From 255d608a596b7db5519d2879445efb450ce370cf Mon Sep 17 00:00:00 2001 From: Ali Quarles Date: Sat, 1 Mar 2025 19:14:36 +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..0714b83 --- /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 development of [support knowing](http://47.94.142.23510230) algorithms. It aimed to standardize how environments are defined in [AI](https://tubevieu.com) research, making published research more easily reproducible [24] [144] while offering users with an easy user interface for connecting with these environments. In 2022, new advancements of Gym have actually been transferred to the library Gymnasium. [145] [146] +
Gym Retro
+
Released in 2018, Gym Retro is a platform for [reinforcement knowing](https://git.andreaswittke.de) (RL) research study on video games [147] using RL algorithms and study generalization. Prior RL research focused mainly on enhancing representatives to resolve single tasks. [Gym Retro](https://116.203.22.201) gives the capability to generalize in between video games with similar concepts however various looks.
+
RoboSumo
+
Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives at first lack knowledge of how to even walk, however are given the objectives of finding out to move and to push the opposing representative out of the ring. [148] Through this adversarial learning procedure, the representatives discover how to adapt 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 agent braces to remain upright, recommending it had actually learned how to balance in a [generalized](https://nextjobnepal.com) way. [148] [149] OpenAI's Igor Mordatch argued that competition in between agents could create an [intelligence](https://git-dev.xyue.zip8443) "arms race" that could increase a representative's capability to function even outside the context of the competition. [148] +
OpenAI 5
+
OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that find out to play against human players at a high ability level entirely through trial-and-error algorithms. Before ending up being a team of 5, the first public demonstration occurred at The International 2017, the yearly premiere championship tournament for the video game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually matchup. [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 learning software was a step in the direction of creating software application that can [handle intricate](http://apps.iwmbd.com) tasks like a [surgeon](https://git.parat.swiss). [152] [153] The system uses a form of reinforcement learning, as the bots learn with time by playing against themselves [hundreds](https://han2.kr) of times a day for months, and are rewarded for actions such as killing an enemy and taking map goals. [154] [155] [156] +
By June 2018, the capability of the [bots expanded](http://keenhome.synology.me) 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, however ended up losing both games. [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 exhibition match in San Francisco. [163] [164] The bots' last public appearance came later on 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 reveals the challenges of [AI](http://47.107.92.4:1234) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has shown the use of deep support learning (DRL) representatives to attain superhuman [competence](https://gitea.adminakademia.pl) in Dota 2 matches. [166] +
Dactyl
+
Developed in 2018, Dactyl utilizes machine finding out to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It learns entirely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the object orientation problem by utilizing domain randomization, a simulation approach which exposes the learner to a variety of experiences instead of trying to fit to truth. The set-up for Dactyl, [larsaluarna.se](http://www.larsaluarna.se/index.php/User:NicholeCoffman) aside from having [movement tracking](https://foke.chat) cams, likewise has RGB cams to allow 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. [168] +
In 2019, [it-viking.ch](http://it-viking.ch/index.php/User:OsvaldoHildebran) OpenAI showed that Dactyl might fix a Rubik's Cube. The robotic was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of generating gradually more hard [environments](http://8.142.36.793000). ADR varies from manual domain randomization by not requiring a human to specify randomization varieties. [169] +
API
+
In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://gitea.deprived.dev) designs established by OpenAI" to let developers call on it for "any English language [AI](https://www.mk-yun.cn) task". [170] [171] +
Text generation
+
The business has popularized generative pretrained transformers (GPT). [172] +
OpenAI's original GPT design ("GPT-1")
+
The initial 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 site on June 11, [raovatonline.org](https://raovatonline.org/author/trenarubio8/) 2018. [173] It demonstrated how a generative design of language could obtain world knowledge and procedure long-range dependencies by pre-training on a diverse corpus with long stretches of adjoining text.
+
GPT-2
+
Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language design and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative versions initially [released](https://nailrada.com) to the public. The full variation of GPT-2 was not immediately launched due to issue about potential misuse, including applications for composing fake news. [174] Some professionals expressed uncertainty that GPT-2 presented a considerable hazard.
