molly96p95951/oddmate
1
0
Code Issues Actions Packages Projects Wiki

Add The Verge Stated It's Technologically Impressive

Molly Gowrie 2025-02-17 12:02:49 +08:00
commit bf42663b02
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 designed to [facilitate](http://59.110.68.1623000) the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are specified in [AI](https://jobs.sudburychamber.ca) research study, making released research study more quickly reproducible [24] [144] while offering users with a simple user interface for interacting with these environments. In 2022, new advancements of Gym have actually been moved to the library Gymnasium. [145] [146]
<br>Gym Retro<br>
<br>Released in 2018, Gym Retro is a platform for support knowing (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research [focused](http://60.209.125.23820010) mainly on [enhancing representatives](https://i10audio.com) to resolve single tasks. Gym Retro gives the ability to generalize between games with comparable concepts but various looks.<br>
<br>RoboSumo<br>
<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially lack understanding of how to even walk, however are given the goals of finding out to move and to press the opposing agent out of the ring. [148] Through this adversarial learning procedure, the representatives find out how to adapt to altering conditions. When an agent is then gotten rid of from this virtual environment and put in a brand-new virtual environment with high winds, the agent braces to remain upright, recommending it had found out how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that [competition](https://git.runsimon.com) in between agents might develop an intelligence "arms race" that could increase a representative's ability to work even outside the context of the competitors. [148]
<br>OpenAI 5<br>
<br>OpenAI Five is a team of 5 OpenAI-curated bots used in the [competitive five-on-five](https://codes.tools.asitavsen.com) computer game Dota 2, that discover to play against human gamers at a high ability level entirely through experimental algorithms. Before becoming a team of 5, the very first public demonstration occurred at The International 2017, the annual best champion tournament for the video game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for two weeks of genuine time, and that the knowing software was an action in the direction of developing software application that can handle complex jobs like a cosmetic surgeon. [152] [153] The system utilizes a kind of support learning, as the bots discover 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]
<br>By June 2018, the capability of the bots broadened to play together as a complete group of 5, and they were able to defeat teams of amateur and [semi-professional players](http://freeflashgamesnow.com). [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert players, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public appearance came later on that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games. [165]
<br>OpenAI 5's mechanisms in Dota 2's bot gamer reveals the difficulties of [AI](https://scm.fornaxian.tech) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has shown making use of deep support knowing (DRL) representatives to [attain superhuman](https://gitea.marvinronk.com) competence in Dota 2 matches. [166]
<br>Dactyl<br>
<br>Developed in 2018, Dactyl uses machine discovering to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It discovers completely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI took on the item orientation issue by using domain randomization, a simulation technique which exposes the learner to a variety of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having cams, also has RGB video cameras to enable the robot to manipulate an approximate item by seeing it. In 2018, OpenAI revealed that the system was able to [control](http://tobang-bangsu.co.kr) a cube and an octagonal prism. [168]
<br>In 2019, OpenAI showed that Dactyl might resolve a Rubik's Cube. The robotic was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by enhancing the toughness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation method of creating progressively more hard environments. ADR varies from manual domain randomization by not needing a human to define randomization ranges. [169]
<br>API<br>
<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://akinsemployment.ca) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](https://video.disneyemployees.net) job". [170] [171]
<br>Text generation<br>
<br>The company 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 design was written by Alec Radford and his coworkers, and released in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative design of language could obtain world understanding and process long-range dependences by pre-training on a diverse corpus with long stretches of contiguous text.<br>
<br>GPT-2<br>
<br>Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language model and [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:GemmaJenson1) the follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just minimal demonstrative variations initially launched to the public. The complete variation of GPT-2 was not instantly released due to concern about potential misuse, including applications for composing fake news. [174] Some professionals revealed uncertainty that GPT-2 [positioned](https://navar.live) a significant risk.<br>
<br>In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to identify "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 hush all other speech and be difficult to filter". [176] In November 2019, OpenAI released the complete variation 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]
<br>GPT-2's authors argue unsupervised language designs to be general-purpose learners, shown by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further 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 a minimum of 3 upvotes. It avoids certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters by encoding both private characters and [multiple-character](https://www.ejobsboard.com) tokens. [181]
<br>GPT-3<br>
<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion specifications, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 designs with as couple of as 125 million specifications were likewise trained). [186]
<br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" tasks and might generalize the function of a single input-output pair. The GPT-3 release paper gave examples of translation and [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11860868) cross-linguistic transfer learning between English and Romanian, and in between English and German. [184]
<br>GPT-3 significantly enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 required a number of thousand petaflop/s-days [b] of calculate, [compared](http://kandan.net) to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately launched to the public for issues of possible abuse, although OpenAI prepared to permit 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 certified specifically to Microsoft. [190] [191]
<br>Codex<br>
<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://101.42.248.108:3000) powering the [code autocompletion](https://tube.denthubs.com) tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the model can develop working code in over a dozen programs languages, many efficiently in Python. [192]
