From a8708cf72652de64b848256c25a2da6e5dba21ad Mon Sep 17 00:00:00 2001 From: shaynescoggins Date: Fri, 7 Feb 2025 02:05:22 +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..e93b220 --- /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 support learning algorithms. It aimed to standardize how environments are specified in [AI](https://careerconnect.mmu.edu.my) research study, making released research study more quickly reproducible [24] [144] while supplying users with an easy user [interface](https://linkin.commoners.in) for engaging with these environments. In 2022, brand-new advancements of Gym have been moved to the [library Gymnasium](http://git.kdan.cc8865). [145] [146] +
Gym Retro
+
Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research on video games [147] using RL algorithms and research study generalization. Prior RL research study focused mainly on optimizing representatives to fix single tasks. Gym Retro gives the ability to generalize in between games with similar principles however various looks.
+
RoboSumo
+
Released in 2017, [larsaluarna.se](http://www.larsaluarna.se/index.php/User:DominickJulian9) RoboSumo is a virtual world where humanoid metalearning robot representatives at first lack understanding of how to even walk, but are offered the objectives of finding out to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the agents find out how to adjust to altering conditions. When a representative is then gotten rid of from this virtual environment and positioned in a new virtual environment with high winds, the representative braces to remain upright, recommending it had discovered how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that [competition](https://denis.usj.es) in between representatives might create an intelligence "arms race" that might increase a representative's ability to work even outside the context of the [competition](https://socialsnug.net). [148] +
OpenAI 5
+
OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:DannielleDixson) that learn to play against human players at a high ability level completely through experimental algorithms. Before becoming a group of 5, the very first public demonstration occurred at The International 2017, the annual best championship tournament for the video game, where Dendi, a professional Ukrainian player, [35.237.164.2](https://35.237.164.2/wiki/User:BessieFitzRoy) lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had learned by playing against itself for two weeks of actual time, and that the knowing software was a step in the direction of producing software application that can manage complex jobs like a surgeon. [152] [153] The system uses a form of reinforcement learning, as the bots learn with time by playing against themselves [hundreds](http://101.42.21.1163000) of times a day for months, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:LawerenceJeanner) 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 group of 5, and they had the ability to defeat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against professional players, however wound up losing both [video games](https://git.snaile.de). [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 look came later that month, where they played in 42,729 overall 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 reveals the difficulties of [AI](https://elit.press) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually demonstrated making use of deep support knowing (DRL) representatives to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
+
Developed in 2018, Dactyl uses machine finding out to train a Shadow Hand, a human-like robot hand, to control physical items. [167] It learns completely in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the item orientation issue by using domain randomization, a simulation technique which exposes the learner to a variety of experiences rather than trying to fit to truth. The set-up for Dactyl, aside from having movement tracking electronic cameras, 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 a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl might solve a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present complex 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 approach of creating progressively more hard environments. ADR varies from manual domain randomization by not [requiring](https://avicii.blog) a human to specify [randomization varieties](https://www.unotravel.co.kr). [169] +
API
+
In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](https://prantle.com) models developed by OpenAI" to let developers call on it for "any English language [AI](https://gitlab.edebe.com.br) task". [170] [171] +
Text generation
+
The company has actually popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT model ("GPT-1")
+
The initial paper on generative pre-training of a transformer-based language design was written by Alec Radford and his coworkers, and [published](https://gold8899.online) in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world [knowledge](http://133.242.131.2263003) and process long-range dependencies by pre-training on a varied corpus with long stretches of adjoining text.
+
GPT-2
+
[Generative Pre-trained](http://8.137.12.293000) Transformer 2 ("GPT-2") is a not being watched transformer language model and the follower to OpenAI's initial GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative variations at first launched to the public. The full version of GPT-2 was not immediately released due to concern about prospective abuse, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:Marcy4075626057) consisting of applications for writing phony news. [174] Some specialists revealed uncertainty that GPT-2 presented a substantial hazard.
+
In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to find "neural phony news". [175] Other scientists, such as Jeremy Howard, warned 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 total variation of the GPT-2 language model. [177] Several sites host interactive presentations of various circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2['s authors](https://git.math.hamburg) argue without supervision language designs to be general-purpose students, shown by GPT-2 attaining advanced accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not further trained on any task-specific input-output examples).
