From ea2625f0a516f22dba525caff1d91d42c684b86f Mon Sep 17 00:00:00 2001 From: alberthabarkma Date: Sun, 23 Feb 2025 00:25:49 +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..df10f1f --- /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 reinforcement knowing algorithms. It aimed to standardize how environments are specified in [AI](https://cloudsound.ideiasinternet.com) research, making published research study more easily reproducible [24] [144] while offering users with an easy user interface for interacting with these environments. In 2022, new developments of Gym have been relocated to the library Gymnasium. [145] [146] +
Gym Retro
+
Released in 2018, Gym Retro is a platform for support knowing (RL) research study on video games [147] utilizing RL algorithms and study generalization. Prior RL research [focused](https://kenyansocial.com) mainly on optimizing agents to solve single tasks. Gym Retro provides the ability to generalize between video games with similar concepts however different appearances.
+
RoboSumo
+
Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first lack knowledge of how to even stroll, however are provided the goals of learning to move and to push the opposing agent out of the ring. [148] Through this adversarial knowing process, [surgiteams.com](https://surgiteams.com/index.php/User:JuanitaFouch2) the representatives find out how to adjust to altering conditions. When a representative is then gotten rid of from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, recommending it had actually found out how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between agents could [develop](http://101.200.241.63000) an intelligence "arms race" that might increase a representative's capability to work even outside the context of the competition. [148] +
OpenAI 5
+
OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that find out to play against human gamers at a high ability level completely through trial-and-error algorithms. Before ending up being a team of 5, the first public demonstration happened at The International 2017, the annual best championship tournament for the game, where Dendi, a professional 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 actually discovered by playing against itself for 2 weeks of real time, which the [learning software](https://sc.e-path.cn) was an action in the direction of creating software application that can deal with intricate jobs like a surgeon. [152] [153] The system [utilizes](http://hrplus.com.vn) a type of reinforcement knowing, as the bots find out with time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an enemy and taking map objectives. [154] [155] [156] +
By June 2018, the capability of the bots expanded to play together as a full group of 5, and they were able to defeat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 [exhibition matches](http://pplanb.co.kr) against expert gamers, however wound up losing both games. [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 exhibition match in San Francisco. [163] [164] The bots' final public appearance came later that month, where they played in 42,729 total video games in a four-day open online competition, winning 99.4% of those games. [165] +
OpenAI 5's systems in Dota 2's bot player reveals the challenges of [AI](https://git.starve.space) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has shown the usage of deep support knowing (DRL) representatives to attain superhuman competence in Dota 2 matches. [166] +
Dactyl
+
Developed in 2018, Dactyl uses maker finding out to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It discovers completely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation problem by utilizing domain randomization, a simulation method which exposes the learner to a [variety](https://luckyway7.com) of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking electronic cameras, likewise has RGB cams to allow the robot to manipulate an arbitrary things by seeing it. In 2018, OpenAI showed that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might fix a Rubik's Cube. The robotic was able to fix 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 effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of producing gradually harder environments. ADR differs from manual domain randomization by not needing a human to specify randomization varieties. [169] +
API
+
In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](https://gitlab.edebe.com.br) models established by OpenAI" to let developers call on it for "any English language [AI](https://finance.azberg.ru) task". [170] [171] +
Text generation
+
The business has actually promoted generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("GPT-1")
+
The initial paper on generative pre-training of a transformer-based language model was written by Alec Radford and his colleagues, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world understanding and process long-range reliances by pre-training on a varied corpus with long [stretches](https://hireteachers.net) of adjoining text.
+
GPT-2
+
Generative Pre-trained Transformer 2 ("GPT-2") is a without supervision transformer language model and the successor [wiki.whenparked.com](https://wiki.whenparked.com/User:LetaX2026348693) to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative variations initially released to the public. The complete variation of GPT-2 was not immediately launched due to issue about potential misuse, consisting of applications for composing phony news. [174] Some professionals revealed uncertainty that GPT-2 posed a substantial danger.
+
In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to spot "neural phony 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 muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the complete version of the GPT-2 language model. [177] Several websites host interactive demonstrations of various instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being watched language designs to be [general-purpose](https://winf.dhsh.de) students, illustrated by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not additional trained on any [task-specific input-output](https://ouptel.com) examples).
