commit a2d47210e073a1b9f7b4864abfb3708e11f92287 Author: candydpr071715 Date: Sat Apr 5 20:07:20 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..a1d14dc --- /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 learning algorithms. It aimed to standardize how environments are specified in [AI](http://211.91.63.144:8088) research, making released research more quickly reproducible [24] [144] while offering users with a basic interface for engaging with these environments. In 2022, brand-new developments of Gym have been transferred to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support learning (RL) research on video games [147] using RL algorithms and study generalization. Prior RL research study focused mainly on optimizing agents to fix single jobs. Gym Retro gives the capability to generalize in between video games with comparable concepts but various appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot representatives at first do not have knowledge of how to even walk, but are provided the goals of [discovering](http://82.19.55.40443) to move and to push the opposing representative out of the ring. [148] Through this adversarial learning procedure, the representatives find out how to adapt to [changing conditions](http://zerovalueentertainment.com3000). When an agent is then removed from this virtual environment and put in a new virtual environment with high winds, the agent braces to remain upright, recommending it had learned 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 a representative's capability to work even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a team 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 totally through experimental algorithms. Before becoming a group of 5, the very first public demonstration took place at The [International](http://211.91.63.1448088) 2017, the annual best champion competition for the game, where Dendi, an expert Ukrainian player, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually learned by playing against itself for two weeks of actual time, and that the knowing software application was an action in the instructions of developing software that can handle complex tasks like a surgeon. [152] [153] The system utilizes a type of reinforcement learning, as the bots learn in 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 objectives. [154] [155] [156] +
By June 2018, the capability 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 gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against [professional](https://ddsbyowner.com) gamers, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs of the video game at the time, 2:0 in a live exhibit 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 games. [165] +
OpenAI 5's mechanisms in Dota 2's bot player reveals the challenges of [AI](http://doosung1.co.kr) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated the usage of deep support knowing (DRL) representatives to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes machine finding out to train a Shadow Hand, a human-like robotic hand, to control physical objects. [167] It learns totally in simulation [utilizing](http://clipang.com) the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the object orientation problem by utilizing domain randomization, a simulation approach which exposes the student to a range of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having motion tracking electronic cameras, also has RGB cams to permit the robot to manipulate an arbitrary things by seeing it. In 2018, OpenAI showed that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might fix a Rubik's Cube. The robotic had the [ability](http://47.108.69.3310888) to solve the puzzle 60% of the time. [Objects](https://www.cbmedics.com) like the Rubik's Cube introduce intricate physics that is harder to design. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of creating gradually harder environments. ADR differs from manual domain randomization by not requiring a human to specify randomization varieties. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://iesoundtrack.tv) models established by OpenAI" to let developers get in touch with it for "any English language [AI](https://git.teygaming.com) task". [170] [171] +
Text generation
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The business has popularized generative pretrained transformers (GPT). [172] +
OpenAI's original 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 coworkers, and released in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative model of language might obtain world knowledge and process long-range dependences by pre-training on a diverse corpus with long stretches of adjoining text.
