From c4fdd456480b03d553040dc32a50666458b8a703 Mon Sep 17 00:00:00 2001 From: chester6395556 Date: Fri, 28 Feb 2025 16:19:04 +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..5d2a6cc --- /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 help with the advancement of reinforcement knowing [algorithms](https://git.pm-gbr.de). It aimed to standardize how environments are defined in [AI](https://pediascape.science) research, making released research more quickly reproducible [24] [144] while offering users with an easy user interface for interacting with these environments. In 2022, brand-new advancements of Gym have been [transferred](http://104.248.138.208) to the library Gymnasium. [145] [146] +
Gym Retro
+
Released in 2018, Gym Retro is a platform for support learning (RL) research on video games [147] utilizing RL algorithms and research study generalization. Prior RL research [focused](https://git.vhdltool.com) mainly on optimizing agents to fix single tasks. Gym Retro gives the capability to generalize in between video games with comparable principles however various appearances.
+
RoboSumo
+
Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives at first lack understanding of how to even stroll, but are offered the goals of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the agents discover how to adapt to altering conditions. When a representative is then gotten rid of from this virtual environment and put in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had actually found out how to stabilize in a generalized method. [148] [149] [OpenAI's Igor](https://talento50zaragoza.com) Mordatch argued that competition in between agents could develop an intelligence "arms race" that could increase a representative's capability to operate even outside the context of the competitors. [148] +
OpenAI 5
+
OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that learn to play against human players at a high ability level entirely through experimental [algorithms](http://ledok.cn3000). Before ending up being a group of 5, the first public presentation happened at The [International](https://yeetube.com) 2017, the annual best championship competition for the video game, where Dendi, a [professional Ukrainian](http://git.z-lucky.com90) player, 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 two weeks of genuine time, which the learning software application was an action in the [instructions](https://git.kansk-tc.ru) of [creating software](https://www.chinami.com) that can deal with intricate jobs like a cosmetic surgeon. [152] [153] The system utilizes a kind 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 expanded to play together as a full team of 5, and they were able to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against professional gamers, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five OG, the ruling world champions of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public appearance came later that month, where they played in 42,729 overall games in a four-day open online competition, winning 99.4% of those video games. [165] +
OpenAI 5's mechanisms in Dota 2's bot gamer reveals the challenges of [AI](https://rpcomm.kr) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually shown making use of deep reinforcement knowing (DRL) representatives to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
+
Developed in 2018, Dactyl utilizes device learning to train a Shadow Hand, a human-like robotic hand, to manipulate physical things. [167] It learns completely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation issue by utilizing domain randomization, a simulation technique which exposes the student to a range of [experiences](https://git.komp.family) rather than trying to fit to truth. The set-up for Dactyl, aside from having movement tracking video cameras, likewise has RGB electronic cameras to allow the robot to control an arbitrary object by seeing it. In 2018, OpenAI revealed that the system was able to [manipulate](https://walnutstaffing.com) a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl might solve a Rubik's Cube. The robotic had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce intricate physics that is harder to model. OpenAI did this by [improving](https://www.basketballshoecircle.com) the toughness of Dactyl to [perturbations](https://www.jobsition.com) by utilizing Automatic Domain Randomization (ADR), a simulation method of [generating progressively](http://82.146.58.193) more tough environments. ADR differs from manual [domain randomization](http://180.76.133.25316300) by not needing a human to specify randomization ranges. [169] +
API
+
In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](https://elsalvador4ktv.com) models established by OpenAI" to let designers contact it for "any English language [AI](http://47.121.121.137:6002) task". [170] [171] +
Text generation
+
The company has promoted generative pretrained [transformers](https://git.kitgxrl.gay) (GPT). [172] +
OpenAI's original GPT model ("GPT-1")
+
The original paper on [generative pre-training](http://mangofarm.kr) of a transformer-based language design was composed by Alec Radford and his associates, and published in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative model of language might obtain world knowledge and procedure long-range reliances by pre-training on a varied corpus with long stretches of contiguous text.
+
GPT-2
+
Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language model and the successor to OpenAI's initial GPT model ("GPT-1"). GPT-2 was announced in February 2019, with just limited demonstrative versions at first released to the public. The full variation of GPT-2 was not instantly launched due to concern about possible abuse, consisting of applications for composing phony news. [174] Some specialists expressed uncertainty that GPT-2 positioned a considerable threat.
