commit ed868c70f43a1b255a1781b456058a84c86ce168 Author: edith476186982 Date: Sun Apr 13 07:11:32 2025 +0800 Add 'The Verge Stated It's Technologically Impressive' 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..59fb0d2 --- /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 help with the advancement of support knowing [algorithms](https://yeetube.com). It aimed to standardize how environments are [defined](https://eelam.tv) in [AI](https://git.getmind.cn) research study, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:MathewCutlack) making published research study more easily reproducible [24] [144] while supplying users with a basic interface for engaging with these environments. In 2022, new developments of Gym have been relocated to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a for reinforcement knowing (RL) research on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on optimizing representatives to fix single tasks. Gym Retro provides the capability to generalize between video 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 representatives initially do not have understanding of how to even stroll, however are provided the goals of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the agents find out how to adapt to changing conditions. When an agent is then eliminated from this virtual environment and put in a new [virtual](https://www.heesah.com) environment with high winds, the agent braces to remain upright, suggesting it had learned how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives could [produce](https://drapia.org) an intelligence "arms race" that might [increase](https://work.melcogames.com) a representative's capability to operate even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a team of 5 OpenAI-curated bots utilized in the [competitive five-on-five](http://140.143.226.1) computer game Dota 2, that learn to play against human gamers at a high skill level totally through experimental [algorithms](https://gitea.sitelease.ca3000). Before ending up being a group of 5, the very first public demonstration occurred at The International 2017, the yearly premiere championship tournament for the game, where Dendi, an [expert Ukrainian](https://git.bugi.si) gamer, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually found out by playing against itself for 2 weeks of real time, and that the knowing software application was an action in the [instructions](https://repo.maum.in) of producing software application that can deal with intricate jobs like a surgeon. [152] [153] The system utilizes a form of support learning, as the bots find out 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 broadened to play together as a complete team of 5, and they were able to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against expert gamers, but ended 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 [exhibition match](http://59.56.92.3413000) in San Francisco. [163] [164] The bots' final public look came later on that month, where they played in 42,729 total video games in a four-day open online competition, winning 99.4% of those video games. [165] +
OpenAI 5's systems in Dota 2's bot gamer reveals the difficulties of [AI](http://www.colegio-sanandres.cl) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has shown making use of deep reinforcement knowing (DRL) agents to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes device learning to train a Shadow Hand, a human-like robot hand, to manipulate physical objects. [167] It learns entirely in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation issue by utilizing domain randomization, a simulation approach which exposes the learner to a range of experiences instead of attempting to fit to [reality](https://cheapshared.com). The set-up for Dactyl, aside from having motion tracking electronic cameras, likewise has RGB video cameras to allow the robot to manipulate an approximate item by seeing it. In 2018, OpenAI showed that the system had the ability to [manipulate](https://optimaplacement.com) a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might solve a Rubik's Cube. The robotic had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to model. OpenAI did this by enhancing the toughness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation method of creating gradually harder [environments](https://community.scriptstribe.com). ADR varies from manual domain randomization by not requiring 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 brand-new [AI](https://gitea.dusays.com) models established by OpenAI" to let developers get in touch with it for "any English language [AI](https://eelam.tv) job". [170] [171] +
Text generation
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The company has actually popularized generative pretrained transformers (GPT). [172] +
[OpenAI's initial](http://krasnoselka.od.ua) GPT model ("GPT-1")
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The initial paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his associates, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world understanding and procedure long-range dependences by pre-training on a diverse corpus with long stretches of contiguous text.
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GPT-2
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Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language design and the successor to OpenAI's initial GPT model ("GPT-1"). GPT-2 was [revealed](https://quickservicesrecruits.com) in February 2019, with just minimal demonstrative variations initially launched to the general public. The full version of GPT-2 was not instantly launched due to issue about possible misuse, consisting of applications for writing fake news. [174] Some specialists expressed uncertainty that GPT-2 presented a considerable hazard.