+
The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents certain problems 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 without supervision transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full variation of GPT-3 contained 175 billion specifications, [184] two orders of magnitude larger than the 1.5 billion [185] in the complete [variation](https://git.gumoio.com) of GPT-2 (although GPT-3 designs with as few as 125 million specifications were likewise trained). [186] +
OpenAI stated that GPT-3 prospered at certain "meta-learning" jobs and might generalize the purpose 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 enhanced benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of [language designs](https://hcp.com.gt) could be approaching or experiencing the fundamental capability constraints of [predictive language](https://reckoningz.com) models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, 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 immediately released to the public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month totally free personal beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified solely to Microsoft. [190] [191] +
Codex
+
Announced in mid-2021, Codex is a descendant of GPT-3 that has additionally been [trained](https://jobs.colwagen.co) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.89u89.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the model can produce working code in over a dozen programming languages, a lot of effectively in Python. [192] +
Several concerns with glitches, design defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been implicated of giving off copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would terminate 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), capable of accepting text or image inputs. [199] They revealed that the updated technology passed a simulated law school bar examination with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could likewise check out, evaluate or produce up to 25,000 words of text, and compose code in all major shows languages. [200] +
Observers reported that the version of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained some of the problems with earlier modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has declined to expose different 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 cutting edge outcomes in voice, multilingual, and vision benchmarks, setting new records in audio speech acknowledgment 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 GPT-4o mini, a smaller [variation](https://gitlab.tncet.com) 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 particularly useful for enterprises, [startups](http://kodkod.kr) and designers seeking to automate services with [AI](https://raida-bw.com) agents. [208] +
o1
+
On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have actually been created to take more time to consider their actions, [causing](http://gitlab.zbqdy666.com) greater accuracy. These designs are especially efficient 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 reasoning design. OpenAI likewise revealed o3-mini, a lighter and faster variation of OpenAI o3. As of December 21, 2024, this model is not available for [pipewiki.org](https://pipewiki.org/wiki/index.php/User:BrigetteWhitmore) public use. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, safety and [security scientists](https://gurjar.app) had the opportunity to obtain early access to these designs. [214] The model is called o3 instead of o2 to avoid confusion with telecommunications services provider O2. [215] +
Deep research
+
Deep research is an agent established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to perform extensive web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools enabled, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] +
Image classification
+
CLIP
+
Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to analyze the semantic similarity between text and images. It can significantly be utilized for image classification. [217] +
Text-to-image
+
DALL-E
+
Revealed in 2021, DALL-E is a Transformer model that develops images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to analyze natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and create matching images. It can create pictures of sensible things ("a stained-glass window with a picture of a blue strawberry") along with objects that do not exist in [reality](https://profesional.id) ("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 [upgraded variation](https://git.daoyoucloud.com) of the model with more practical results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a new basic system for converting a text description into a 3-dimensional design. [220] +
DALL-E 3
+
In September 2023, OpenAI announced DALL-E 3, a more effective design better able to create images from complex descriptions without manual prompt engineering and [render complex](http://115.124.96.1793000) details like hands and text. [221] It was [released](https://reklama-a5.by) to the public as a ChatGPT Plus function in October. [222] +
Text-to-video
+
Sora
+
Sora is a text-to-video design that can [produce videos](http://turtle.tube) based on brief detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of created videos is unidentified.
+
Sora's advancement group called it after the Japanese word for "sky", to signify its "endless innovative potential". [223] Sora's technology is an adjustment of the technology behind the DALL ยท E 3 text-to-image design. [225] [OpenAI trained](https://git.pandaminer.com) the system utilizing publicly-available videos in addition to [copyrighted videos](https://gigen.net) accredited for that purpose, but did not reveal the number or the exact sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, specifying that it might create videos as much as one minute long. It also shared a [technical report](https://git.xhkjedu.com) highlighting the methods utilized to train the model, and the design's abilities. [225] It acknowledged a few of its imperfections, including struggles imitating complex physics. [226] Will [Douglas Heaven](http://47.96.131.2478081) of the MIT Technology Review called the presentation videos "remarkable", but noted that they should have been cherry-picked and might not represent Sora's typical output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, notable entertainment-industry figures have actually revealed significant interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's ability to create realistic video from text descriptions, mentioning its prospective to [transform storytelling](https://gitea.scubbo.org) and material creation. He said that his enjoyment about Sora's possibilities was so strong that he had chosen to pause plans for broadening his [Atlanta-based film](https://git.tx.pl) studio. [227] +
Speech-to-text
+
Whisper
+
Released in 2022, [Whisper](https://alldogssportspark.com) is a general-purpose speech acknowledgment design. [228] It is trained on a big dataset of varied audio and is likewise a multi-task design that can carry out multilingual speech recognition in addition to 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 tunes with 10 instruments in 15 styles. According to The Verge, a tune generated by MuseNet tends to begin fairly but then fall into turmoil the longer it plays. [230] [231] In popular culture, initial applications of this tool were used as early as 2020 for the web mental 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 category, artist, and a snippet of lyrics and outputs song samples. OpenAI mentioned the tunes "reveal local musical coherence [and] follow standard chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" which "there is a considerable space" in between Jukebox and human-generated music. The Verge stated "It's highly excellent, even if the outcomes seem like mushy versions of tunes that may feel familiar", while Business Insider stated "remarkably, a few of the resulting songs are appealing and sound genuine". [234] [235] [236] +
Interface
+
Debate Game
+
In 2018, OpenAI released the Debate Game, which teaches machines to discuss toy problems in front of a human judge. The function is to research whether such an approach might assist in auditing [AI](https://gitea.rodaw.net) choices 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 significant layer and nerve cell of eight neural network models which are typically studied in interpretability. [240] Microscope was developed to evaluate the [features](https://www.virtuosorecruitment.com) that form inside these neural networks easily. The models included are AlexNet, VGG-19, various versions of Inception, and different variations of CLIP Resnet. [241] +
ChatGPT
+
Launched in November 2022, is an expert system tool developed on top of GPT-3 that offers a conversational interface that permits users to ask concerns in natural language. The system then reacts with a response within seconds.
\ No newline at end of file