From 9cdd1471ee254bb8f06c8a0631840bac182195d1 Mon Sep 17 00:00:00 2001 From: anthonyewart0 Date: Tue, 18 Feb 2025 13:22:41 +0600 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..223ce6b --- /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 development of support learning algorithms. It aimed to standardize how environments are specified in [AI](https://gogs.sxdirectpurchase.com) research study, making published research study more quickly reproducible [24] [144] while offering users with a basic interface for connecting with these environments. In 2022, brand-new advancements of Gym have actually been relocated 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 on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on enhancing agents to resolve single jobs. Gym Retro offers the ability 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 robot agents initially do not have knowledge of how to even stroll, but are provided the goals of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives discover how to adjust to altering conditions. When a representative is then removed from this virtual environment and put in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents might produce an intelligence "arms race" that might increase an agent's ability to function even outside the context of the [competitors](https://pyra-handheld.com). [148] +
OpenAI 5
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OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that find out to play against human players at a high ability level totally through trial-and-error algorithms. Before becoming a group of 5, the first public presentation occurred at The International 2017, the annual best championship tournament for the video 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 learned by playing against itself for 2 weeks of actual time, which the knowing software [application](http://rackons.com) was a step in the direction of creating software application that can manage intricate tasks like a surgeon. [152] [153] The system uses a kind of support learning, as the bots find out gradually by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an opponent and [yewiki.org](https://www.yewiki.org/User:LucianaChau79) taking map objectives. [154] [155] [156] +
By June 2018, the [capability](https://git.genowisdom.cn) 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](https://mediawiki1263.00web.net). [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against expert gamers, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling 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 came later on that month, where they played in 42,729 overall games in a four-day open online competition, [winning](https://www.mepcobill.site) 99.4% of those games. [165] +
OpenAI 5['s systems](https://git.gqnotes.com) in Dota 2's bot player reveals the challenges of [AI](https://git.noisolation.com) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has shown using deep reinforcement knowing (DRL) agents to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses [device finding](https://www.yanyikele.com) out to train a Shadow Hand, a human-like robotic hand, to manipulate physical items. [167] It discovers totally in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation problem by utilizing domain randomization, a simulation method which exposes the student to a range of experiences instead of attempting to fit to truth. The set-up for [gratisafhalen.be](https://gratisafhalen.be/author/starlao635/) Dactyl, aside from having movement tracking cameras, [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:UnaProsser9137) likewise has RGB cameras to enable the robotic to control an arbitrary item by seeing it. In 2018, OpenAI showed that the system had the ability to [manipulate](https://code.dsconce.space) a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl could fix a Rubik's Cube. The robotic had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce intricate physics that is harder to design. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a [simulation approach](https://satitmattayom.nrru.ac.th) of generating progressively harder environments. ADR varies from manual domain randomization by not requiring a human to define randomization ranges. [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](http://47.100.72.85:3000) designs developed by OpenAI" to let designers call on it for "any English language [AI](https://photohub.b-social.co.uk) job". [170] [171] +
Text generation
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The business has 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 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 knowledge and process long-range dependences by pre-training on a varied corpus with long stretches of contiguous text.
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GPT-2
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Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language model and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative versions at first launched to the public. The complete variation of GPT-2 was not right away launched due to [concern](https://xn--114-2k0oi50d.com) about [prospective](http://wiki.iurium.cz) abuse, including applications for composing [fake news](https://nailrada.com). [174] Some professionals expressed uncertainty that GPT-2 postured a considerable threat.
