:Juliane3350) generate approximately 25,000 words of text, and write code in all major shows languages. [200] +
Observers reported that the version of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained a few of the problems with earlier revisions. [201] GPT-4 is likewise [capable](https://code.dev.beejee.org) of taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal numerous [technical details](http://fcgit.scitech.co.kr) and stats about GPT-4, such as the [accurate size](https://mediawiki1334.00web.net) of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained advanced lead to voice, multilingual, and vision criteria, setting 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 launched GPT-4o mini, a smaller version 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 particularly helpful for enterprises, startups and designers seeking to automate services with [AI](https://sublimejobs.co.za) representatives. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and [raovatonline.org](https://raovatonline.org/author/angelicadre/) o1-mini models, which have been designed to take more time to consider their actions, leading to greater accuracy. These designs are especially effective in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was replaced by o1. [211] +
o3
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On December 20, 2024, [OpenAI revealed](http://betterlifenija.org.ng) o3, the follower of the o1 thinking design. OpenAI also unveiled o3-mini, a lighter and much faster variation 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, security and security researchers had the opportunity to obtain early access to these models. [214] The design is called o3 rather than o2 to avoid confusion with [telecommunications companies](https://brotato.wiki.spellsandguns.com) O2. [215] +
Deep research
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Deep research is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of [OpenAI's](https://europlus.us) o3 model to carry out comprehensive web surfing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools enabled, it reached an accuracy 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 evaluate the semantic similarity in 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 in 2021, DALL-E is a Transformer design that develops 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 handbag shaped like a pentagon" or "an isometric view of a sad capybara") and [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2684771) create matching images. It can develop images of sensible objects ("a stained-glass window with a picture of a blue strawberry") as well as objects 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 revealed DALL-E 2, an upgraded version of the model with more reasonable results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new basic system for converting 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 generate images from complicated descriptions without manual timely engineering and render intricate details like hands and text. [221] It was [launched](http://8.140.205.1543000) 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 design that can generate videos based on brief detailed triggers [223] in addition to extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The [optimum length](https://www.tinguj.com) of created videos is unidentified.
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Sora's advancement group called it after the Japanese word for "sky", to signify its "unlimited creative capacity". [223] Sora's technology is an adjustment of the technology behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos as well as copyrighted videos licensed for that purpose, however did not expose the number or the [exact sources](https://japapmessenger.com) of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it might create videos approximately one minute long. It likewise shared a technical report highlighting the methods used to train the design, and the model's capabilities. [225] It acknowledged some of its shortcomings, including struggles simulating [complex physics](https://skylockr.app). [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "remarkable", however kept in mind that they must have been cherry-picked and might not represent Sora's typical output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:CatalinaHoffnung) notable entertainment-industry figures have revealed considerable interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's ability to generate reasonable video from text descriptions, mentioning its potential to revolutionize storytelling and content production. He said that his excitement about Sora's possibilities was so strong that he had decided to stop briefly prepare for expanding his [Atlanta-based motion](http://120.92.38.24410880) 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 model. [228] It is trained on a large dataset of varied audio and is also a multi-task design that can perform multilingual speech acknowledgment 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 to predict subsequent musical notes in MIDI music files. It can create tunes with 10 instruments in 15 designs. According to The Verge, a [tune generated](https://www.milegajob.com) by MuseNet tends to begin fairly but then fall under turmoil the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for the web mental 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 music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs song samples. OpenAI mentioned the songs "show regional musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes lack "familiar larger musical structures such as choruses that duplicate" which "there is a considerable gap" in between Jukebox and human-generated music. The Verge stated "It's technically impressive, even if the results sound like mushy versions of tunes that might feel familiar", while Business Insider mentioned "surprisingly, a few of the resulting tunes are catchy and sound legitimate". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, OpenAI introduced the Debate Game, which to debate toy problems in front of a human judge. The purpose is to research whether such a technique might help in auditing [AI](https://asromafansclub.com) decisions and in establishing explainable [AI](https://cmegit.gotocme.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and nerve cell of eight neural network designs which are frequently studied in [interpretability](https://myteacherspool.com). [240] Microscope was created to analyze the functions that form inside these neural networks quickly. The designs [consisted](https://evertonfcfansclub.com) of are AlexNet, VGG-19, different versions of Inception, and different versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that supplies a conversational interface that permits users to ask [concerns](https://voyostars.com) in natural language. The system then responds with an answer within seconds.
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