commit ae6d3db56b4c284dd4daa14b7ffd4a794e4f88ab Author: serenaezx8288 Date: Thu Feb 6 23:10:03 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..bb8f585 --- /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 designed to help with the advancement of reinforcement knowing algorithms. It aimed to [standardize](https://placementug.com) how [environments](https://git.nosharpdistinction.com) are defined in [AI](http://121.36.27.6:3000) research study, making released research more easily reproducible [24] [144] while offering users with a simple user interface for communicating with these environments. In 2022, new advancements 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 [reinforcement knowing](http://sujongsa.net) (RL) research on computer game [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing representatives to solve single tasks. Gym Retro offers the ability to generalize between video games with comparable ideas but different looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially lack understanding of how to even walk, but are provided the goals of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial learning process, the agents learn how to adjust to changing conditions. When a representative is then removed from this virtual environment and placed in a new [virtual environment](https://www.joinyfy.com) with high winds, the representative braces to remain upright, recommending it had actually found out how to [balance](http://49.235.147.883000) in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between agents might develop an intelligence "arms race" that could increase an agent's capability to work even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that find out to play against human players at a high skill level entirely through experimental algorithms. Before becoming a team of 5, the first public demonstration happened at The International 2017, the annual premiere championship competition for the video game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live one-on-one 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 actual time, and that the learning software was an action in the direction of [creating software](https://www.joboont.in) that can deal with intricate jobs like a surgeon. [152] [153] The system utilizes a kind of reinforcement learning, as the bots learn over 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 expanded to play together as a full team of 5, and they had the ability to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against professional gamers, but ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:Margareta19E) the ruling 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 that month, where they played in 42,729 overall video 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 shows the obstacles of [AI](https://3.123.89.178) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has actually demonstrated making use of deep support learning (DRL) agents to attain superhuman proficiency in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses [device discovering](http://gitlab.rainh.top) to train a Shadow Hand, a human-like robot hand, to control physical items. [167] It discovers entirely in [simulation utilizing](https://findgovtsjob.com) the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the item orientation problem by using domain randomization, a simulation approach which exposes the learner to a variety of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking video cameras, also has RGB video cameras to allow the robotic to control an approximate things by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robot had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce intricate [physics](https://sowjobs.com) that is harder to design. OpenAI did this by improving the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of generating progressively harder environments. 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://www.k4be.eu) models developed by OpenAI" to let designers contact it for "any English language [AI](http://gitlab.digital-work.cn) job". [170] [171] +
Text generation
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The company has actually promoted generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("GPT-1")
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The original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his associates, and released in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world understanding and procedure long-range dependencies 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 2 ("GPT-2") is a without supervision transformer language model and the successor to [OpenAI's original](https://git.hackercan.dev) GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative [versions](https://git.opskube.com) at first launched to the public. The complete version of GPT-2 was not immediately launched due to issue about prospective abuse, including applications for writing phony news. [174] Some professionals expressed uncertainty that GPT-2 posed a substantial danger.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to [discover](https://tubechretien.com) "neural fake news". [175] Other researchers, such as Jeremy Howard, alerted of "the innovation to absolutely 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 total version of the GPT-2 language design. [177] Several websites host interactive presentations of various circumstances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue without supervision language models to be general-purpose learners, highlighted by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not further trained on any [task-specific input-output](http://bammada.co.kr) examples).
