From 1e31dc3953b284e02d9741f335521a7b235775e8 Mon Sep 17 00:00:00 2001 From: brendaseaver3 Date: Wed, 12 Mar 2025 05:17:26 +0300 Subject: [PATCH] Add The Verge Stated It's Technologically Impressive --- ...tated-It%27s-Technologically-Impressive.md | 76 +++++++++++++++++++ 1 file changed, 76 insertions(+) create mode 100644 The-Verge-Stated-It%27s-Technologically-Impressive.md 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..7038e9f --- /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 developed](https://git.foxarmy.org) to help with the advancement of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://git.penwing.org) research, making [published](https://git.junzimu.com) research study more quickly reproducible [24] [144] while supplying users with an easy user interface for interacting with these environments. In 2022, brand-new advancements of Gym have been relocated 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] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on optimizing agents to solve single tasks. Gym Retro provides the ability to generalize between games with comparable principles but various looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially do not have [understanding](https://uconnect.ae) of how to even stroll, however are provided the goals of discovering to move and to press the opposing agent out of the ring. [148] Through this adversarial learning process, the representatives learn how to adjust to changing conditions. When an agent is then gotten rid of from this virtual environment and positioned in a new virtual environment with high winds, the representative braces to remain upright, recommending it had discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents might produce an intelligence "arms race" that might increase a [representative's ability](https://git.declic3000.com) to work even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a group 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 skill level entirely through experimental algorithms. Before ending up being a group of 5, the very first public presentation occurred at The International 2017, the yearly best championship competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually match. [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 application was a step in the direction of creating software application that can deal with complicated tasks like a cosmetic surgeon. [152] [153] The system [utilizes](https://www.social.united-tuesday.org) a form of support learning, as the bots learn gradually 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](http://128.199.125.933000) to play together as a complete group of 5, and they had the ability to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The [International](https://noinai.com) 2018, OpenAI Five played in 2 exhibit matches against expert players, however wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champions of the game at the time, 2:0 in a [live exhibition](https://ransomware.design) match in San Francisco. [163] [164] The bots' last public appearance came later that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those video games. [165] +
OpenAI 5's systems in Dota 2's bot player reveals the obstacles of [AI](https://wiki.rolandradio.net) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually shown using deep support knowing (DRL) representatives to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses device learning to train a Shadow Hand, a [human-like robot](http://h2kelim.com) hand, to manipulate physical items. [167] It finds out totally in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation issue by utilizing domain randomization, a simulation method which exposes the learner to a range of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking cams, also has RGB [video cameras](https://www.belizetalent.com) to enable the robot to control an arbitrary item by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl could solve a [Rubik's Cube](http://begild.top8418). The robot had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce [intricate physics](https://www.womplaz.com) that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation method of producing progressively harder environments. ADR varies from manual domain randomization by not needing a human to specify randomization ranges. [169] +
API
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In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](http://8.134.237.70:7999) models established by OpenAI" to let developers get in touch with it for "any English language [AI](https://git.danomer.com) job". [170] [171] +
Text generation
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The company has actually promoted generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT design ("GPT-1")
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The initial 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 site on June 11, 2018. [173] It revealed how a generative model of language might obtain world knowledge and procedure long-range dependences by pre-training on a [diverse corpus](http://e-kou.jp) with long stretches of adjoining 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 original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just limited demonstrative versions initially launched to the general public. The complete version of GPT-2 was not instantly released due to issue about possible abuse, [consisting](http://git.cqbitmap.com8001) of applications for composing fake news. [174] Some experts revealed uncertainty that GPT-2 posed a [considerable risk](http://h2kelim.com).
