From d3176267ee539696035f5ba7ba0159d6917b0b4d Mon Sep 17 00:00:00 2001 From: seannno5682887 Date: Sat, 15 Feb 2025 11:19:40 +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..d7fd545 --- /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 assist in the development of support learning algorithms. It aimed to standardize how environments are specified in [AI](https://xn--9m1bq6p66gu3avit39e.com) research study, making published research more easily reproducible [24] [144] while offering users with an easy user interface for connecting with these environments. In 2022, new developments of Gym have actually been relocated to the [library Gymnasium](http://hitbat.co.kr). [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support learning (RL) research study on video games [147] [utilizing RL](http://210.236.40.2409080) algorithms and study generalization. Prior RL research [focused](https://twitemedia.com) mainly on optimizing representatives to solve single tasks. Gym Retro offers the capability to generalize in between games with similar concepts however various looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first do not have understanding of how to even walk, but are given the objectives of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial learning process, the agents discover how to adapt to changing conditions. When a representative is then eliminated from this virtual environment and positioned in a brand-new virtual environment with high winds, the agent braces to remain upright, [wiki.myamens.com](http://wiki.myamens.com/index.php/User:LoreenErtel66) suggesting it had found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that [competition](https://git.wheeparam.com) between agents could produce an intelligence "arms race" that could increase an agent's ability to work even outside the context of the [competition](https://www.flughafen-jobs.com). [148] +
OpenAI 5
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OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five computer [game Dota](http://geoje-badapension.com) 2, that learn to play against human gamers at a high ability level entirely through experimental algorithms. Before becoming a group of 5, the very first public presentation took place at The International 2017, the annual premiere [championship](https://www.employment.bz) tournament for the game, where Dendi, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) an expert Ukrainian player, 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 discovered by playing against itself for two weeks of genuine time, and [wiki.lafabriquedelalogistique.fr](https://wiki.lafabriquedelalogistique.fr/Utilisateur:Thaddeus3154) that the learning software application was an action in the direction of creating software application that can handle complex jobs like a cosmetic surgeon. [152] [153] The system uses a kind of support learning, as the bots discover gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an enemy and taking map goals. [154] [155] [156] +
By June 2018, the ability of the bots expanded to play together as a full group of 5, and they had the ability to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against expert players, but wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the [reigning](https://git.ipmake.me) world champs of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public look 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://weeddirectory.com) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has shown using deep reinforcement learning (DRL) agents to attain superhuman [proficiency](https://www.tmip.com.tr) in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes maker discovering to train a Shadow Hand, a human-like robotic hand, to control physical objects. [167] It finds out completely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI tackled the object orientation issue by utilizing domain randomization, a simulation approach which exposes the student to a range of [experiences](https://tageeapp.com) instead of trying to fit to truth. The set-up for Dactyl, aside from having movement tracking electronic cameras, likewise has RGB video cameras to allow 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 was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube [introduce](http://223.68.171.1508004) [complicated physics](http://47.98.226.2403000) that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation approach of producing progressively harder environments. [ADR differs](http://8.140.200.2363000) from manual domain randomization by not requiring 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](https://repo.amhost.net) models developed by OpenAI" to let developers contact it for "any English language [AI](https://git.watchmenclan.com) task". [170] [171] +
Text generation
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The business has actually popularized 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 composed by Alec Radford and his associates, and released in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative design of language could obtain world understanding and [pediascape.science](https://pediascape.science/wiki/User:CaroleRinaldi) process long-range reliances 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 an unsupervised transformer language model and the follower to [OpenAI's original](https://rassi.tv) GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just restricted demonstrative variations initially launched to the public. The full variation of GPT-2 was not right away released due to concern about potential abuse, including applications for writing fake news. [174] Some specialists expressed uncertainty that GPT-2 presented a considerable hazard.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to identify "neural phony news". [175] Other researchers, such as Jeremy Howard, cautioned of "the technology 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 version of the GPT-2 language design. [177] Several websites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue without supervision language designs to be general-purpose students, shown by GPT-2 [attaining advanced](https://professionpartners.co.uk) accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further trained on any [task-specific input-output](http://139.199.191.273000) 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 issues encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both individual characters and multiple-character tokens. [181] +
GPT-3
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First [explained](https://gitlab-dev.yzone01.com) in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a without supervision transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI specified that the complete version of GPT-3 contained 175 billion criteria, [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 parameters were likewise trained). [186] +
OpenAI mentioned 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 in between English and Romanian, and between English and German. [184] +
