From b172f00e6e8c9442d6e7798cb56e0a219ec34b0b Mon Sep 17 00:00:00 2001 From: Aliza Krischock Date: Sun, 9 Feb 2025 06:04:43 +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..69e8bfb --- /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 defined in [AI](https://223.130.175.147:6501) research, making released research more easily reproducible [24] [144] while offering users with a basic interface for interacting with these environments. In 2022, new developments of Gym have been transferred to the library Gymnasium. [145] [146] +
Gym Retro
+
Released in 2018, Gym Retro is a platform for support learning (RL) research on computer game [147] utilizing RL [algorithms](https://prantle.com) and study generalization. Prior RL research focused mainly on enhancing agents to fix single tasks. Gym Retro provides the capability to generalize between video games with similar principles however various looks.
+
RoboSumo
+
Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially lack knowledge of how to even stroll, however are given the goals of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, the agents learn how to adapt to altering conditions. When a representative is then eliminated from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually learned how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might develop an intelligence "arms race" that might increase a representative's capability to operate even outside the context of the competitors. [148] +
OpenAI 5
+
OpenAI Five is a group of 5 OpenAI-curated bots utilized in the competitive five-on-five [video game](https://projectblueberryserver.com) Dota 2, that learn to play against human players at a high ability [level totally](https://www.virsocial.com) through trial-and-error algorithms. Before becoming a team of 5, the first public presentation happened at The [International](https://timviecvtnjob.com) 2017, the yearly premiere championship tournament for the video 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 actual time, which the knowing software was an action in the direction of creating software application that can deal with complicated tasks like a surgeon. [152] [153] The system uses a type of support learning, as the bots find out in time by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156] +
By June 2018, the ability of the bots expanded to play together as a full 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 [exhibit matches](https://ezworkers.com) against expert players, but wound up losing both [video games](http://www.stardustpray.top30009). [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champions of the game at the time, 2:0 in a [live exhibit](https://marcosdumay.com) match in San Francisco. [163] [164] The bots' final public appearance came later that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games. [165] +
OpenAI 5's mechanisms in Dota 2's bot gamer shows the challenges of [AI](https://sun-clinic.co.il) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated using [deep support](https://firefish.dev) knowing (DRL) agents to attain superhuman skills in Dota 2 [matches](https://almanyaisbulma.com.tr). [166] +
Dactyl
+
Developed in 2018, Dactyl uses device finding out to train a Shadow Hand, a human-like robot hand, to control physical objects. [167] It finds out totally in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI tackled the things orientation issue by utilizing domain randomization, a simulation technique which exposes the student to a range of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking cams, also has RGB cameras to allow the robot to control an approximate object by seeing it. In 2018, OpenAI revealed that the system was able to control 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 present [complicated physics](https://firefish.dev) that is harder to model. OpenAI did this by improving the effectiveness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation method of creating gradually harder environments. ADR varies from manual domain randomization by not needing a human to define randomization varieties. [169] +
API
+
In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](http://jsuntec.cn:3000) models developed by OpenAI" to let [designers](http://git.cyjyyjy.com) get in touch with it for "any English language [AI](https://inicknet.com) task". [170] [171] +
Text generation
+
The company has actually promoted generative pretrained transformers (GPT). [172] +
OpenAI's original GPT design ("GPT-1")
+
The initial paper on generative pre-training of a transformer-based language model was written by Alec Radford and his associates, and published in preprint on OpenAI's website on June 11, 2018. [173] It [revealed](http://8.211.134.2499000) how a generative design of language could obtain world knowledge and procedure long-range dependencies by pre-training on a varied corpus with long stretches of adjoining text.
+
GPT-2
+
Generative Pre-trained Transformer 2 ("GPT-2") is a not being [watched transformer](http://git.pushecommerce.com) language design and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative versions initially released to the public. The complete version of GPT-2 was not immediately released due to issue about prospective misuse, including applications for writing fake news. [174] Some experts revealed uncertainty that GPT-2 positioned a substantial danger.
+
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, warned 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 impossible to filter". [176] In November 2019, OpenAI released the total variation of the GPT-2 language design. [177] Several sites host interactive demonstrations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue unsupervised language designs to be general-purpose learners, shown by GPT-2 attaining cutting [edge accuracy](https://mulaybusiness.com) and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not more trained on any task-specific input-output examples).
