blanche55x7118
/
nongnghiepso
1
0
Code Issues Packages Projects Wiki

Add The Verge Stated It's Technologically Impressive

Blanche Gracia 2025-04-11 17:06:23 +08:00
commit fb724cdef9
1 changed files with 76 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

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

@ -0,0 +1,76 @@
<br>Announced in 2016, Gym is an open-source Python library developed to facilitate the advancement of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://www.opad.biz) research, making released research study more [easily reproducible](http://154.64.253.773000) [24] [144] while providing users with a basic interface for engaging with these environments. In 2022, new advancements of Gym have actually been transferred to the library Gymnasium. [145] [146]
<br>Gym Retro<br>
<br>Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on enhancing agents to solve single jobs. Gym Retro provides the ability to generalize in between games with similar ideas however various appearances.<br>
<br>RoboSumo<br>
<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot representatives initially lack understanding of how to even walk, but are offered the objectives of finding out to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives learn how to adjust to changing conditions. When an agent is then eliminated from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually discovered how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might develop an [intelligence](https://www.smfsimple.com) "arms race" that might increase an agent's ability to work even outside the context of the competitors. [148]
<br>OpenAI 5<br>
<br>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 at a high ability level completely through experimental algorithms. Before becoming a group of 5, the first public demonstration happened at The International 2017, the yearly premiere champion [tournament](https://www.bolsadetrabajotafer.com) for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had learned by playing against itself for two weeks of actual time, and that the knowing software application was a step in the instructions of [developing software](http://thegrainfather.com) that can deal with complex jobs like a cosmetic surgeon. [152] [153] The system [utilizes](https://git.poggerer.xyz) a kind of reinforcement knowing, as the bots discover over time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156]
<br>By June 2018, the capability of the bots broadened to play together as a complete team of 5, and they had the ability to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against expert players, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champions of the game at the time, 2:0 in a [live exhibition](http://recruitmentfromnepal.com) match in [San Francisco](https://git.xjtustei.nteren.net). [163] [164] The bots' last public look 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 games. [165]
<br>OpenAI 5's mechanisms in Dota 2's bot player shows the [obstacles](https://careers.ebas.co.ke) of [AI](https://git.watchmenclan.com) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually shown making use of deep support knowing (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166]
<br>Dactyl<br>
<br>Developed in 2018, Dactyl utilizes maker learning to train a Shadow Hand, a [human-like robotic](https://aloshigoto.jp) hand, to manipulate physical things. [167] It learns totally in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation problem by using domain randomization, a simulation approach which exposes the learner to a range of experiences instead of attempting to fit to reality. The set-up for Dactyl, aside from having cams, also has RGB cameras to enable the robotic to manipulate an arbitrary object by seeing it. In 2018, OpenAI showed that the system had the ability to manipulate a cube and an octagonal prism. [168]
<br>In 2019, OpenAI demonstrated that Dactyl might fix a Rubik's Cube. The robotic had the ability to fix the puzzle 60% of the time. [Objects](http://sdongha.com) like the Rubik's Cube introduce intricate physics that is harder to model. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of producing gradually more difficult environments. ADR varies from manual domain randomization by not needing a human to specify randomization ranges. [169]
<br>API<br>
<br>In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](https://premiergitea.online:3000) designs developed by OpenAI" to let developers get in touch with it for "any English language [AI](http://park1.wakwak.com) job". [170] [171]
<br>Text generation<br>
<br>The business has actually popularized generative pretrained transformers (GPT). [172]
<br>OpenAI's original GPT model ("GPT-1")<br>
<br>The original paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his colleagues, and published in [preprint](http://1.94.127.2103000) on OpenAI's website on June 11, 2018. [173] It showed how a generative design of language could obtain world [understanding](https://git.arcbjorn.com) and process long-range [reliances](http://fatims.org) 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 language design and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative versions at first released to the public. The complete version of GPT-2 was not immediately released due to issue about prospective misuse, consisting of applications for writing fake news. [174] Some specialists revealed uncertainty that GPT-2 postured a substantial threat.<br>
