From 4c11f40f49c5afc0db63dd8feb4aaac4c9d7a024 Mon Sep 17 00:00:00 2001 From: arethasteinmet Date: Fri, 21 Feb 2025 06:04:06 +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..8653c33 --- /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 facilitate the development of reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](https://careers.tu-varna.bg) research study, making published research more easily reproducible [24] [144] while supplying users with an easy user interface for connecting with these environments. In 2022, new advancements 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 [yewiki.org](https://www.yewiki.org/User:UteRodriguez984) support learning (RL) research study on computer game [147] using RL algorithms and study generalization. Prior RL research focused mainly on optimizing agents to fix single tasks. Gym Retro offers the [capability](https://agora-antikes.gr) to generalize between games with similar ideas however different looks.
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RoboSumo
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Released in 2017, RoboSumo is a [virtual](http://hi-couplering.com) world where [humanoid metalearning](https://lovn1world.com) robot agents at first lack understanding of how to even walk, however are provided the objectives of [finding](http://101.34.66.2443000) out to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing procedure, the representatives learn how to adapt to altering conditions. When an agent is then removed from this virtual environment and put in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had found out how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might produce an intelligence "arms race" that might increase an agent's capability to work even outside the [context](https://my.buzztv.co.za) of the [competition](https://miderde.de). [148] +
OpenAI 5
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OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that discover to play against human gamers at a high ability level totally through trial-and-error algorithms. Before ending up being a group of 5, the very first public presentation took place at The [International](https://divsourcestaffing.com) 2017, the yearly best champion tournament for the game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually learned by playing against itself for 2 weeks of genuine time, which the learning software [application](http://tfjiang.cn32773) was an action in the direction of creating software that can [handle complex](https://git.lunch.org.uk) tasks like a cosmetic surgeon. [152] [153] The system uses a form of support learning, as the bots discover 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 goals. [154] [155] [156] +
By June 2018, the ability of the bots broadened to play together as a complete group of 5, and they were able to defeat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against professional gamers, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public appearance came later on that month, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:XFPZack3509) 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 mechanisms in Dota 2's bot gamer shows the obstacles of [AI](http://39.98.84.232:3000) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated using deep support learning (DRL) representatives to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses device finding out to train a Shadow Hand, a human-like robot hand, to control physical things. [167] It learns entirely in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI took on the item orientation issue by utilizing domain randomization, a simulation technique which exposes the student to a range of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking cameras, also has RGB cameras to permit the robot to control an approximate item 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](https://www.informedica.llc) that Dactyl might resolve a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube [introduce](https://www.pinnaclefiber.com.pk) intricate physics that is harder to model. OpenAI did this by enhancing the toughness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation technique of producing progressively harder environments. ADR differs from manual domain randomization by not needing a human to specify randomization ranges. [169] +
API
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In June 2020, [OpenAI revealed](http://dcmt.co.kr) a multi-purpose API which it said was "for accessing new [AI](http://git.twopiz.com:8888) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](http://47.121.121.137:6002) task". [170] [171] +
Text generation
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The company has promoted generative [pretrained transformers](http://1.14.122.1703000) (GPT). [172] +
[OpenAI's original](http://81.70.25.1443000) GPT model ("GPT-1")
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The original paper on generative pre-training of a [transformer-based language](https://papersoc.com) design was composed by Alec Radford and his colleagues, and published in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative model of language could obtain world knowledge and process long-range dependences 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](https://firstcanadajobs.ca) model and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only restricted demonstrative variations at first launched to the general public. The full version of GPT-2 was not instantly launched due to concern about potential abuse, including applications for writing fake news. [174] Some professionals revealed uncertainty that GPT-2 postured a significant hazard.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to find "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 drown out 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 different instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue unsupervised language models to be general-purpose students, illustrated by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot jobs (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 somewhat 40 [gigabytes](http://www.jimtangyh.xyz7002) of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain issues encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of [characters](https://gitlab.dangwan.com) by encoding both individual characters and [multiple-character](https://2t-s.com) 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 stated](https://thematragroup.in) that the full variation of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 designs with as few as 125 million specifications were also trained). [186] +
OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" jobs and could generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and [cross-linguistic transfer](https://git.nullstate.net) learning in between English and Romanian, and in between English and German. [184] +
