From 557019b78f9eb69b4e122b91547225f272304e83 Mon Sep 17 00:00:00 2001 From: karolkelleher Date: Thu, 27 Feb 2025 03:57:26 +0800 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..6322bb5 --- /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 to assist in the advancement of reinforcement learning [algorithms](https://repo.komhumana.org). It aimed to standardize how environments are defined in [AI](https://recruitment.transportknockout.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 been moved to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research study on video games [147] utilizing RL algorithms and study generalization. Prior RL research [focused](https://animployment.com) mainly on optimizing agents to solve single tasks. Gym Retro offers the ability to generalize between video games with similar concepts but different appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where [humanoid metalearning](https://hayhat.net) robot agents at first do not have understanding of how to even walk, however are given the objectives of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial learning procedure, the representatives find out how to adapt to altering conditions. When a representative is then eliminated from this virtual environment and positioned in a new virtual environment with high winds, [wiki-tb-service.com](http://wiki-tb-service.com/index.php?title=Benutzer:TobiasChristison) the representative braces to remain upright, recommending it had actually learned how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives could produce an intelligence "arms race" that could increase a representative's capability to operate even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a group of 5 [OpenAI-curated bots](https://rrallytv.com) utilized in the competitive five-on-five computer game Dota 2, that find out to play against human players at a high ability level entirely through experimental algorithms. Before ending up being a group of 5, the first public presentation happened at The International 2017, the annual best [championship competition](https://www.thempower.co.in) for the game, where Dendi, a professional Ukrainian player, 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 two weeks of real time, and that the learning software was an action in the direction of developing software that can deal with complex tasks like a surgeon. [152] [153] The system utilizes a form of support knowing, as the bots discover gradually by playing against themselves hundreds of times a day for months, and are rewarded for [actions](http://47.100.72.853000) such as eliminating an enemy and taking map objectives. [154] [155] [156] +
By June 2018, the ability of the bots broadened to play together as a full group of 5, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:Rosaline99U) and they had the ability to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The [International](http://git.bkdo.net) 2018, OpenAI Five played in two exhibit matches against expert gamers, but wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last [public appearance](https://www.iratechsolutions.com) came later that month, where they played in 42,729 total video 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 shows the difficulties of [AI](https://git.qoto.org) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated the use of [deep reinforcement](https://calciojob.com) (DRL) representatives to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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[Developed](https://becalm.life) in 2018, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11984259) Dactyl uses device discovering to train a Shadow Hand, a human-like robot hand, to manipulate physical objects. [167] It learns completely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation problem by utilizing domain randomization, a simulation approach which exposes the student to a variety of experiences rather than trying to fit to truth. The set-up for Dactyl, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) aside from having motion tracking cams, also has RGB video cameras to permit the robot to manipulate an arbitrary things by seeing it. In 2018, OpenAI revealed that the system had the ability to [control](https://git.frugt.org) a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl could resolve a Rubik's Cube. The robotic was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to model. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a [simulation technique](http://www.grainfather.eu) of producing progressively more tough environments. ADR differs from manual domain randomization by not [requiring](https://git.citpb.ru) a human to specify randomization ranges. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://intermilanfansclub.com) designs established by OpenAI" to let developers get in touch with it for "any English language [AI](https://jobs.constructionproject360.com) job". [170] [171] +
Text generation
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The company has actually promoted generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT model ("GPT-1")
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The original paper on generative pre-training of a transformer-based language design was [composed](http://47.244.232.783000) by Alec Radford and his coworkers, and released in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world understanding and process 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 design and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just restricted demonstrative variations at first released to the general public. The complete variation of GPT-2 was not instantly launched due to issue about prospective abuse, including applications for composing fake news. [174] Some specialists expressed uncertainty that GPT-2 posed a substantial hazard.