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In action to GPT-2, the Allen Institute for Artificial Intelligence [responded](https://droidt99.com) with a tool to discover "neural fake news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to completely 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 released the total version of the GPT-2 language design. [177] Several websites host interactive presentations of different instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being watched language designs to be general-purpose students, shown by GPT-2 attaining cutting edge accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not additional trained on any [task-specific input-output](https://www.muslimtube.com) 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 at least 3 upvotes. It prevents certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both specific 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 an unsupervised transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude larger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as few as 125 million [specifications](https://mulaybusiness.com) were likewise trained). [186] +
OpenAI stated that GPT-3 succeeded 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 between English and Romanian, and between [English](http://24insite.com) and German. [184] +
GPT-3 dramatically improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs 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 to tens 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 general public for issues of possible abuse, although OpenAI planned to allow gain access to through a paid cloud API after a two-month totally 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 in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://play.sarkiniyazdir.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was [released](https://www.h0sting.org) in private beta. [194] According to OpenAI, the model can produce working code in over a lots programs languages, most efficiently in Python. [192] +
Several concerns with problems, design flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been accused of [discharging copyrighted](https://www.xcoder.one) code, with no author attribution or license. [197] +
OpenAI revealed that they would stop assistance for 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), capable of accepting text or image inputs. [199] They revealed that the updated technology 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 read, analyze or create as much as 25,000 words of text, and write code in all major programs languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained some of the problems with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on [ChatGPT](http://8.137.103.2213000). [202] OpenAI has decreased to reveal numerous technical details and statistics about GPT-4, such as the accurate size of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and [produce](https://seconddialog.com) text, images and audio. [204] GPT-4o attained advanced 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 launched GPT-4o mini, a smaller 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](https://squishmallowswiki.com) for business, start-ups and designers seeking to automate services with [AI](http://www.engel-und-waisen.de) [representatives](https://www.lotusprotechnologies.com). [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have been developed to take more time to consider their actions, leading to greater precision. These designs are particularly 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 unveiled o3, the [successor](https://yeetube.com) of the o1 [reasoning model](http://christianpedia.com). OpenAI also [revealed](http://hanbitoffice.com) o3-mini, a lighter and faster version of OpenAI o3. As of December 21, 2024, this model is not available for public use. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, safety 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 telecoms companies O2. [215] +
Deep research
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Deep research study is a representative established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to carry out extensive web browsing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools made it possible for, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] +
Image category
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CLIP
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Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to examine the semantic resemblance in between text and images. It can notably be used for image category. [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 utilizes a 12-billion-parameter version of GPT-3 to translate natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of an unfortunate capybara") and produce matching images. It can create pictures of practical items ("a stained-glass window with an image of a blue strawberry") along with items that do not exist in truth ("a cube with the texture of a porcupine"). As of 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 [updated variation](https://peopleworknow.com) of the model with more sensible outcomes. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a new basic system for transforming a text description into a 3-dimensional model. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, a more effective design better able to produce images from complex descriptions without manual timely engineering and render intricate details like hands and text. [221] It was released to the general public as a ChatGPT Plus [function](https://www.drawlfest.com) in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video design that can create videos based upon brief detailed prompts [223] as well as extend existing videos forwards or backwards in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of created videos is unknown.
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Sora's advancement team named it after the Japanese word for "sky", to represent its "limitless imaginative capacity". [223] [Sora's innovation](https://filmcrib.io) is an adjustment of the technology behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos [accredited](https://dongawith.com) for that purpose, but did not reveal the number or the [exact sources](https://git.saidomar.fr) of the videos. [223] +
OpenAI showed some [Sora-created high-definition](https://wik.co.kr) videos to the public on February 15, 2024, mentioning that it could produce videos up to one minute long. It likewise shared a technical report highlighting the techniques used to train the design, and the model's abilities. [225] It acknowledged some of its imperfections, consisting of struggles simulating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", but kept in mind that they need to have been cherry-picked and may not represent Sora's normal output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, notable entertainment-industry figures have revealed considerable interest in the technology's potential. In an interview, actor/filmmaker [Tyler Perry](http://wiki.lexserve.co.ke) revealed his astonishment at the [technology's ability](https://drapia.org) to create reasonable video from text descriptions, mentioning its prospective to change storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had decided to pause prepare for expanding his Atlanta-based movie 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 on a big 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 produce songs with 10 instruments in 15 designs. According to The Verge, a tune generated by MuseNet tends to start fairly but then fall into turmoil the longer it plays. [230] [231] In popular culture, initial applications of this tool were utilized as early as 2020 for the internet 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 create music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs song [samples](https://healthcarejob.cz). OpenAI mentioned the tunes "show local musical coherence [and] follow conventional chord patterns" however acknowledged that the songs do not have "familiar bigger musical structures such as choruses that repeat" and that "there is a significant gap" between Jukebox and human-generated music. The Verge stated "It's technically outstanding, even if the outcomes seem like mushy versions of tunes that may feel familiar", while Business Insider specified "surprisingly, 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 launched the Debate Game, which teaches devices to dispute toy issues in front of a human judge. The purpose is to research whether such a technique might assist in auditing [AI](https://gitea.ruwii.com) choices and in establishing explainable [AI](https://www.freetenders.co.za). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and nerve cell of 8 neural network models which are typically studied in interpretability. [240] Microscope was created to evaluate the features that form inside these neural networks quickly. The designs consisted of are AlexNet, VGG-19, different versions of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an artificial intelligence tool built on top of GPT-3 that supplies a conversational interface that enables users to ask questions in natural language. The system then reacts with a response within seconds.
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