<br>Several concerns with glitches, design flaws and security vulnerabilities were mentioned. [195] [196]
<br>GitHub Copilot has actually been accused of producing copyrighted code, with no author attribution or license. [197]
<br>OpenAI revealed that they would cease assistance for Codex API on March 23, 2023. [198]
<br>GPT-4<br>
<br>On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), [efficient](http://git.emagenic.cl) in accepting text or image inputs. [199] They revealed that the upgraded innovation passed a simulated law school bar examination with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, analyze or create approximately 25,000 words of text, and write code in all major shows [languages](http://123.56.247.1933000). [200]
<br>Observers reported that the version of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 [retained](https://www.teamswedenclub.com) some of the issues with earlier revisions. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has decreased to reveal various technical details and data about GPT-4, such as the exact size of the model. [203]
<br>GPT-4o<br>
<br>On May 13, 2024, OpenAI announced 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 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]
<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller version 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 expects it to be particularly beneficial for enterprises, startups and developers looking for to automate services with [AI](https://hugoooo.com) representatives. [208]
<br>o1<br>
<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have actually been designed to take more time to consider their reactions, causing greater accuracy. These designs are especially effective in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was replaced by o1. [211]
<br>o3<br>
<br>On December 20, 2024, OpenAI unveiled o3, the follower of the o1 thinking design. OpenAI likewise unveiled o3-mini, a lighter and [quicker variation](https://app.galaxiesunion.com) of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecommunications services [service](http://www.thynkjobs.com) [provider](https://gitea.mpc-web.jp) O2. [215]
<br>Deep research<br>
<br>Deep research study is an [agent established](https://git.ddswd.de) by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform extensive web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [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 analyze the semantic similarity in 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 design that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to analyze natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can create images of reasonable things ("a stained-glass window with an image of a blue strawberry") in addition to objects that do not exist in reality ("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 model with more [realistic outcomes](https://coding.activcount.info). [219] In December 2022, OpenAI published on GitHub software for Point-E, a new rudimentary system for converting a text description into a 3-dimensional design. [220]
<br>DALL-E 3<br>
<br>In September 2023, OpenAI revealed DALL-E 3, a more powerful design better able to produce images from complicated descriptions without manual prompt engineering and render complex 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 short detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.<br>
<br>Sora's advancement team named it after the [Japanese](https://moojijobs.com) word for "sky", to signify its "endless imaginative capacity". [223] Sora's technology is an adaptation of the innovation behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos certified 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](https://love63.ru) videos to the public on February 15, 2024, [stating](https://kod.pardus.org.tr) that it might create videos as much as one minute long. It likewise shared a technical report highlighting the approaches used to train the design, and the design's abilities. [225] It acknowledged some of its imperfections, consisting of battles replicating [complicated physics](https://www.cupidhive.com). [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "remarkable", however noted that they need to have been [cherry-picked](https://okk-shop.com) and may not represent Sora's typical output. [225]
<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, significant entertainment-industry figures have actually revealed significant interest in the [innovation's capacity](https://git.camus.cat). In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's capability to produce practical video from text descriptions, citing its prospective to transform storytelling and material development. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to pause prepare 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 on a large dataset of diverse audio and is likewise a multi-task design that can perform multilingual speech recognition as well as 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 anticipate subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 styles. According to The Verge, a song produced by MuseNet tends to begin fairly but then fall under turmoil the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were used as early as 2020 for the web mental thriller Ben Drowned to develop music for the titular character. [232] [233]
<br>Jukebox<br>
<br>[Released](https://ramique.kr) in 2020, [Jukebox](https://www.ontheballpersonnel.com.au) is an open-sourced algorithm to create music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and [outputs song](http://xiaomu-student.xuetangx.com) samples. OpenAI specified the songs "reveal regional musical coherence [and] follow standard chord patterns" but acknowledged that the songs do not have "familiar bigger musical structures such as choruses that duplicate" and that "there is a significant space" in between Jukebox and human-generated music. The Verge specified "It's technologically impressive, even if the results seem like mushy variations of tunes that might feel familiar", while Business Insider mentioned "surprisingly, a few of the resulting songs are catchy and sound genuine". [234] [235] [236]
<br>User user interfaces<br>
<br>Debate Game<br>
<br>In 2018, OpenAI launched the Debate Game, which teaches makers to dispute toy issues in front of a human judge. The purpose is to research study whether such an approach might help in [auditing](https://code.dev.beejee.org) [AI](https://git.paaschburg.info) decisions and in establishing explainable [AI](http://git.qwerin.cz). [237] [238]
<br>Microscope<br>
<br>Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and nerve cell of eight neural network designs which are frequently studied in interpretability. [240] Microscope was created to analyze the features that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, various variations of Inception, and different variations of CLIP Resnet. [241]
<br>ChatGPT<br>
<br>Launched in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that supplies a conversational user interface that enables users to ask concerns in natural language. The system then reacts with an answer within seconds.<br>