adelaidekosovi
/
236
1
0
Code Issues Packages Projects Wiki

Update 'The Verge Stated It's Technologically Impressive'

master
Adelaide Kosovich 1 month ago
parent 1f43fc2f67
commit 209b11c449
1 changed files with 76 additions and 0 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 76
      The-Verge-Stated-It%27s-Technologically-Impressive.md

76
The-Verge-Stated-It%27s-Technologically-Impressive.md
Unescape

@ -0,0 +1,76 @@
<br>Announced in 2016, Gym is an open-source Python library created to assist in the advancement of reinforcement learning algorithms. It aimed to standardize how environments are specified in [AI](https://easy-career.com) 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 actually been [relocated](https://git.markscala.org) to the library Gymnasium. [145] [146]
<br>Gym Retro<br>
<br>Released in 2018, Gym Retro is a platform for [reinforcement knowing](http://150.158.93.1453000) (RL) research on computer game [147] using [RL algorithms](https://git.iidx.ca) and study generalization. Prior RL research focused mainly on optimizing agents to resolve single jobs. Gym Retro gives the ability to generalize between games with similar ideas however various appearances.<br>
<br>RoboSumo<br>
<br>Released in 2017, [RoboSumo](https://kryza.network) is a virtual world where humanoid metalearning robot representatives at first lack understanding of how to even stroll, but are provided the objectives of finding out to move and to push the opposing representative out of the ring. [148] Through this adversarial learning procedure, the representatives discover how to adapt to changing conditions. When an agent is then eliminated from this virtual environment and positioned in a new virtual environment with high winds, the representative braces to remain upright, recommending it had actually found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between agents might create an intelligence "arms race" that might increase a representative's capability to function even outside the context of the competition. [148]
<br>OpenAI 5<br>
<br>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 gamers](https://ourehelp.com) at a high skill level entirely through trial-and-error algorithms. Before becoming a team of 5, the first public demonstration took place at The International 2017, the annual premiere champion competition for the video game, where Dendi, an expert Ukrainian player, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually learned by playing against itself for two weeks of real time, which the learning software was a step in the direction of developing software application that can manage complex tasks like a surgeon. [152] [153] The system utilizes a type of support knowing, as the bots learn with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an opponent and taking map goals. [154] [155] [156]
<br>By June 2018, the ability of the bots expanded to play together as a complete group of 5, and they were able to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against professional gamers, however wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champs 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 on that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those video games. [165]
<br>OpenAI 5's systems in Dota 2's bot gamer shows the [obstacles](http://secdc.org.cn) of [AI](https://setiathome.berkeley.edu) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has demonstrated using deep support knowing (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166]
<br>Dactyl<br>
<br>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 [it-viking.ch](http://it-viking.ch/index.php/User:RaphaelLodewyckx) training code as OpenAI Five. OpenAI took on the issue by utilizing domain randomization, a [simulation](https://git.zyhhb.net) method which exposes the learner to a range of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having motion tracking video cameras, also has RGB cams to permit the [robotic](http://135.181.29.1743001) to control an [approximate object](http://lesstagiaires.com) by seeing it. In 2018, OpenAI revealed that the system had the ability to manipulate a cube and an [octagonal prism](https://sportworkplace.com). [168]
<br>In 2019, OpenAI showed that Dactyl might solve a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present complicated 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 producing gradually more hard environments. ADR differs from manual domain randomization by not needing a human to define randomization varieties. [169]
<br>API<br>
<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://lazerjobs.in) models developed by OpenAI" to let designers call on it for "any English language [AI](http://idesys.co.kr) job". [170] [171]
<br>Text generation<br>
<br>The business has actually promoted generative pretrained transformers (GPT). [172]
<br>OpenAI's original GPT design ("GPT-1")<br>
<br>The original paper on generative pre-training of a transformer-based language design was written by Alec Radford and his coworkers, and published in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative model of language could obtain world knowledge and procedure long-range dependencies by pre-training on a diverse corpus with long stretches of adjoining text.<br>
<br>GPT-2<br>
