From 22aef566fe77162a970686e62507ae257e02c88e Mon Sep 17 00:00:00 2001 From: myrtishugo2323 Date: Mon, 17 Feb 2025 21:09:13 +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..8c43f46 --- /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 help with the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are specified in [AI](http://121.36.37.70:15501) research, making released research study more quickly reproducible [24] [144] while supplying users with a simple interface for connecting with these environments. In 2022, new developments of Gym have actually been transferred to the library Gymnasium. [145] [146] +
Gym Retro
+
Released in 2018, Gym Retro is a platform for support knowing (RL) research on video games [147] utilizing [RL algorithms](https://src.enesda.com) and research study generalization. [Prior RL](https://www.videomixplay.com) research focused mainly on enhancing representatives to resolve single jobs. Gym Retro offers the ability to generalize in between video games with comparable principles but different looks.
+
RoboSumo
+
Released in 2017, [RoboSumo](https://git.mm-music.cn) is a virtual world where humanoid metalearning robot representatives initially lack understanding of how to even stroll, however are offered the objectives of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial learning process, the [representatives](https://scholarpool.com) find out how to adjust to altering conditions. When a representative is then eliminated from this virtual environment and placed in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had learned how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives could create an intelligence "arms race" that might increase an agent's ability to work even outside the context of the competition. [148] +
OpenAI 5
+
OpenAI Five is a group of 5 OpenAI-curated bots [utilized](http://106.14.65.137) in the competitive five-on-five video game Dota 2, that learn to play against [human players](https://jobs.fabumama.com) at a high skill level completely through experimental algorithms. Before ending up being a team of 5, the very first public presentation occurred at The International 2017, the annual premiere championship tournament for the video game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for 2 weeks of actual time, which the knowing software was an action in the direction of developing software that can manage intricate jobs like a cosmetic surgeon. [152] [153] The system uses a form of support knowing, as the bots find out over time by [playing](https://git.fafadiatech.com) against themselves numerous times a day for months, and are rewarded for actions such as eliminating an opponent and taking map objectives. [154] [155] [156] +
By June 2018, the capability of the 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 two exhibition matches against expert gamers, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champs of the video game at the time, 2:0 in a live exhibit 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 video games. [165] +
OpenAI 5's systems in Dota 2's bot player reveals the difficulties of [AI](http://candidacy.com.ng) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has shown using deep reinforcement [knowing](https://ravadasolutions.com) (DRL) agents to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
+
Developed in 2018, Dactyl utilizes [machine finding](http://hmzzxc.com3000) out to train a Shadow Hand, a human-like robotic hand, to manipulate physical things. [167] It learns entirely in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the item orientation problem by utilizing domain randomization, [it-viking.ch](http://it-viking.ch/index.php/User:Dianna01H6) a simulation technique which exposes the learner to a variety of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking cams, also has RGB electronic cameras to allow the robotic to control an arbitrary object by seeing it. In 2018, OpenAI showed that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl might solve a Rubik's Cube. The robot had the ability to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce 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 method of producing progressively more [challenging environments](http://47.95.216.250). ADR differs from manual domain randomization by not needing a human to define randomization [varieties](http://git.superiot.net). [169] +
API
+
In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](https://gitea.carmon.co.kr) designs established by OpenAI" to let developers call on it for "any English language [AI](https://www.maisondurecrutementafrique.com) job". [170] [171] +
Text generation
+
The company has [promoted generative](https://git.goatwu.com) pretrained transformers (GPT). [172] +
OpenAI's original [GPT design](http://orcz.com) ("GPT-1")
+
The original paper on generative pre-training of a transformer-based language design was written by Alec Radford and his colleagues, and published in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative design of language might obtain world knowledge and [process long-range](https://git.touhou.dev) reliances by pre-training on a varied corpus with long stretches of adjoining text.
+
GPT-2
+
Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language design and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only restricted demonstrative variations initially launched to the public. The complete version of GPT-2 was not right away released due to concern about prospective abuse, consisting of applications for writing phony news. [174] Some specialists expressed uncertainty that GPT-2 presented a substantial risk.
+
In action to GPT-2, the Allen Institute for [Artificial Intelligence](https://git.yinas.cn) responded with a tool to identify "neural fake news". [175] Other researchers, such as Jeremy Howard, cautioned of "the technology to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be impossible to filter". [176] In November 2019, OpenAI released the complete variation of the GPT-2 language model. [177] Several sites host interactive demonstrations of different instances 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, shown by GPT-2 [attaining state-of-the-art](https://phpcode.ketofastlifestyle.com) precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further trained on any [task-specific input-output](https://embargo.energy) examples).