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In action to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural phony news". [175] Other scientists, such as Jeremy Howard, cautioned 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 impossible to filter". [176] In November 2019, OpenAI released the complete variation of the GPT-2 language model. [177] Several websites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being watched language models to be general-purpose students, illustrated by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not further 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 with at least 3 upvotes. It avoids certain problems [encoding vocabulary](https://git.guaranteedstruggle.host) with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both private 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 not being watched transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were also trained). [186] +
OpenAI specified that GPT-3 succeeded at certain "meta-learning" tasks and might generalize the function of a [single input-output](https://whoosgram.com) pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning in between English and Romanian, and between English and German. [184] +
GPT-3 considerably enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or coming across the basic capability constraints of predictive language designs. [187] Pre-training GPT-3 [required](https://mediawiki1334.00web.net) a number of 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 right away released to the general public for concerns of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a two-month complimentary private 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](https://git.pleasantprogrammer.com) of GPT-3 that has furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.viorsan.com) powering the [code autocompletion](http://58.34.54.469092) tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the design can create working code in over a lots shows languages, a lot of efficiently in Python. [192] +
Several issues with glitches, design defects and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has actually been accused of emitting copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would discontinue assistance for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the updated 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 could likewise check out, [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:MMMLeanne883075) examine or [produce](https://fondnauk.ru) approximately 25,000 words of text, and write code in all major programs languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is also capable of taking images as input on [ChatGPT](http://gnu5.hisystem.com.ar). [202] OpenAI has actually declined to reveal numerous technical details and statistics 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 launched GPT-4o, which can process and produce text, images and audio. [204] GPT-4o [attained cutting](https://tygerspace.com) edge lead to voice, multilingual, and vision criteria, setting brand-new records in audio speech acknowledgment and [translation](http://thinkwithbookmap.com). [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 released 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](https://revinr.site) to $5 and $15 respectively for GPT-4o. [OpenAI expects](http://43.143.245.1353000) it to be especially useful for business, startups and developers seeking to automate services with [AI](https://exajob.com) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been created to take more time to think about their actions, causing higher accuracy. These designs are particularly effective in science, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=12035368) coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) o1-preview was replaced by o1. [211] +
o3
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On December 20, 2024, OpenAI unveiled o3, the successor of the o1 thinking model. OpenAI likewise unveiled o3-mini, a lighter and quicker variation of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, safety and [security researchers](http://gitlab.flyingmonkey.cn8929) had the chance to obtain early access to these designs. [214] The model is called o3 instead of o2 to avoid confusion with telecommunications companies O2. [215] +
Deep research
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Deep research study is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out extensive web browsing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools allowed, it reached an accuracy 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 model that is trained to [evaluate](http://git.hnits360.com) 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 design that produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version 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 produce matching images. It can develop pictures of practical items ("a stained-glass window with an image of a blue strawberry") in addition to objects 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 upgraded variation of the design with more realistic results. [219] In December 2022, [OpenAI published](http://117.72.17.1323000) on GitHub software application for Point-E, a brand-new basic 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 [powerful model](https://git.ffho.net) much better able to create images from complex descriptions without manual timely engineering and render intricate details like hands and text. [221] It was launched to the general 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 upon brief detailed triggers [223] as well as extend existing videos forwards or backwards in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of produced videos is unidentified.
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Sora's advancement team named it after the Japanese word for "sky", to signify its "unlimited innovative capacity". [223] Sora's innovation is an adaptation of the innovation behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos as well as copyrighted videos certified for that purpose, but did not expose the number or the exact sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the public on February 15, 2024, stating that it might generate videos up to one minute long. It also shared a technical report highlighting the methods used to train the design, and the model's abilities. [225] It acknowledged a few of its drawbacks, including battles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", but noted that they must have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demonstration, notable entertainment-industry figures have actually revealed considerable interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's ability to generate sensible video from text descriptions, mentioning its prospective to transform storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had actually decided to stop briefly strategies for expanding his Atlanta-based film studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, Whisper is a general-purpose speech acknowledgment design. [228] It is trained on a large dataset of diverse audio and is also a [multi-task design](https://gitea.v-box.cn) that can perform multilingual [speech acknowledgment](https://rugraf.ru) 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 predict subsequent musical notes in MIDI music files. It can create tunes with 10 in 15 styles. According to The Verge, a song created by MuseNet tends to start fairly but then fall under chaos the longer it plays. [230] [231] In popular culture, initial applications of this tool were used as early as 2020 for the web psychological 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 genre, artist, and a [snippet](https://jp.harmonymart.in) of lyrics and outputs tune samples. OpenAI stated the tunes "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the songs lack "familiar bigger musical structures such as choruses that duplicate" and that "there is a significant gap" in between Jukebox and human-generated music. The Verge stated "It's highly remarkable, even if the outcomes seem like mushy variations of songs that might feel familiar", while Business Insider specified "remarkably, a few of the resulting tunes are appealing 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 problems in front of a human judge. The purpose is to research study whether such a method might assist in auditing [AI](https://ransomware.design) choices and in establishing explainable [AI](https://stationeers-wiki.com). [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 models which are frequently studied in interpretability. [240] Microscope was created to analyze the features that form inside these neural networks quickly. The models included are AlexNet, VGG-19, different variations of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system tool built on top of GPT-3 that offers a conversational [interface](https://tagreba.org) that permits users to ask questions in [natural language](http://xingyunyi.cn3000). The system then reacts with an answer within seconds.
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