+
The corpus it was trained on, called WebText, contains somewhat 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by utilizing byte [pair encoding](https://git.k8sutv.it.ntnu.no). This allows representing any string of characters by encoding both individual characters and multiple-character tokens. [181] +
GPT-3
+
First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being watched transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full version of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as few as 125 million specifications were also trained). [186] +
OpenAI mentioned that GPT-3 prospered at certain "meta-learning" tasks and could generalize the function of a [single input-output](https://church.ibible.hk) pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer knowing in between English and Romanian, and in between English and German. [184] +
GPT-3 dramatically enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or experiencing the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 [required](https://igita.ir) a number of thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly launched 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 began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed exclusively to Microsoft. [190] [191] +
Codex
+
Announced in mid-2021, Codex is a descendant of GPT-3 that has actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.k4be.eu) powering the code autocompletion [tool GitHub](https://igit.heysq.com) Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the model can produce working code in over a lots shows languages, a lot of effectively in Python. [192] +
Several problems with glitches, style defects and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has been accused of releasing copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would cease support for Codex API on March 23, 2023. [198] +
GPT-4
+
On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the upgraded innovation passed a simulated law school bar examination with a rating around the leading 10% of test takers. (By contrast, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:Margareta19E) GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also check out, evaluate or produce up to 25,000 words of text, and compose code in all major programming languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an [improvement](https://mediascatter.com) on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose numerous technical details and statistics about GPT-4, such as the exact size of the design. [203] +
GPT-4o
+
On May 13, 2024, OpenAI announced 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 brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask [Language](http://182.92.251.553000) Understanding (MMLU) standard compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI released GPT-4o mini, a smaller variation of GPT-4o replacing 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 beneficial for enterprises, start-ups and developers looking for to automate services with [AI](http://103.254.32.77) representatives. [208] +
o1
+
On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have actually been designed to take more time to think of their actions, leading to greater accuracy. These models are particularly effective in science, coding, and thinking jobs, and were made available to Plus and Staff member. [209] [210] In December 2024, o1-preview was changed by o1. [211] +
o3
+
On December 20, 2024, OpenAI unveiled o3, the follower of the o1 reasoning design. OpenAI also unveiled o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this model 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 opportunity to obtain early access to these models. [214] The model is called o3 instead of o2 to prevent confusion with [telecoms](https://www.worlddiary.co) companies O2. [215] +
Deep research study
+
Deep research study is an agent established by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform substantial web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools made it possible for, it reached an [accuracy](https://www.kukustream.com) of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] +
Image classification
+
CLIP
+
Revealed in 2021, [links.gtanet.com.br](https://links.gtanet.com.br/terilenz4996) CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the semantic similarity between text and images. It can especially be utilized for image category. [217] +
Text-to-image
+
DALL-E
+
Revealed in 2021, DALL-E is a Transformer model that produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of an unfortunate capybara") and produce corresponding images. It can produce images of realistic 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"). As of March 2021, no API or code is available.
+
DALL-E 2
+
In April 2022, [OpenAI revealed](http://git.qhdsx.com) DALL-E 2, an updated variation of the design with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new primary system for transforming a text description into a 3-dimensional design. [220] +
DALL-E 3
+
In September 2023, OpenAI announced DALL-E 3, a more [effective model](http://117.72.39.1253000) better able to [produce](http://47.122.26.543000) images from complex descriptions without manual prompt engineering and render intricate details like hands and text. [221] It was released to the general public as a ChatGPT Plus feature in October. [222] +
Text-to-video
+
Sora
+
Sora is a [text-to-video model](https://www.careermakingjobs.com) that can generate videos based on short detailed triggers [223] in addition to extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The maximal length of created videos is unknown.
+
Sora's advancement team called it after the Japanese word for "sky", to signify its "endless imaginative capacity". [223] Sora's innovation is an adaptation of the [innovation](http://162.55.45.543000) 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 purpose, but did not reveal the number or the specific 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 create videos up to one minute long. It also shared a technical report highlighting the methods utilized to train the design, and the model's abilities. [225] It acknowledged a few of its imperfections, including battles replicating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but kept in mind that they must have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, notable entertainment-industry figures have actually shown considerable interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry [revealed](http://gitlab.nsenz.com) his awe at the innovation's ability to create realistic video from text descriptions, citing its [prospective](http://filmmaniac.ru) to change storytelling and material development. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to pause strategies for expanding his Atlanta-based motion picture studio. [227] +
Speech-to-text
+
Whisper
+
Released in 2022, Whisper is a general-purpose speech recognition design. [228] It is trained on a big dataset of varied 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
+
MuseNet
+
Released in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in MIDI music files. It can create tunes with 10 instruments in 15 styles. According to The Verge, a song created by MuseNet tends to start fairly however then fall into chaos the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for [wiki.whenparked.com](https://wiki.whenparked.com/User:JZKMireya164733) the internet mental thriller Ben Drowned to create music for the titular character. [232] [233] +
Jukebox
+
Released in 2020, Jukebox is an open-sourced algorithm to [generate](https://git.smartenergi.org) 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 specified the songs "show local musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" which "there is a substantial gap" in between Jukebox and human-generated music. The Verge mentioned "It's technically outstanding, even if the results sound like mushy variations of tunes that might feel familiar", while Business Insider mentioned "remarkably, some of the resulting songs are memorable and sound genuine". [234] [235] [236] +
User user interfaces
+
Debate Game
+
In 2018, OpenAI launched the Debate Game, which teaches makers to dispute toy problems in front of a human judge. The function is to research whether such a technique might assist in auditing [AI](http://www.grainfather.co.nz) decisions and in establishing explainable [AI](http://84.247.150.84:3000). [237] [238] +
Microscope
+
Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and neuron of 8 neural network designs which are typically studied in [interpretability](http://www.s-golflex.kr). [240] Microscope was produced to examine the features that form inside these neural networks easily. The models included are AlexNet, VGG-19, different versions of Inception, and various variations of CLIP Resnet. [241] +
ChatGPT
+
Launched in November 2022, ChatGPT is a synthetic intelligence tool constructed 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.
\ No newline at end of file