commit a403374db71b04530b7f098a9cea5e26649c92d7 Author: stephanrignall Date: Sun Apr 6 20:18:16 2025 +0800 Add The Verge Stated It's Technologically Impressive 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..7f10b48 --- /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 facilitate the development of reinforcement learning [algorithms](http://139.199.191.273000). It aimed to standardize how environments are specified in [AI](https://www.istorya.net) research, making released research study more easily reproducible [24] [144] while providing users with an easy interface for engaging with these environments. In 2022, new advancements of Gym have been transferred 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 computer game [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing representatives to resolve single tasks. Gym Retro provides the ability to generalize between video games with comparable ideas but various appearances.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially lack understanding of how to even walk, however are offered the goals of learning to move and to push the opposing representative out of the ring. [148] Through this adversarial learning process, the agents discover how to adjust to changing conditions. When a representative is then removed from this virtual environment and placed in a new virtual environment with high winds, the [agent braces](https://www.tvcommercialad.com) to remain upright, recommending it had discovered how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents might create an intelligence "arms race" that could increase a representative's ability to operate even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that learn to play against human players at a high ability level completely through experimental algorithms. Before becoming a team of 5, the first public presentation occurred at The International 2017, the yearly premiere 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 found out by playing against itself for 2 weeks of real time, which the knowing software was an action in the direction of developing software application that can deal with complex tasks like a surgeon. [152] [153] The system uses a type of reinforcement knowing, as the bots learn gradually by [playing](https://testgitea.cldevops.de) against themselves hundreds of 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 capability of the bots broadened to play together as a full team of 5, and they had the ability to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against expert gamers, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champions 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 that month, where they played in 42,729 total games in a four-day open online competitors, winning 99.4% of those games. [165] +
OpenAI 5's mechanisms in Dota 2's bot gamer shows the difficulties of [AI](https://www.shopes.nl) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has shown making use of deep support knowing (DRL) representatives to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses machine finding out to train a Shadow Hand, a human-like robotic hand, to manipulate physical items. [167] It discovers entirely 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 learner to a range of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking electronic cameras, also has RGB cams to permit the robot to control an arbitrary object by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an [octagonal prism](http://47.95.216.250). [168] +
In 2019, OpenAI demonstrated that Dactyl could solve a Rubik's Cube. The [robotic](https://theindietube.com) had the ability to solve the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by improving the toughness of Dactyl to [perturbations](https://www.cdlcruzdasalmas.com.br) by utilizing Automatic Domain Randomization (ADR), a simulation method of producing gradually harder environments. ADR varies from manual domain randomization by not requiring 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 brand-new [AI](https://jobs.salaseloffshore.com) designs developed by OpenAI" to let developers contact it for "any English language [AI](https://jobsnotifications.com) task". [170] [171] +
Text generation
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The company has actually popularized generative pretrained transformers (GPT). [172] +
OpenAI's original GPT design ("GPT-1")
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The initial paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a [generative model](https://www.trappmasters.com) of language might obtain world understanding 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 without supervision transformer language model and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative versions initially released to the general public. The complete version of GPT-2 was not instantly launched due to issue about potential abuse, including applications for composing fake news. [174] Some experts revealed uncertainty that GPT-2 positioned a considerable threat.