+
The corpus it was trained on, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It [prevents](http://47.102.102.152) certain issues encoding vocabulary with word tokens by using byte pair encoding. 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](https://thecodelab.online) model and the [successor](https://bug-bounty.firwal.com) to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion criteria, [184] two orders of magnitude larger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 designs with as couple of as 125 million criteria were likewise trained). [186] +
OpenAI mentioned that GPT-3 was successful at certain "meta-learning" jobs and might generalize the function of a single input-output pair. The GPT-3 release paper [offered examples](https://karmadishoom.com) of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184] +
GPT-3 drastically enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or coming across the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 needed [numerous](https://git.xaviermaso.com) thousand petaflop/s-days [b] of compute, [compared](https://git.programming.dev) to 10s of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately released to the public for issues of possible abuse, although OpenAI planned to enable 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 licensed exclusively to Microsoft. [190] [191] +
Codex
+
Announced in mid-2021, Codex is a descendant of GPT-3 that has actually furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://collegestudentjobboard.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can create working code in over a dozen programs languages, many successfully in Python. [192] +
Several problems with problems, style defects and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has been accused of [emitting copyrighted](https://www.etymologiewebsite.nl) code, without any author attribution or license. [197] +
OpenAI announced that they would stop assistance 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), capable of accepting text or image inputs. [199] They announced that the upgraded innovation passed a simulated law school bar exam with a score around the leading 10% of test takers. (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 write code in all major shows languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is likewise capable of taking images as input on [ChatGPT](https://www.ontheballpersonnel.com.au). [202] OpenAI has declined to reveal various [technical details](http://mengqin.xyz3000) and data about GPT-4, such as the precise size of the design. [203] +
GPT-4o
+
On May 13, 2024, OpenAI announced and released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained cutting [edge lead](https://socipops.com) to voice, multilingual, and vision criteria, setting new records in audio speech recognition and translation. [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 released](https://code.flyingtop.cn) GPT-4o mini, a smaller variation of GPT-4o replacing 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 expects it to be particularly helpful for enterprises, start-ups and designers seeking to automate services with [AI](http://yun.pashanhoo.com:9090) agents. [208] +
o1
+
On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been designed to take more time to consider their actions, resulting in higher accuracy. These models are particularly efficient in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was replaced by o1. [211] +
o3
+
On December 20, 2024, OpenAI unveiled o3, the follower of the o1 thinking design. OpenAI likewise unveiled o3-mini, a [lighter](http://www.yfgame.store) and faster version of OpenAI o3. Since December 21, 2024, this design is not available for public usage. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the chance to obtain early access to these models. [214] The model is called o3 instead of o2 to prevent confusion with telecommunications services company O2. [215] +
Deep research
+
Deep research study is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform comprehensive web browsing, 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 of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] +
Image classification
+
CLIP
+
Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to examine the semantic resemblance in between text and images. It can especially be used for image category. [217] +
Text-to-image
+
DALL-E
+
Revealed in 2021, DALL-E is a Transformer design that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to [interpret natural](https://iamzoyah.com) language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and [generate matching](http://git.365zuoye.com) images. It can [produce images](https://sosmed.almarifah.id) of [reasonable items](https://git.newpattern.net) ("a stained-glass window with a picture of a blue strawberry") along with things that do not exist in truth ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.
+
DALL-E 2
+
In April 2022, OpenAI revealed DALL-E 2, an updated variation of the model with more practical outcomes. [219] In December 2022, OpenAI published on GitHub software for Point-E, a new basic system for converting a into a 3-dimensional design. [220] +
DALL-E 3
+
In September 2023, OpenAI announced DALL-E 3, a more effective model much better able to create images from intricate descriptions without manual timely [engineering](http://47.108.94.35) and render complex details like hands and text. [221] It was launched to the public as a ChatGPT Plus function in October. [222] +
Text-to-video
+
Sora
+
Sora is a [text-to-video design](http://xn--mf0bm6uh9iu3avi400g.kr) that can produce videos based upon short detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of produced videos is unidentified.
+
Sora's development team named it after the Japanese word for "sky", to signify its "endless creative potential". [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 using publicly-available videos as well as copyrighted videos licensed 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, mentioning that it might generate videos as much as one minute long. It also shared a technical report highlighting the approaches used to train the model, and the design's abilities. [225] It acknowledged some of its shortcomings, including battles mimicing 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 common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, noteworthy entertainment-industry figures have shown considerable interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to produce sensible video from text descriptions, mentioning its possible to revolutionize storytelling and content production. He said that his enjoyment about Sora's possibilities was so strong that he had decided to stop briefly prepare for expanding his Atlanta-based motion picture studio. [227] +
Speech-to-text
+
Whisper
+
Released in 2022, Whisper is a general-purpose speech acknowledgment design. [228] It is [trained](http://jobsgo.co.za) on a large dataset of varied audio and is also a multi-task design that can carry out multilingual speech recognition along with speech translation and language identification. [229] +
Music generation
+
MuseNet
+
Released in 2019, MuseNet is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 designs. According to The Verge, a tune generated by MuseNet tends to [start fairly](http://wiki-tb-service.com) but then fall under 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](https://www.webthemes.ca) to create music for the titular character. [232] [233] +
Jukebox
+
Released in 2020, Jukebox is an open-sourced algorithm to generate 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 the songs "show local musical coherence [and] follow traditional chord patterns" but acknowledged that the songs do not have "familiar larger musical structures such as choruses that repeat" and that "there is a significant space" in between Jukebox and human-generated music. The Verge specified "It's technologically remarkable, even if the outcomes seem like mushy variations of tunes that might feel familiar", while Business Insider mentioned "remarkably, some of the resulting tunes are appealing and sound genuine". [234] [235] [236] +
User interfaces
+
Debate Game
+
In 2018, OpenAI introduced the Debate Game, which teaches machines to debate toy issues in front of a human judge. The purpose is to research whether such a technique may assist in auditing [AI](http://27.154.233.186:10080) choices and in establishing explainable [AI](https://gitee.mmote.ru). [237] [238] +
Microscope
+
Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and neuron of eight neural network models which are frequently studied in interpretability. [240] Microscope was created to examine the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various versions of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
+
Launched in November 2022, ChatGPT is an expert system tool built on top of GPT-3 that offers a conversational interface that permits users to ask questions in natural language. The system then reacts with an answer within seconds.
\ No newline at end of file