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The corpus it was trained on, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:HunterY514213) called WebText, contains somewhat 40 gigabytes of text from [URLs shared](https://bytevidmusic.com) in Reddit [submissions](http://47.75.109.82) with at least 3 upvotes. It avoids certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This [permits representing](http://175.24.174.1733000) any string of characters by encoding both individual 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 follower to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as few as 125 million criteria were also trained). [186] +
OpenAI stated that GPT-3 prospered at certain "meta-learning" tasks and [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:FlorianHoutz6) could generalize the purpose of a [single input-output](https://freakish.life) pair. The GPT-3 release paper gave examples of [translation](http://tools.refinecolor.com) and cross-linguistic transfer knowing between English and Romanian, and in between English and German. [184] +
GPT-3 drastically enhanced benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or encountering the essential ability constraints of predictive language designs. [187] Pre-training GPT-3 [required](https://realhindu.in) several thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the complete 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 planned to permit gain access to through a paid cloud API after a two-month totally free private beta that started in June 2020. [170] [189] +
On September 23, [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:MichaelCrocker0) 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](http://47.107.29.61:3000) powering the code autocompletion [tool GitHub](https://www.fionapremium.com) Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can develop working code in over a lots programs languages, a lot of efficiently in Python. [192] +
Several concerns with problems, [style defects](https://abcdsuppermarket.com) and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been implicated of [producing copyrighted](http://2.47.57.152) code, without any author attribution or license. [197] +
OpenAI announced that they would [cease support](http://git.datanest.gluc.ch) 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), efficient in accepting text or image inputs. [199] They announced that the upgraded technology passed a simulated law [school bar](http://www.hydrionlab.com) examination 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 could also check out, examine or [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:DannielleDixson) produce as much as 25,000 words of text, and compose code in all significant shows languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an [enhancement](https://pattonlabs.com) on the previous GPT-3.5-based version, with the caution that GPT-4 retained some of the problems with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose various technical details and statistics about GPT-4, such as the exact size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and [released](http://139.9.50.1633000) GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained advanced 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 interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:FidelBatt531106) $15 respectively for GPT-4o. OpenAI anticipates it to be especially useful for business, start-ups and developers seeking to automate services with [AI](http://demo.qkseo.in) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have actually been created to take more time to think of their reactions, resulting in greater precision. These models are especially reliable 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 revealed o3, the follower of the o1 reasoning model. OpenAI also revealed o3-mini, a lighter and much faster variation of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are [testing](http://durfee.mycrestron.com3000) o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these designs. [214] The model is called o3 rather than o2 to avoid confusion with telecoms providers O2. [215] +
Deep research study
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Deep research study is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform substantial web surfing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools enabled, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) standard. [120] +
Image classification
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CLIP
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[Revealed](https://www.calogis.com) in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to analyze the semantic resemblance 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 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 shaped like a pentagon" or "an isometric view of a sad capybara") and generate matching images. It can create pictures of practical objects ("a stained-glass window with an image of a blue strawberry") as well as objects 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 announced DALL-E 2, an updated variation of the design with more practical results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new fundamental system for transforming a text description into a 3-dimensional design. [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more [effective model](http://59.57.4.663000) much better able to create images from complicated descriptions without manual timely engineering and render complex details like hands and text. [221] It was released to the public as a ChatGPT Plus function in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video design that can generate videos based on brief detailed prompts [223] as well as extend existing videos forwards or backwards in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of produced videos is unknown.
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Sora's advancement team called it after the Japanese word for "sky", to symbolize its "unlimited imaginative potential". [223] Sora's innovation is an adjustment of the innovation behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system [utilizing](http://124.221.76.2813000) publicly-available videos as well as copyrighted videos licensed for that purpose, however did not reveal the number or the precise sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the public on February 15, 2024, specifying that it might produce videos approximately one minute long. It also shared a technical report highlighting the techniques used to train the model, and the [model's abilities](https://sapjobsindia.com). [225] It acknowledged a few of its imperfections, consisting of battles mimicing complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the [presentation videos](https://callingirls.com) "remarkable", but noted that they must have been cherry-picked and may not represent Sora's normal output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, [noteworthy entertainment-industry](https://rapid.tube) figures have revealed significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's ability to create reasonable video from text descriptions, citing its possible to reinvent storytelling and material production. He said that his enjoyment about Sora's possibilities was so strong that he had decided to stop briefly prepare for broadening his Atlanta-based motion picture 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 large dataset of varied audio and is likewise a multi-task design that can carry out multilingual speech acknowledgment in addition to 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 forecast subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 designs. According to The Verge, a song created by MuseNet tends to start fairly but then fall under mayhem the longer it plays. [230] [231] In pop culture, initial applications of this tool were [utilized](http://119.3.9.593000) as early as 2020 for the internet mental thriller Ben Drowned 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, the system accepts a category, artist, and a snippet of lyrics and outputs song samples. OpenAI specified the songs "show regional musical coherence [and] follow conventional chord patterns" but acknowledged that the songs do not have "familiar larger musical structures such as choruses that duplicate" which "there is a significant space" between Jukebox and human-generated music. The Verge specified "It's highly impressive, even if the outcomes sound like mushy versions of songs that might feel familiar", while Business Insider [mentioned](http://hammer.x0.to) "surprisingly, some of the resulting songs are appealing and sound legitimate". [234] [235] [236] +
User user interfaces
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Debate Game
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In 2018, OpenAI launched the Debate Game, which teaches devices to discuss toy problems in front of a human judge. The purpose is to research study whether such an approach may assist in auditing [AI](http://1.14.105.160:9211) decisions and in establishing explainable [AI](https://axc.duckdns.org:8091). [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 eight neural network designs which are typically studied in interpretability. [240] Microscope was created to examine the features that form inside these easily. The designs included are AlexNet, [fishtanklive.wiki](https://fishtanklive.wiki/User:GiuseppeXve) VGG-19, different variations of Inception, and different variations of [CLIP Resnet](https://trackrecord.id). [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an artificial intelligence tool developed on top of GPT-3 that provides a conversational interface that enables users to ask questions in natural language. The system then responds with an answer within seconds.
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