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In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to identify "neural fake news". [175] Other researchers, 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 drown out all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the total version of the GPT-2 language model. [177] Several sites host [interactive demonstrations](https://suomalaistajalkapalloa.com) of different circumstances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue not being watched language models to be general-purpose learners, highlighted by GPT-2 attaining modern 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](https://ssh.joshuakmckelvey.com) in Reddit submissions with a minimum of 3 upvotes. It prevents certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This allows 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 without supervision transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 contained 175 billion parameters, [184] 2 orders of [magnitude bigger](https://git.sofit-technologies.com) than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were likewise trained). [186] +
OpenAI stated that GPT-3 prospered at certain "meta-learning" jobs and might generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184] +
GPT-3 dramatically enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs could be approaching or encountering the basic ability constraints of predictive language models. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of calculate, compared 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 general public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a [two-month free](https://www.drawlfest.com) 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 additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://www.litehome.top) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the design can create working code in over a [dozen programs](https://www.valenzuelatrabaho.gov.ph) languages, most efficiently in Python. [192] +
Several concerns with problems, style flaws and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has actually been implicated of giving off [copyrighted](https://oakrecruitment.uk) code, without any author attribution or license. [197] +
OpenAI revealed 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](https://git.freesoftwareservers.com) 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the upgraded technology passed a simulated law school bar with a score around the leading 10% of [test takers](http://git.iloomo.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, evaluate or create up to 25,000 words of text, and compose code in all significant programs 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 issues with earlier modifications. [201] GPT-4 is also [capable](https://www.waitumusic.com) of taking images as input on ChatGPT. [202] OpenAI has actually declined to reveal various technical details and data about GPT-4, such as the exact size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI announced and released 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 acknowledgment and [translation](https://talentup.asia). [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI launched GPT-4o mini, a smaller sized variation of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT interface. Its API costs $0.15 per million [input tokens](https://repo.komhumana.org) 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](https://code.nwcomputermuseum.org.uk) looking for to automate services with [AI](https://dreamtube.congero.club) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have actually been created to take more time to think of their reactions, resulting in greater [accuracy](http://elektro.jobsgt.ch). These models are especially efficient in science, coding, and thinking tasks, and 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 revealed o3, the successor of the o1 thinking model. OpenAI also revealed o3-mini, a lighter and quicker variation of OpenAI o3. As of 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, security 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 telecoms services service provider O2. [215] +
Deep research study
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Deep research is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to [perform substantial](https://parentingliteracy.com) web browsing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120] +
Image classification
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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 evaluate the semantic similarity in between text and images. It can notably be utilized 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 model that creates images from textual descriptions. [218] DALL-E uses a 12[-billion-parameter](http://39.99.158.11410080) version of GPT-3 to interpret natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and produce matching images. It can create images of practical items ("a stained-glass window with a picture of a blue strawberry") as well as items that do not exist in reality ("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 announced DALL-E 2, an updated variation of the design with more realistic results. [219] In December 2022, OpenAI released on [GitHub software](https://www.shwemusic.com) for Point-E, a new primary system for converting a text description into a 3-dimensional model. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, a more effective design better able to generate images from complex descriptions without manual timely engineering 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 model that can create videos based on short detailed prompts [223] along with 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 [unidentified](https://www.bjs-personal.hu).
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Sora's development group called it after the Japanese word for "sky", to symbolize its "endless 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 using publicly-available videos as well as copyrighted videos certified for [wiki.myamens.com](http://wiki.myamens.com/index.php/User:TawnyaWhitley87) that function, but did not reveal 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 could generate videos as much as one minute long. It also shared a technical report highlighting the techniques utilized to train the model, and the design's capabilities. [225] It acknowledged a few of its drawbacks, consisting of struggles 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 normal output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, significant entertainment-industry figures have revealed substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to create [realistic video](https://git.137900.xyz) from text descriptions, citing its potential to revolutionize storytelling and material creation. He said that his excitement about [Sora's possibilities](https://code.3err0.ru) was so strong that he had decided to stop briefly plans for [broadening](https://gitea.thuispc.dynu.net) his Atlanta-based movie studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, [Whisper](https://job.honline.ma) is a general-purpose speech acknowledgment design. [228] It is trained on a big dataset of varied audio and is likewise a [multi-task](https://daystalkers.us) design that can perform multilingual speech recognition as well as 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](https://git.lotus-wallet.com) net trained to forecast subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a song created by MuseNet tends to begin fairly however then fall under chaos the longer it plays. [230] [231] In pop culture, [preliminary applications](https://theboss.wesupportrajini.com) of this tool were used as early as 2020 for the internet mental thriller 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 genre, artist, and a snippet of lyrics and outputs song samples. [OpenAI mentioned](https://blkbook.blactive.com) the songs "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" which "there is a significant space" between Jukebox and human-generated music. The Verge stated "It's technically remarkable, even if the outcomes sound like mushy variations of tunes that might feel familiar", while Business Insider stated "surprisingly, some of the resulting tunes are appealing and sound genuine". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI released the Debate Game, which teaches makers to debate toy problems in front of a human judge. The [function](http://www.asystechnik.com) is to research study whether such a method may help in auditing [AI](https://git.desearch.cc) decisions and in developing explainable [AI](https://sebeke.website). [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 designs which are often studied in interpretability. [240] Microscope was created to examine the features that form inside these neural networks easily. The models consisted of are AlexNet, [yewiki.org](https://www.yewiki.org/User:LucianaChau79) 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 built on top of GPT-3 that supplies 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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