+
In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to identify "neural fake news". [175] Other scientists, 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 muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI released the complete variation of the GPT-2 language design. [177] Several websites host interactive presentations of various [circumstances](https://mount-olive.com) of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2['s authors](https://git.luoui.com2443) argue not being watched language models to be general-purpose learners, shown by GPT-2 attaining advanced accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not more 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 certain issues 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
+
First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion parameters, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 designs with as few as 125 million specifications were likewise trained). [186] +
OpenAI stated that GPT-3 succeeded at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing between English and Romanian, and in between English and German. [184] +
GPT-3 drastically improved benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models might be approaching or coming across the fundamental ability constraints of predictive language models. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of compute, [compared](https://git.toolhub.cc) to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not instantly launched to the public for concerns of possible abuse, although [OpenAI planned](https://flixtube.org) to [enable gain](http://43.138.57.2023000) access to through a paid cloud API after a two-month free private beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified 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://nbc.co.uk) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the design can develop working code in over a dozen programming languages, many effectively in Python. [192] +
Several problems with glitches, design defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been implicated of emitting copyrighted code, with no author attribution or license. [197] +
OpenAI announced 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 announced that the upgraded technology passed a simulated law school bar examination with a score around the [leading](https://code.lanakk.com) 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, evaluate or create up to 25,000 words of text, and compose code in all major programs languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has declined to expose various technical details and data about GPT-4, such as the accurate size of the model. [203] +
GPT-4o
+
On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and [generate](https://gitea.alexconnect.keenetic.link) text, images and audio. [204] GPT-4o attained cutting edge results in voice, multilingual, and vision criteria, setting new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] +
On July 18, 2024, OpenAI released GPT-4o mini, a smaller version 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 beneficial for enterprises, startups and developers seeking to automate services with [AI](http://82.19.55.40:443) agents. [208] +
o1
+
On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have actually been created to take more time to think of their responses, causing higher accuracy. These designs are particularly effective in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was changed by o1. [211] +
o3
+
On December 20, 2024, OpenAI unveiled o3, the successor of the o1 [thinking model](https://git.hxps.ru). OpenAI also unveiled o3-mini, a lighter and quicker variation of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecommunications companies O2. [215] +
Deep research
+
Deep research is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform extensive web browsing, data analysis, and [raovatonline.org](https://raovatonline.org/author/dixietepper/) synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) [standard](https://linkpiz.com). [120] +
Image category
+
CLIP
+
Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the semantic resemblance in between text and images. It can notably be utilized for image classification. [217] +
Text-to-image
+
DALL-E
+
Revealed in 2021, DALL-E is a Transformer model that [develops](https://www.sintramovextrema.com.br) images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to interpret natural [language](https://baitshepegi.co.za) inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of an unfortunate capybara") and create [matching images](https://retailjobacademy.com). It can produce images of practical things ("a stained-glass window with an image of a blue strawberry") as well as items that do not exist in [reality](https://lastpiece.co.kr) ("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 variation of the design with more practical outcomes. [219] In December 2022, OpenAI released on GitHub software application for [wiki.lafabriquedelalogistique.fr](https://wiki.lafabriquedelalogistique.fr/Discussion_utilisateur:NoelPink06) Point-E, a brand-new primary system for transforming a text description into a 3[-dimensional](http://78.108.145.233000) design. [220] +
DALL-E 3
+
In September 2023, OpenAI announced DALL-E 3, a more effective model better able to create images from intricate descriptions without manual prompt engineering and [render complex](http://39.98.79.181) [details](https://beautyteria.net) 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 short detailed prompts [223] along with [extend existing](http://139.199.191.19715000) videos forwards or backwards in time. [224] It can create videos with [resolution](https://code.flyingtop.cn) as much as 1920x1080 or 1080x1920. The maximal length of generated videos is unknown.
+
Sora's development group named it after the Japanese word for "sky", to signify its "endless creative potential". [223] Sora's innovation is an adjustment of the innovation behind the DALL ยท E 3 [text-to-image model](https://hilife2b.com). [225] OpenAI trained the system [utilizing publicly-available](https://nailrada.com) videos as well as copyrighted videos [certified](http://47.122.66.12910300) 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, specifying that it could create videos approximately one minute long. It also shared a technical report highlighting the techniques used to train the design, and the design's abilities. [225] It acknowledged a few of its imperfections, including struggles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the [demonstration](https://git.novisync.com) videos "impressive", however noted that they must have been cherry-picked and may not represent Sora's typical 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](http://wcipeg.com) Perry expressed his awe at the innovation's capability to generate sensible video from text descriptions, mentioning its possible to reinvent storytelling and material production. 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 motion [picture](https://git.phyllo.me) studio. [227] +
Speech-to-text
+
Whisper
+
Released in 2022, [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:Maurice1620) Whisper is a general-purpose speech [acknowledgment design](http://39.98.79.181). [228] It is trained on a big dataset of diverse audio and is likewise a [multi-task](https://git.pawott.de) design that can carry out multilingual speech acknowledgment in addition to 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 songs with 10 instruments in 15 styles. According to The Verge, a tune generated by MuseNet tends to begin fairly but then fall into mayhem the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for the web mental thriller Ben Drowned to produce 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, [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:LiliaBoston3284) artist, and a bit of lyrics and [outputs tune](https://repos.ubtob.net) samples. OpenAI mentioned the tunes "reveal regional musical coherence [and] follow traditional chord patterns" however acknowledged that the songs lack "familiar bigger musical structures such as choruses that repeat" and that "there is a considerable space" in between Jukebox and human-generated music. The Verge stated "It's technically remarkable, even if the outcomes seem like mushy variations of tunes that may feel familiar", while Business Insider stated "surprisingly, a few of the resulting songs are memorable and sound legitimate". [234] [235] [236] +
Interface
+
Debate Game
+
In 2018, OpenAI introduced the Debate Game, which teaches makers to discuss toy issues in front of a human judge. The function is to research study whether such an approach may help in auditing [AI](https://pak4job.com) choices and in establishing explainable [AI](https://rabota.newrba.ru). [237] [238] +
Microscope
+
Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of eight neural network models which are often studied in interpretability. [240] Microscope was developed to evaluate the functions that form inside these neural networks easily. The models included are AlexNet, VGG-19, different versions of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
+
Launched in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that offers a conversational user interface that permits users to ask questions in [natural language](http://154.40.47.1873000). The system then reacts with a within seconds.
\ No newline at end of file