+
The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from [URLs shared](https://lr-mediconsult.de) in Reddit submissions with at least 3 upvotes. It prevents 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](https://careers.midware.in) [a] Transformer 3 (GPT-3) is a without supervision transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion parameters, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as few as 125 million criteria were likewise trained). [186] +
OpenAI specified that GPT-3 was successful at certain "meta-learning" tasks and might generalize the function of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer knowing between English and Romanian, and in between English and German. [184] +
GPT-3 dramatically improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or encountering the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 needed a number of 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 right away released to the general public for concerns of possible abuse, although [OpenAI prepared](https://customerscomm.com) 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, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:MaurineMyers) GPT-3 was licensed specifically to Microsoft. [190] [191] +
Codex
+
Announced in mid-2021, Codex is a descendant of GPT-3 that has actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://oldgit.herzen.spb.ru) 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 develop working code in over a dozen programs languages, most efficiently in Python. [192] +
Several problems with problems, style defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been implicated of producing copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would cease assistance 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), efficient in accepting text or image inputs. [199] They announced that the updated innovation passed a simulated law school [bar test](https://abilliontestimoniesandmore.org) 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 might likewise read, evaluate or create approximately 25,000 words of text, and compose code in all significant programs languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has declined to expose various technical details and stats about GPT-4, such as the exact size of the model. [203] +
GPT-4o
+
On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and produce text, images and audio. [204] GPT-4o [attained modern](http://www.hnyqy.net3000) lead to voice, multilingual, and vision standards, setting brand-new records in audio speech acknowledgment and [translation](https://git.home.lubui.com8443). [205] [206] It scored 88.7% on the Massive Multitask Language [Understanding](https://gitr.pro) (MMLU) criteria compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI launched GPT-4o mini, a smaller version 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 expects it to be especially useful for enterprises, start-ups and designers looking for to automate services with [AI](https://gitea.freshbrewed.science) agents. [208] +
o1
+
On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have actually been created to take more time to think of their responses, causing higher precision. These designs are particularly reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was replaced by o1. [211] +
o3
+
On December 20, 2024, OpenAI revealed o3, the successor of the o1 thinking model. OpenAI also revealed o3-mini, a lighter and [faster variation](https://www.dynamicjobs.eu) of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the opportunity to obtain early access to these designs. [214] The model is called o3 rather than o2 to prevent confusion with [telecommunications companies](https://signedsociety.com) O2. [215] +
Deep research study
+
Deep research is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to carry out comprehensive web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools enabled, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] +
Image category
+
CLIP
+
Revealed in 2021, CLIP ([Contrastive Language-Image](http://27.128.240.723000) Pre-training) is a design that is trained to analyze the semantic resemblance in between text and images. It can notably be used 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 translate natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of a sad capybara") and create matching images. It can create images of reasonable things ("a stained-glass window with an image of a blue strawberry") in addition to things that do not exist in truth ("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 DALL-E 2, an updated version of the model with more sensible results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new basic 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 effective design better able to generate images from complex descriptions without manual prompt engineering and render complex details like hands and text. [221] It was released to the public as a ChatGPT Plus function in October. [222] +
Text-to-video
+
Sora
+
Sora is a text-to-video design that can generate videos based on brief detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution up to 1920x1080 or [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:EMKMichaela) 1080x1920. The maximal length of generated videos is unknown.
+
Sora's development group called it after the Japanese word for "sky", to symbolize its "unlimited creative potential". [223] Sora's innovation is an adjustment of the innovation behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos as well as [copyrighted videos](http://christianpedia.com) certified for that function, however did not reveal the number or the precise 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 generate videos approximately one minute long. It also shared a technical report highlighting the methods utilized to train the design, and the model's capabilities. [225] It acknowledged a few of its shortcomings, consisting of struggles mimicing complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but kept in mind that they should have been cherry-picked and might not represent Sora's common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, significant entertainment-industry figures have shown substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's capability to produce practical video from text descriptions, mentioning its possible 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 prepare for expanding his Atlanta-based film studio. [227] +
Speech-to-text
+
Whisper
+
Released in 2022, Whisper is a general-purpose speech acknowledgment design. [228] It is trained on a large dataset of varied audio and is likewise a multi-task model that can carry out multilingual speech acknowledgment as well as speech translation and language recognition. [229] +
Music generation
+
MuseNet
+
Released in 2019, MuseNet is a deep neural net trained to forecast subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 designs. According to The Verge, a tune produced by MuseNet tends to begin fairly however then fall into chaos the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were utilized as early as 2020 for the internet psychological thriller Ben Drowned to develop music for the titular character. [232] [233] +
Jukebox
+
Released in 2020, Jukebox is an open-sourced algorithm to produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs tune samples. OpenAI mentioned the songs "show local musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that duplicate" which "there is a significant gap" in between Jukebox and human-generated music. The Verge mentioned "It's technically impressive, even if the results seem like mushy variations of songs that might feel familiar", while Business Insider specified "remarkably, some of the resulting tunes are memorable and sound genuine". [234] [235] [236] +
User user interfaces
+
Debate Game
+
In 2018, [OpenAI launched](https://git.goatwu.com) the Debate Game, which teaches machines to discuss toy issues in front of a human judge. The [function](http://git.jishutao.com) is to research whether such a [technique](http://git.ndjsxh.cn10080) may assist in auditing [AI](https://git.jzmoon.com) decisions and in developing explainable [AI](https://earlyyearsjob.com). [237] [238] +
Microscope
+
Released in 2020, [Microscope](https://cats.wiki) [239] is a collection of visualizations of every substantial layer and nerve cell of 8 neural network designs which are typically studied in interpretability. [240] Microscope was developed to examine the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, various variations of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
+
Launched in November 2022, ChatGPT is an artificial intelligence tool built on top of GPT-3 that provides a conversational user interface that enables users to ask [questions](https://mastercare.care) in natural language. The system then responds with a response within seconds.
\ No newline at end of file