<br>In response 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, alerted of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be impossible to filter". [176] In November 2019, OpenAI released the complete variation of the GPT-2 language design. [177] Several sites host interactive demonstrations of different [instances](http://47.101.207.1233000) of GPT-2 and other transformer models. [178] [179] [180]
<br>GPT-2's authors argue without supervision language models to be general-purpose students, shown by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the design 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 prevents certain concerns encoding [vocabulary](https://pittsburghpenguinsclub.com) 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]
<br>GPT-3<br>
<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an [unsupervised transformer](https://chat.app8station.com) language design and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were likewise trained). [186]
<br>OpenAI mentioned that GPT-3 prospered at certain "meta-learning" jobs and could generalize the [function](https://jobidream.com) of a single input-output pair. The GPT-3 release paper provided examples of translation and [wiki.whenparked.com](https://wiki.whenparked.com/User:LashawnLutwyche) cross-linguistic transfer knowing in between [English](http://www.kotlinx.com3000) and Romanian, and between English and German. [184]
<br>GPT-3 dramatically enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or encountering the basic ability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not right away [launched](http://47.244.232.783000) to the public for issues of possible abuse, [89u89.com](https://www.89u89.com/author/busterroby/) although OpenAI prepared to enable gain access to through a paid cloud API after a two-month free private beta that started in June 2020. [170] [189]
<br>On September 23, 2020, GPT-3 was licensed solely to Microsoft. [190] [191]
<br>Codex<br>
<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.bourseeye.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:DewittDenson02) an API was launched in private beta. [194] According to OpenAI, the model can produce working code in over a lots shows languages, a lot of successfully in Python. [192]
<br>Several concerns with problems, style defects and security vulnerabilities were cited. [195] [196]
<br>GitHub Copilot has been accused of emitting copyrighted code, with no author attribution or license. [197]
<br>OpenAI revealed that they would stop 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), efficient in [accepting text](https://bd.cane-recruitment.com) or image inputs. [199] They announced that the upgraded innovation passed a simulated law school bar exam with a score 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 generate approximately 25,000 words of text, and compose code in all significant programs languages. [200]
<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has actually declined to reveal numerous technical details and statistics about GPT-4, such as the accurate size of the design. [203]
<br>GPT-4o<br>
<br>On May 13, 2024, [OpenAI revealed](http://43.139.10.643000) and released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained advanced lead to 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) criteria compared to 86.5% by GPT-4. [207]
<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller variation of GPT-4o changing 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 looking for to automate services with [AI](https://caringkersam.com) representatives. [208]
<br>o1<br>
<br>On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have actually been developed to take more time to consider their responses, causing higher accuracy. These designs are particularly reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was changed by o1. [211]
<br>o3<br>
<br>On December 20, 2024, OpenAI revealed o3, the follower of the o1 reasoning design. OpenAI also unveiled o3-mini, a lighter and faster variation of OpenAI o3. Since December 21, 2024, this model is not available for public usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the chance to obtain early access to these designs. [214] The design is called o3 rather than o2 to prevent confusion with telecommunications services supplier O2. [215]
<br>Deep research study<br>
<br>Deep research study is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to [perform extensive](http://gitlab.digital-work.cn) web surfing, data analysis, and synthesis, delivering detailed [reports](https://3.223.126.156) within a timeframe of 5 to thirty minutes. [216] With searching and [Python tools](https://washcareer.com) 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 Pre-training) is a model that is trained to examine the semantic resemblance between text and images. It can notably be used for image category. [217]
<br>Text-to-image<br>
<br>DALL-E<br>