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In reaction to GPT-2, the Allen Institute for [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:MacFalls93386606) Artificial Intelligence responded with a tool to detect "neural fake news". [175] Other scientists, 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 muffle all other speech and be impossible to filter". [176] In November 2019, OpenAI released the complete variation of the GPT-2 [language model](https://www.florevit.com). [177] Several sites 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 designs to be general-purpose students, highlighted by GPT-2 attaining advanced accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the model 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 with at least 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both individual characters and [yewiki.org](https://www.yewiki.org/User:MorrisVillasenor) 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 design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion specifications, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were likewise trained). [186] +
OpenAI stated that GPT-3 prospered at certain "meta-learning" jobs and could generalize the purpose of a [single input-output](https://gitea.tgnotify.top) pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning in between English and Romanian, and in between English and German. [184] +
GPT-3 considerably enhanced benchmark outcomes over GPT-2. [OpenAI cautioned](https://spiritustv.com) that such scaling-up of language models could be approaching or coming across the fundamental ability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of compute, [compared](https://git.dsvision.net) to 10s of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly released to the 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 private 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 additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://shankhent.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the design can [develop](https://ckzink.com) working code in over a dozen shows languages, many efficiently in Python. [192] +
Several problems with problems, style defects and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has been implicated of discharging copyrighted code, without any author attribution or license. [197] +
OpenAI revealed that they would cease 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 announced that the updated innovation 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 read, examine or produce up to 25,000 words of text, and compose code in all significant programming languages. [200] +
Observers reported that the iteration of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained some of the problems with earlier revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has decreased to expose different technical details and stats about GPT-4, such as the exact size of the design. [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](http://xn--ok0b74gbuofpaf7p.com) edge results in voice, multilingual, and vision criteria, setting 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 sized version of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT user interface. Its [API costs](http://47.102.102.152) $0.15 per million [input tokens](https://git.fracturedcode.net) and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI expects it to be especially useful for business, start-ups and designers looking for to automate services with [AI](http://24insite.com) representatives. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have been created to take more time to think about their responses, [leading](https://camtalking.com) to greater accuracy. These designs are particularly efficient in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Staff member. [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 follower of the o1 thinking model. OpenAI likewise unveiled o3-mini, a lighter and much faster variation of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the opportunity to obtain early access to these designs. [214] The design is called o3 rather than o2 to prevent confusion with telecommunications providers O2. [215] +
Deep research study
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Deep research is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform extensive web surfing, data analysis, and synthesis, [delivering detailed](https://govtpakjobz.com) reports within a timeframe of 5 to thirty minutes. [216] With browsing and [Python tools](https://wiki.solsombra-abdl.com) 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 analyze the [semantic similarity](https://goodinfriends.com) 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](https://www.jobzpakistan.info) in 2021, DALL-E is a Transformer model that develops images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and create matching images. It can produce images of practical things ("a stained-glass window with an image of a blue strawberry") as well as items that do not exist in truth ("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 DALL-E 2, an upgraded variation of the design with more sensible outcomes. [219] In December 2022, OpenAI published on GitHub software for Point-E, a new rudimentary system for converting 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 design better able to generate images from complicated descriptions without manual [prompt engineering](https://bebebi.com) and render complicated details like hands and text. [221] It was launched to the public as a ChatGPT Plus [feature](http://plethe.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 on short detailed triggers [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of [generated](http://123.207.206.1358048) videos is unknown.
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Sora's advancement team called it after the Japanese word for "sky", to symbolize its "limitless imaginative capacity". [223] Sora's technology 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 in addition to copyrighted videos certified for that purpose, but did not reveal the number or the exact sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, stating that it could create videos approximately one minute long. It also shared a technical report highlighting the methods utilized to train the model, and the model's capabilities. [225] It acknowledged some of its drawbacks, consisting of battles simulating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", however kept in mind that they should 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 shown significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to create [realistic](https://git.thunraz.se) video from text descriptions, mentioning its possible to change storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had actually chosen to stop briefly plans 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 varied audio and is likewise a multi-task design that can perform multilingual speech acknowledgment along with 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 generate songs with 10 instruments in 15 styles. According to The Verge, a tune generated by MuseNet tends to begin fairly however then fall into chaos the longer it plays. [230] [231] In popular culture, preliminary 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 produce music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs tune samples. OpenAI specified the songs "show regional musical coherence [and] follow standard chord patterns" but acknowledged that the tunes lack "familiar bigger musical structures such as choruses that duplicate" which "there is a substantial gap" in between Jukebox and human-generated music. The Verge stated "It's technologically outstanding, even if the results sound like mushy versions of tunes that may feel familiar", while Business Insider mentioned "surprisingly, some of the resulting tunes are memorable and sound legitimate". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, [OpenAI released](https://comunidadebrasilbr.com) the Debate Game, which teaches machines to dispute toy problems in front of a human judge. The [purpose](https://pedulidigital.com) is to research study whether such an approach may help in auditing [AI](http://nas.killf.info:9966) choices and in establishing explainable [AI](http://49.234.213.44). [237] [238] +
Microscope
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[Released](http://www.book-os.com3000) in 2020, Microscope [239] is a collection of visualizations of every [considerable layer](http://81.70.93.2033000) and nerve cell of 8 neural network models which are often studied in interpretability. [240] Microscope was developed to evaluate the features that form inside these neural networks easily. The designs included are AlexNet, VGG-19, different versions of Inception, and different 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 provides a conversational user interface that permits users to ask concerns in natural language. The system then reacts with an answer within seconds.
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