+
In response to GPT-2, the Allen Institute for [Artificial Intelligence](https://becalm.life) [responded](http://kyeongsan.co.kr) with a tool to detect "neural phony 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 difficult to filter". [176] In November 2019, OpenAI launched the total version of the GPT-2 language model. [177] Several websites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being watched language models to be general-purpose students, highlighted by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the design 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 at least 3 upvotes. It prevents certain problems encoding vocabulary with word tokens by utilizing byte pair [encoding](https://abalone-emploi.ch). This allows representing any string of characters by encoding both private characters and multiple-character tokens. [181] +
GPT-3
+
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 that the complete version of GPT-3 contained 175 billion specifications, [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 few as 125 million criteria were also trained). [186] +
OpenAI specified that GPT-3 prospered at certain "meta-learning" tasks and could generalize the function of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer knowing in between English and Romanian, and between English and [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:ShanePantoja67) German. [184] +
GPT-3 dramatically enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs could be approaching or experiencing the basic capability constraints of predictive language models. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the complete 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 planned to enable 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 specifically to Microsoft. [190] [191] +
Codex
+
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://git.tederen.com) 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 develop working code in over a lots programming languages, a lot of effectively in Python. [192] +
Several concerns with glitches, design flaws and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has actually been [implicated](http://ledok.cn3000) of emitting copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would stop support for Codex API on March 23, 2023. [198] +
GPT-4
+
On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar test 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 read, examine or create up to 25,000 words of text, and write code in all major shows languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the problems with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to reveal numerous [technical details](https://pak4job.com) and data about GPT-4, such as the precise size of the model. [203] +
GPT-4o
+
On May 13, 2024, OpenAI announced and released GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained cutting edge results in 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) benchmark compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized 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 anticipates](https://167.172.148.934433) it to be particularly beneficial for business, startups and designers seeking to automate services with [AI](https://foke.chat) representatives. [208] +
o1
+
On September 12, 2024, OpenAI launched the o1[-preview](http://47.99.37.638099) and o1-mini designs, which have actually been designed to take more time to consider their reactions, resulting in greater accuracy. These designs are especially 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 [changed](http://47.103.29.1293000) by o1. [211] +
o3
+
On December 20, 2024, OpenAI unveiled o3, the follower of the o1 thinking model. OpenAI likewise unveiled o3-mini, a lighter and much faster variation of OpenAI o3. As of December 21, 2024, this design is not available for [public usage](http://106.52.121.976088). According to OpenAI, they are [testing](http://139.162.7.1403000) o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security researchers had the opportunity to obtain early access to these models. [214] The model is called o3 instead of o2 to avoid confusion with [telecoms companies](http://119.23.72.7) O2. [215] +
Deep research
+
Deep research study is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform extensive web browsing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] +
Image category
+
CLIP
+
Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the semantic similarity in between text and images. It can notably be used for image classification. [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 variation of GPT-3 to interpret natural language inputs (such as "a green leather purse formed like a pentagon" or "an isometric view of an unfortunate capybara") and generate corresponding images. It can develop pictures of [reasonable items](http://travelandfood.ru) ("a stained-glass window with an image of a blue strawberry") along with items 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 announced DALL-E 2, an [updated](http://123.206.9.273000) version of the design with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new simple system for transforming a text description into a 3-dimensional design. [220] +
DALL-E 3
+
In September 2023, OpenAI revealed DALL-E 3, a more powerful model much better able to create images from complicated descriptions without manual timely engineering and render complicated details like hands and text. [221] It was [launched](https://video.lamsonsaovang.com) to the public as a ChatGPT Plus feature in October. [222] +
Text-to-video
+
Sora
+
Sora is a text-to-video design that can generate videos based upon short detailed triggers [223] along with extend existing videos forwards or backwards in time. [224] It can generate videos with resolution up to 1920x1080 or 1080x1920. The optimum length of created videos is unidentified.
+
Sora's development group named it after the Japanese word for "sky", to signify its "unlimited creative potential". [223] Sora's innovation is an adjustment of the technology behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos along with copyrighted videos licensed for that purpose, however did not expose 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 as much as one minute long. It also shared a technical report highlighting the techniques used to train the design, and the model's capabilities. [225] It acknowledged some of its drawbacks, consisting of struggles mimicing [intricate](https://git.andrewnw.xyz) physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", however kept in mind that they need to have been cherry-picked and might not represent Sora's normal 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 revealed his awe at the technology's ability to generate reasonable video from text descriptions, mentioning its potential to change storytelling and material production. He said that his enjoyment about [Sora's possibilities](https://job4thai.com) was so strong that he had actually decided to pause prepare for expanding his Atlanta-based movie studio. [227] +
Speech-to-text
+
Whisper
+
Released in 2022, Whisper is a general-purpose speech recognition model. [228] It is trained on a big dataset of varied audio and is also a [multi-task design](https://gitlab.alpinelinux.org) that can perform multilingual speech acknowledgment as well as speech translation and language identification. [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 designs. According to The Verge, a tune created by MuseNet tends to start fairly however then fall under chaos the longer it plays. [230] [231] In popular culture, initial applications 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
+
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 stated the tunes "reveal regional musical coherence [and] follow standard chord patterns" but acknowledged that the songs do not have "familiar larger musical structures such as choruses that repeat" which "there is a considerable space" in between Jukebox and human-generated music. The Verge specified "It's highly impressive, even if the results seem like mushy variations of songs that might feel familiar", while Business Insider stated "surprisingly, some of the resulting songs are memorable and sound genuine". [234] [235] [236] +
Interface
+
Debate Game
+
In 2018, OpenAI launched the Debate Game, which teaches machines to debate toy problems in front of a human judge. The purpose is to research study whether such a technique may help in auditing [AI](http://gogsb.soaringnova.com) decisions and in establishing explainable [AI](http://g-friend.co.kr). [237] [238] +
Microscope
+
Released in 2020, Microscope [239] is a collection of [visualizations](https://manilall.com) of every considerable layer and nerve cell of eight neural network designs which are typically studied in interpretability. [240] Microscope was created to evaluate the features that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, different versions of Inception, and various variations of CLIP Resnet. [241] +
ChatGPT
+
Launched in November 2022, ChatGPT is an artificial intelligence tool constructed on top of GPT-3 that provides a conversational user interface that enables users to ask questions in natural language. The system then reacts with an answer within seconds.
\ No newline at end of file