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In response to GPT-2, the Allen Institute for [Artificial Intelligence](https://beta.hoofpick.tv) reacted with a tool to identify "neural fake news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation to totally 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 version of the GPT-2 language model. [177] Several sites host interactive presentations of various instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue without supervision language designs to be general-purpose students, highlighted by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not additional trained on any [task-specific](https://washcareer.com) 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 using byte pair encoding. This allows 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 follower to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion parameters, [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 couple of as 125 million criteria were also trained). [186] +
OpenAI stated that GPT-3 was successful at certain "meta-learning" jobs and could generalize the function of a single input-output pair. The GPT-3 offered examples of translation and cross-linguistic transfer learning between English and Romanian, and in between English and German. [184] +
GPT-3 significantly enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or encountering the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly launched to the general public for issues of possible abuse, although OpenAI planned to allow gain access to through a paid cloud API after a two-month free personal beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed exclusively to [Microsoft](https://service.aicloud.fit50443). [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://dancelover.tv) 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 create working code in over a dozen programming languages, most effectively in Python. [192] +
Several issues with glitches, design defects and [security](https://taelimfwell.com) vulnerabilities were cited. [195] [196] +
GitHub Copilot has been accused of producing copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would cease assistance for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI announced the [release](https://xhandler.com) 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 exam with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise check out, analyze or generate approximately 25,000 words of text, and write code in all significant programming languages. [200] +
Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained some of the problems with earlier revisions. [201] GPT-4 is also [capable](https://wellandfitnessgn.co.kr) of taking images as input on ChatGPT. [202] OpenAI has actually [declined](http://123.207.52.1033000) to reveal various technical details and data about GPT-4, such as the precise size of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained state-of-the-art lead to voice, multilingual, and vision criteria, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI released GPT-4o mini, a smaller version of GPT-4o changing 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 particularly beneficial for business, start-ups and designers looking for to automate services with [AI](http://47.93.16.222:3000) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:CharleyRudall29) which have been developed to take more time to think of their actions, leading to higher precision. These models are particularly [reliable](https://job.honline.ma) in science, coding, and thinking jobs, and [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:AndreThorp2) 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 unveiled](https://git.poggerer.xyz) o3, the successor of the o1 thinking design. OpenAI likewise revealed o3-mini, a lighter and faster version of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these models. [214] The design is called o3 rather than o2 to avoid confusion with telecoms companies O2. [215] +
Deep research study
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Deep research is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of [OpenAI's](http://8.211.134.2499000) o3 design to perform substantial web browsing, information analysis, and synthesis, [delivering detailed](https://tintinger.org) reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools enabled, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] +
Image classification
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CLIP
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Revealed in 2021, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:JoshKnaggs8102) CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the semantic similarity between text and images. It can significantly 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 creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate matching images. It can produce pictures of practical things ("a stained-glass window with a picture of a blue strawberry") along with items 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 DALL-E 2, an updated version of the model with more realistic results. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new fundamental system for converting a text description into a 3-dimensional model. [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more effective design much better able to create images from intricate descriptions without manual prompt engineering and render [intricate details](http://121.4.154.1893000) like hands and text. [221] It was [released](https://memorial-genweb.org) 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 model that can produce videos based upon short detailed prompts [223] in addition to extend existing videos forwards or backwards in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.
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Sora's advancement group called it after the Japanese word for "sky", to signify its "limitless creative potential". [223] Sora's technology is an adjustment of the technology behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos certified for that function, but did not reveal the number or the precise sources of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it might generate videos up to one minute long. It likewise shared a technical report highlighting the techniques used to train the model, and the design's capabilities. [225] It acknowledged some of its drawbacks, consisting of battles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", but noted that they must have been cherry-picked and may not represent Sora's normal output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, significant entertainment-industry figures have actually revealed significant interest in the technology's capacity. In an interview, actor/filmmaker [Tyler Perry](https://social.japrime.id) revealed his astonishment at the innovation's ability to produce practical video from text descriptions, citing its potential to transform storytelling and content development. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to pause plans for [broadening](http://81.70.24.14) 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 recognition model. [228] It is trained on a big dataset of diverse audio and is also a multi-task design that can carry out multilingual speech recognition along with speech translation and language recognition. [229] +
Music generation
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MuseNet
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Released in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in [MIDI music](https://www.sportpassionhub.com) files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a song created by MuseNet tends to start fairly but then fall into turmoil the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were used as early as 2020 for the internet mental [thriller](https://upskillhq.com) Ben Drowned to create music for the titular character. [232] [233] +
Jukebox
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Released in 2020, Jukebox is an open-sourced algorithm to create 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 mentioned the songs "show local musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes lack "familiar larger musical structures such as choruses that duplicate" and that "there is a significant gap" between Jukebox and human-generated music. The Verge stated "It's highly outstanding, even if the outcomes seem like mushy variations of songs that might feel familiar", while Business Insider specified "surprisingly, some of the resulting tunes 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 machines to debate toy problems in front of a human judge. The function is to research study whether such a method might assist in auditing [AI](https://www.jungmile.com) decisions and in establishing explainable [AI](https://54.165.237.249). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and neuron of 8 neural network models which are often studied in interpretability. [240] Microscope was developed to examine the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, various variations of Inception, and various [variations](https://forum.petstory.ge) of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an [artificial intelligence](https://edujobs.itpcrm.net) tool built on top of GPT-3 that offers a conversational interface that enables users to ask concerns in natural language. The system then responds with a response within seconds.
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