<br>Generative Pre-trained Transformer 2 ("GPT-2") is a without [supervision transformer](https://git.owlhosting.cloud) language design and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative versions initially released to the public. The complete variation of GPT-2 was not right away launched due to issue about possible abuse, consisting of applications for writing phony news. [174] Some professionals expressed uncertainty that GPT-2 presented a significant threat.<br>
<br>In action to GPT-2, the Allen Institute for Artificial Intelligence [reacted](https://tv.goftesh.com) with a tool to find "neural phony news". [175] Other researchers, such as Jeremy Howard, warned of "the innovation to absolutely 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 launched the total version of the GPT-2 language design. [177] Several sites host interactive presentations of various instances of GPT-2 and other transformer models. [178] [179] [180]
<br>GPT-2's authors argue without supervision language designs to be [general-purpose](https://mediawiki.hcah.in) students, illustrated by GPT-2 [attaining cutting](https://www.hirerightskills.com) edge precision and perplexity on 7 of 8 [zero-shot tasks](https://82.65.204.63) (i.e. the model was not additional trained on any task-specific input-output examples).<br>
<br>The corpus it was trained on, called WebText, contains somewhat 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by using byte pair encoding. This allows representing any string of characters by encoding both private characters and [multiple-character](https://git.thewebally.com) tokens. [181]
<br>GPT-3<br>
<br>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 specified that the full variation of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as few as 125 million criteria were likewise trained). [186]
<br>OpenAI specified that GPT-3 was successful at certain "meta-learning" jobs and could generalize the function 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 between English and German. [184]
<br>GPT-3 drastically enhanced benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or experiencing the basic capability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not right away launched 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 complimentary personal beta that began in June 2020. [170] [189]
<br>On September 23, 2020, GPT-3 was licensed specifically to Microsoft. [190] [191]
<br>Codex<br>
<br>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](https://zidra.ru) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the design can develop working code in over a dozen shows languages, most efficiently in Python. [192]
<br>Several concerns with problems, design flaws and security vulnerabilities were cited. [195] [196]
<br>GitHub Copilot has actually been accused of producing copyrighted code, with no author attribution or license. [197]
<br>OpenAI announced that they would discontinue assistance for Codex API on March 23, 2023. [198]
<br>GPT-4<br>
<br>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 revealed that the upgraded innovation passed a simulated law school bar test with a score around the leading 10% of [test takers](http://116.63.157.38418). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could likewise check out, analyze or create approximately 25,000 words of text, and write code in all major shows languages. [200]
<br>Observers reported that the model of ChatGPT utilizing 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 modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose numerous technical details and data about GPT-4, such as the exact size of the design. [203]
<br>GPT-4o<br>
<br>On May 13, 2024, OpenAI revealed and released GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision standards, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the [Massive Multitask](https://wiki.openwater.health) Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207]
<br>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, [yewiki.org](https://www.yewiki.org/User:EwanDyke4311656) compared to $5 and $15 respectively for GPT-4o. OpenAI expects it to be particularly helpful for enterprises, startups and designers looking for to automate services with [AI](https://trulymet.com) representatives. [208]
<br>o1<br>
<br>On September 12, 2024, OpenAI released the o1[-preview](https://career.agricodeexpo.org) and o1-mini designs, which have been created to take more time to consider their reactions, resulting in higher precision. These models are especially reliable in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, [wavedream.wiki](https://wavedream.wiki/index.php/User:EfrainCantero) o1-preview was changed by o1. [211]
<br>o3<br>
<br>On December 20, 2024, OpenAI revealed 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 use. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the chance to obtain early access to these designs. [214] The design is called o3 rather than o2 to avoid confusion with telecoms services supplier O2. [215]
<br>Deep research study<br>
<br>Deep research study is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform comprehensive web browsing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120]
<br>Image classification<br>
<br>CLIP<br>