GPT-3 drastically improved benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models might be approaching or encountering the essential capability constraints of predictive language designs. [187] Pre-training GPT-3 [required numerous](http://47.99.37.638099) thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately released to the general public for concerns of possible abuse, although OpenAI planned to allow gain access to through a paid cloud API after a [two-month totally](https://vieclamangiang.net) free personal 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 of GPT-3 that has additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://82.146.58.193) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the model can create working code in over a lots shows languages, a lot of efficiently in Python. [192] +
Several issues with glitches, style flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been implicated of producing copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would terminate support 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 or image inputs. [199] They revealed that the upgraded innovation passed a simulated law school bar exam with a score around the [leading](http://42.192.14.1353000) 10% of [test takers](https://www.finceptives.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, evaluate or generate as much as 25,000 words of text, and compose code in all major programs languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has declined to reveal various [technical details](https://daystalkers.us) 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 announced and launched GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision standards, setting new records in [audio speech](https://www.kritterklub.com) 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 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 anticipates it to be especially helpful for business, start-ups and developers looking for to automate services with [AI](https://www.cittamondoagency.it) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been developed to take more time to consider their reactions, causing greater precision. These models are especially reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was changed by o1. [211] +
o3
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On December 20, 2024, OpenAI revealed o3, the successor of the o1 reasoning design. OpenAI likewise unveiled o3-mini, a lighter and quicker variation of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are evaluating 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 model is called o3 rather than o2 to prevent confusion with telecoms companies O2. [215] +
Deep research
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Deep research study is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform substantial web surfing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools made it possible for, it reached a [precision](http://1024kt.com3000) 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 examine the semantic similarity in between text and images. It can especially 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 an unfortunate capybara") and create corresponding images. It can create pictures of sensible things ("a stained-glass window with an image of a blue strawberry") in addition to objects 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 announced DALL-E 2, an updated version of the design with more practical outcomes. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-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 much better able to generate images from [intricate descriptions](https://moztube.com) without manual prompt 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 produce videos based on brief detailed prompts [223] as well as extend existing videos forwards or backwards in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of created videos is unknown.
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Sora's development team called it after the Japanese word for "sky", to symbolize its "unlimited innovative capacity". [223] Sora's technology is an adjustment 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, however did not reveal the number or the precise sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it might generate videos approximately one minute long. It likewise shared a technical report highlighting the techniques 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 "impressive", however noted that they need to have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some academic leaders following [Sora's public](https://gitlab.dndg.it) demo, significant entertainment-industry figures have shown significant interest in the innovation's [potential](https://quicklancer.bylancer.com). In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's ability to generate sensible video from text descriptions, mentioning its potential to reinvent storytelling and material development. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to pause plans for [expanding](https://gogs.eldarsoft.com) his Atlanta-based motion [picture](https://gitea.shoulin.net) 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 large dataset of diverse audio and is also a multi-task model that can carry out [multilingual speech](https://pakkjob.com) acknowledgment in addition to 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](https://amorweddfair.com) to forecast subsequent musical notes in MIDI music files. It can generate tunes with 10 instruments in 15 designs. According to The Verge, a tune generated by MuseNet tends to begin fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the internet mental thriller Ben Drowned to develop music for the [titular character](https://pakallnaukri.com). [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](http://81.70.25.1443000) a category, artist, and a snippet of lyrics and outputs tune samples. OpenAI stated the tunes "reveal regional musical coherence [and] follow traditional chord patterns" but acknowledged that the songs lack "familiar bigger musical structures such as choruses that repeat" and that "there is a considerable space" in between Jukebox and human-generated music. The Verge specified "It's technologically excellent, even if the outcomes seem like mushy variations of songs that may feel familiar", while Business Insider mentioned "remarkably, a few of the resulting songs are appealing and sound legitimate". [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 [discuss](https://myvip.at) toy problems in front of a human judge. The function is to research whether such an approach might assist in auditing [AI](https://eukariyer.net) choices and in establishing explainable [AI](https://tweecampus.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and nerve cell of 8 neural network models which are typically studied in interpretability. [240] Microscope was created to evaluate the features that form inside these neural networks quickly. The designs consisted of are AlexNet, VGG-19, different versions of Inception, and various variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, [ChatGPT](https://gitea.shoulin.net) is an artificial intelligence tool built on top of GPT-3 that offers a conversational user interface that enables users to ask concerns in natural language. The system then reacts with a response within seconds.
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