GPT-3 considerably enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the basic capability constraints of predictive language [designs](https://findspkjob.com). [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly released to the general public for concerns of possible abuse, although OpenAI prepared to permit gain access to through a paid [cloud API](https://gogolive.biz) after a two-month totally free personal beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed specifically to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.molokoin.ru) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can working code in over a lots shows languages, many effectively in Python. [192] +
Several issues with glitches, design flaws and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has been accused of producing copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would terminate 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), capable of accepting text or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar test 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 might also check out, analyze or produce up to 25,000 words of text, and write code in all major programming languages. [200] +
Observers reported that the model of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 retained 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 expose different technical details and data about GPT-4, such as the precise size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision standards, setting new records in audio speech recognition 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 released GPT-4o mini, a smaller variation of GPT-4o changing 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 $15 respectively for GPT-4o. OpenAI expects it to be especially helpful for business, start-ups and [designers](https://www.wikispiv.com) looking for to automate services with [AI](http://www.0768baby.com) representatives. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been created to take more time to believe about their responses, leading to greater precision. These [designs](https://drshirvany.ir) are particularly 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 by o1. [211] +
o3
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On December 20, 2024, OpenAI unveiled o3, the successor of the o1 thinking design. OpenAI likewise revealed o3-mini, a [lighter](https://paroldprime.com) and [quicker variation](https://koubry.com) of OpenAI o3. As of December 21, 2024, this design 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 designs. [214] The design is called o3 rather than o2 to prevent confusion with telecoms providers O2. [215] +
Deep research study
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Deep research study is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the [capabilities](https://mxlinkin.mimeld.com) of OpenAI's o3 model to perform comprehensive web browsing, information analysis, and synthesis, providing 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) standard. [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 similarity in between text and images. It can significantly 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 develops 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 purse shaped like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can produce pictures of reasonable things ("a stained-glass window with an image of a blue strawberry") along with things that do not exist in reality ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.
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DALL-E 2
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In April 2022, [OpenAI revealed](http://101.34.211.1723000) DALL-E 2, an upgraded version of the model with more practical results. [219] In December 2022, OpenAI published on GitHub software for Point-E, a brand-new simple system for converting a text description into a 3-dimensional design. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, a more effective design much better able to generate images from [complicated descriptions](https://asesordocente.com) without manual prompt [engineering](https://www.longisland.com) 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 design that can [generate](https://lab.gvid.tv) videos based upon brief detailed prompts [223] along with extend existing videos forwards or backwards in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.
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Sora's development team named it after the Japanese word for "sky", to symbolize its "unlimited imaginative potential". [223] Sora's innovation is an adaptation of the technology behind the DALL ยท E 3 [text-to-image](https://www.runsimon.com) model. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted [videos certified](https://code.linkown.com) for that purpose, however did not reveal 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 might generate videos up to one minute long. It also shared a technical report highlighting the methods used to train the design, and the design's capabilities. [225] It acknowledged some of its imperfections, consisting of battles mimicing complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", however noted that they need to have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, notable entertainment-industry figures have shown significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's ability to produce realistic video from text descriptions, mentioning its prospective to revolutionize storytelling and material creation. He said that his excitement 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 big dataset of varied audio and is also a multi-task model that can carry out multilingual speech [acknowledgment](http://111.2.21.14133001) 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 forecast subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 styles. According to The Verge, a tune produced by MuseNet tends to begin fairly however then fall into [turmoil](https://www.scikey.ai) the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the internet 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](http://111.61.77.359999) with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI mentioned the songs "show regional musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" and that "there is a substantial space" in between Jukebox and human-generated music. The Verge specified "It's technically impressive, even if the outcomes sound like mushy versions of tunes that may feel familiar", while Business Insider specified "surprisingly, a few of the resulting songs are catchy and sound legitimate". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, [OpenAI released](https://app.galaxiesunion.com) the Debate Game, which teaches machines to discuss toy problems in front of a human judge. The purpose is to research study whether such a method might assist in auditing [AI](https://my-sugar.co.il) choices and in establishing explainable [AI](http://repo.sprinta.com.br:3000). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of 8 neural network models which are frequently studied in interpretability. [240] Microscope was developed to evaluate the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various versions of Inception, and various variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is a synthetic intelligence tool constructed on top of GPT-3 that offers a conversational interface that permits users to ask concerns in natural language. The system then responds with an answer within seconds.
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