<br>Revealed in 2021, CLIP ([Contrastive Language-Image](http://218.17.2.1033000) Pre-training) is a design that is trained to examine the semantic similarity between text and images. It can notably be utilized for image classification. [217]
<br>Text-to-image<br>
<br>DALL-E<br>
<br>Revealed in 2021, DALL-E is a Transformer model that creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to interpret natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images. It can produce images of realistic items ("a stained-glass window with a picture of a blue strawberry") in addition to things that do not exist in truth ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.<br>
<br>DALL-E 2<br>
<br>In April 2022, OpenAI announced DALL-E 2, an [upgraded](https://gitea.baxir.fr) version of the model with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new primary system for transforming a text description into a 3-dimensional model. [220]
<br>DALL-E 3<br>
<br>In September 2023, OpenAI announced DALL-E 3, a more effective model better able to generate images from complex descriptions without manual prompt engineering and render intricate details like hands and text. [221] It was released to the general public as a ChatGPT Plus feature in October. [222]
<br>Text-to-video<br>
<br>Sora<br>
<br>Sora is a text-to-video model that can generate videos based on brief detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.<br>
<br>Sora's development team named it after the Japanese word for "sky", to signify its "endless creative capacity". [223] Sora's technology is an adjustment of the innovation behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos as well as copyrighted videos accredited for that purpose, however did not reveal the number or the [precise sources](https://www.highpriceddatinguk.com) of the videos. [223]
<br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, stating that it could produce videos up to one minute long. It also shared a technical report highlighting the approaches used to train the design, and the model's abilities. [225] It acknowledged some of its shortcomings, consisting of battles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", but kept in mind that they should have been cherry-picked and may not represent Sora's normal output. [225]
<br>Despite uncertainty from some academic leaders following [Sora's public](https://addify.ae) demonstration, significant entertainment-industry figures have revealed considerable interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to produce practical video from text descriptions, citing its potential to reinvent storytelling and content production. He said that his [excitement](http://git.dashitech.com) about Sora's possibilities was so strong that he had chosen to pause prepare for expanding his Atlanta-based motion picture studio. [227]
<br>Speech-to-text<br>
<br>Whisper<br>
<br>Released in 2022, Whisper is a general-purpose speech [acknowledgment design](https://git.cnpmf.embrapa.br). [228] It is trained on a large dataset of varied audio and is also a multi-task model that can perform multilingual speech recognition along with speech translation and language recognition. [229]
<br>Music generation<br>
<br>MuseNet<br>
<br>Released in 2019, MuseNet is a [deep neural](https://git.markscala.org) net trained to anticipate subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 designs. According to The Verge, a tune created by MuseNet tends to start fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, initial applications of this tool were used as early as 2020 for the web psychological thriller Ben Drowned to create music for the [titular character](http://wecomy.co.kr). [232] [233]
<br>Jukebox<br>
<br>Released in 2020, Jukebox is an open-sourced algorithm to generate music with vocals. After [training](http://lesstagiaires.com) on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs song samples. OpenAI mentioned the songs "reveal regional musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes do not have "familiar larger musical structures such as choruses that duplicate" and that "there is a considerable gap" in between Jukebox and human-generated music. The Verge mentioned "It's highly excellent, even if the outcomes seem like mushy versions of songs that might feel familiar", while Business Insider stated "remarkably, some of the resulting tunes are appealing and sound legitimate". [234] [235] [236]
<br>Interface<br>
<br>Debate Game<br>
<br>In 2018, OpenAI released the Debate Game, which teaches devices to debate toy problems in front of a human judge. The purpose is to research whether such a technique may help in auditing [AI](https://spaceballs-nrw.de) decisions and in establishing explainable [AI](https://nujob.ch). [237] [238]
<br>Microscope<br>
<br>Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of eight neural network designs which are typically studied in interpretability. [240] Microscope was produced to [examine](https://gitter.top) the functions that form inside these neural networks easily. The models included are AlexNet, VGG-19, different variations of Inception, and various versions of CLIP Resnet. [241]
<br>ChatGPT<br>
<br>Launched in November 2022, ChatGPT is an expert system tool built on top of GPT-3 that supplies a conversational user interface that permits users to ask questions in natural language. The system then reacts with a response within seconds.<br>
Write Preview
Loading…
Cancel
Save