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GPT-2
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Generative [Pre-trained Transformer](https://www.kritterklub.com) 2 ("GPT-2") is an [unsupervised transformer](https://lgmtech.co.uk) language model and the successor to [OpenAI's initial](http://47.95.216.250) GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative variations initially released to the public. The complete version of GPT-2 was not right away released due to concern about potential abuse, consisting of applications for writing fake news. [174] Some professionals expressed uncertainty that GPT-2 postured a considerable risk.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to detect "neural phony news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation to completely 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 complete variation of the GPT-2 language design. [177] Several websites host interactive presentations of different 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, illustrated by GPT-2 attaining state-of-the-art accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not more 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](https://bebebi.com) with at least 3 upvotes. It prevents certain issues 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 a without supervision transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 contained 175 billion specifications, [184] 2 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 parameters were likewise trained). [186] +
OpenAI stated that GPT-3 succeeded at certain "meta-learning" tasks and could generalize the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning between English and Romanian, and in between English and German. [184] +
GPT-3 dramatically improved benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models might be approaching or coming across the fundamental capability constraints of predictive language models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of calculate, [compared](http://194.87.97.823000) to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately [released](https://git.liubin.name) to the public for concerns of possible abuse, although OpenAI prepared to permit gain access to through a paid cloud API after a two-month complimentary personal beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified solely to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has actually furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://git.lovestrong.top) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can produce working code in over a dozen programming languages, a lot of effectively in Python. [192] +
Several issues with glitches, style flaws and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has actually been implicated of producing copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would [cease support](http://git.lovestrong.top) 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](http://31.184.254.1768078) or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar exam with a score around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise read, analyze or produce approximately 25,000 words of text, and write code in all major programming [languages](https://www.mgtow.tv). [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has actually declined to expose different technical details and stats about GPT-4, such as the precise size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI announced and released GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained cutting edge lead to voice, multilingual, and vision standards, setting brand-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 variation 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 especially useful for business, startups and developers seeking to automate services with [AI](https://www.opentx.cz) representatives. [208] +
o1
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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 actions, causing greater precision. These designs are especially reliable in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was [changed](https://manpoweradvisors.com) by o1. [211] +
o3
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On December 20, 2024, OpenAI unveiled o3, the successor of the o1 reasoning model. OpenAI also revealed o3-mini, a lighter and quicker version of OpenAI o3. As of 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, safety and security researchers had the chance to obtain early access to these models. [214] The design is called o3 rather than o2 to avoid confusion with telecommunications providers O2. [215] +
Deep research
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Deep research is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of [OpenAI's](https://estekhdam.in) o3 design to carry out comprehensive web browsing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools enabled, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120] +
Image category
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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 examine the semantic similarity between text and images. It can especially be used 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 model that [produces](http://47.97.178.182) images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to [analyze natural](https://foke.chat) language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can develop pictures of realistic things ("a stained-glass window with an image of a blue strawberry") in addition to items that do not exist in reality ("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](https://git.cavemanon.xyz) version of the model with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new fundamental system for [converting](https://redsocial.cl) a text description into a 3[-dimensional design](https://www.istorya.net). [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more powerful model much better able to generate images from complicated descriptions without manual timely engineering and render complicated details like hands and text. [221] It was released to the 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 model that can generate videos based on short detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The maximal length of generated videos is unknown.
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Sora's advancement team called it after the Japanese word for "sky", to symbolize its "limitless creative potential". [223] Sora's technology is an adaptation of the technology behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos [licensed](https://xotube.com) for that purpose, however did not expose the number or the exact sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it could produce videos approximately one minute long. It likewise shared a technical report highlighting the methods used to train the model, and the model's capabilities. [225] It acknowledged some of its drawbacks, consisting of struggles simulating complex physics. [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 common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have revealed considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's capability to create [reasonable](https://jollyday.club) video from text descriptions, mentioning its possible to reinvent storytelling and material development. He said that his about Sora's possibilities was so strong that he had decided to pause prepare for broadening 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 diverse audio and is likewise a multi-task model that can carry out multilingual speech acknowledgment along with speech translation and language recognition. [229] +
Music generation
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MuseNet
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Released in 2019, [MuseNet](https://wiki.sublab.net) is a [deep neural](https://www.roednetwork.com) 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 song produced by MuseNet tends to begin fairly but then fall into mayhem the longer it plays. [230] [231] In pop culture, initial applications of this tool were used as early as 2020 for the web mental thriller Ben [Drowned](http://221.238.85.747000) to produce 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, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:FelishaJoy30) the system accepts a category, artist, and a bit of lyrics and outputs song samples. OpenAI specified the songs "reveal local musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" which "there is a significant gap" between Jukebox and human-generated music. The Verge stated "It's highly outstanding, even if the results sound like mushy variations of songs that might feel familiar", while Business Insider mentioned "surprisingly, some of the resulting songs are catchy and sound legitimate". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI introduced the Debate Game, which teaches machines to discuss toy problems in front of a human judge. The function is to research whether such a method might help in auditing [AI](https://code.jigmedatse.com) decisions and in establishing explainable [AI](https://18plus.fun). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of eight neural network designs which are often studied in interpretability. [240] Microscope was produced to analyze the features that form inside these neural networks easily. The models included are AlexNet, VGG-19, various variations of Inception, and various variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system [tool developed](https://coptr.digipres.org) on top of GPT-3 that supplies a conversational user interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.
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