<br>Revealed in 2021, DALL-E is a Transformer model that produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to interpret natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and generate matching images. It can develop pictures of reasonable items ("a stained-glass window with a picture of a blue strawberry") along with 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 version of the design with more practical results. [219] In December 2022, OpenAI published on GitHub software for Point-E, a new fundamental system for transforming a text description into a 3-dimensional model. [220]
<br>DALL-E 3<br>
<br>In September 2023, OpenAI revealed DALL-E 3, a more powerful model better able to generate images from complicated descriptions without manual timely engineering and render intricate details like hands and text. [221] It was [launched](https://atfal.tv) to the public as a ChatGPT Plus function in October. [222]
<br>Text-to-video<br>
<br>Sora<br>
<br>Sora is a text-to-video design that can create videos based on brief detailed triggers [223] in addition to extend existing videos forwards or in reverse in time. [224] It can [generate videos](https://mobidesign.us) with resolution approximately 1920x1080 or 1080x1920. The optimum length of produced videos is unidentified.<br>
<br>Sora's development group called it after the Japanese word for "sky", to represent its "endless creative potential". [223] Sora's technology is an adjustment of the technology behind the DALL · E 3 [text-to-image](https://globalabout.com) design. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos licensed for that function, however did not reveal the number or the precise sources of the videos. [223]
<br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it might create videos approximately one minute long. It also shared a technical report highlighting the techniques utilized to train the design, and the model's abilities. [225] It acknowledged a few of its drawbacks, consisting of struggles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", however kept in mind that they must have been cherry-picked and may not represent Sora's [typical output](https://studiostilesandtotalfitness.com). [225]
<br>Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have revealed substantial interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's capability to generate reasonable video from text descriptions, citing its potential to change storytelling and material creation. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to stop briefly strategies for expanding his Atlanta-based movie studio. [227]
<br>Speech-to-text<br>
<br>Whisper<br>
<br>Released in 2022, Whisper is a general-purpose speech acknowledgment design. [228] It is [trained](http://sdongha.com) on a big dataset of diverse audio and is likewise a multi-task model that can carry out multilingual speech acknowledgment in addition to speech translation and language recognition. [229]
<br>Music generation<br>
<br>MuseNet<br>
<br>Released in 2019, MuseNet is a deep neural net trained to forecast subsequent musical notes in [MIDI music](https://www.matesroom.com) files. It can [produce songs](https://myclassictv.com) with 10 [instruments](http://211.119.124.1103000) in 15 styles. According to The Verge, a tune created by MuseNet tends to begin fairly however then fall under mayhem the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were [utilized](https://git.thatsverys.us) as early as 2020 for the web psychological thriller Ben Drowned to produce music for the titular character. [232] [233]
<br>Jukebox<br>
<br>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 bit of lyrics and outputs tune samples. OpenAI specified the tunes "show local musical coherence [and] follow standard chord patterns" but acknowledged that the songs lack "familiar bigger musical structures such as choruses that duplicate" which "there is a substantial gap" in between Jukebox and human-generated music. The Verge specified "It's technologically outstanding, even if the results sound like mushy versions of songs that may feel familiar", while Business Insider specified "remarkably, some of the resulting songs are catchy and sound legitimate". [234] [235] [236]
<br>Interface<br>
<br>Debate Game<br>
<br>In 2018, [OpenAI introduced](https://www.grandtribunal.org) the Debate Game, which teaches devices to dispute toy problems in front of a human judge. The purpose is to research whether such a technique may help in auditing [AI](http://missima.co.kr) decisions and in establishing explainable [AI](http://59.57.4.66:3000). [237] [238]
<br>Microscope<br>
<br>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 developed to examine the features that form inside these neural networks easily. The designs consisted of are AlexNet, VGG-19, different variations of Inception, and various variations of [CLIP Resnet](http://git.lovestrong.top). [241]
<br>ChatGPT<br>
<br>Launched in November 2022, ChatGPT is an expert system [tool developed](https://vids.nickivey.com) on top of GPT-3 that offers a conversational interface that permits users to ask [questions](https://www.kukustream.com) in natural language. The system then reacts with a response within seconds.<br>