azucenanun9157/lovetechconsulting
1
0
Code Issues Actions Packages Projects Wiki

Add The Verge Stated It's Technologically Impressive

Azucena Sison 2025-02-15 05:56:05 +08:00
parent 1dccd3de1c
commit 57bfa52f06
1 changed files with 76 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

76
The-Verge-Stated-It%27s-Technologically-Impressive.md Normal file

@ -0,0 +1,76 @@
<br>Announced in 2016, Gym is an open-source Python library created to facilitate the advancement of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://insta.kptain.com) research study, making published research more [easily reproducible](http://49.235.130.76) [24] [144] while [providing](https://git.the-kn.com) users with a basic interface for interacting with these environments. In 2022, brand-new developments of Gym have actually been transferred to the library Gymnasium. [145] [146]
<br>Gym Retro<br>
<br>Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research study on video games [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing representatives to solve single tasks. Gym Retro offers the capability to generalize in between games with similar concepts but various appearances.<br>
<br>RoboSumo<br>
<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first do not have understanding of how to even walk, however are provided the goals of finding out to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing process, the representatives discover how to adjust to [altering conditions](https://storymaps.nhmc.uoc.gr). When an agent is then gotten rid of from this virtual environment and put in a new virtual environment with high winds, the agent braces to remain upright, [recommending](http://git.daiss.work) it had actually discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives could produce an intelligence "arms race" that might increase a representative's capability to function even outside the context of the competition. [148]
<br>OpenAI 5<br>
<br>OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that learn to play against human players at a high ability level entirely through experimental algorithms. Before ending up being a team of 5, the first public presentation occurred at The International 2017, the yearly premiere [champion tournament](http://119.3.9.593000) for the video game, where Dendi, a professional Ukrainian 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 discovered by playing against itself for two weeks of actual time, which the knowing software was a step in the instructions of producing software application that can deal with complex tasks like a surgeon. [152] [153] The system utilizes a type of [reinforcement](https://opela.id) learning, as the bots discover with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an enemy and taking map goals. [154] [155] [156]
<br>By June 2018, the ability of the bots broadened to play together as a full team 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 two exhibition matches against professional gamers, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public look came later on that month, where they played in 42,729 overall video games in a four-day open online competition, [winning](https://furrytube.furryarabic.com) 99.4% of those games. [165]
<br>OpenAI 5's mechanisms in Dota 2's bot gamer shows the difficulties of [AI](https://redmonde.es) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has shown the use of deep support learning (DRL) representatives to attain superhuman competence in Dota 2 matches. [166]
<br>Dactyl<br>
<br>Developed in 2018, Dactyl utilizes machine discovering to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It finds out entirely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the object orientation issue by using domain randomization, a simulation technique which exposes the learner to a variety of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking cams, likewise has RGB cams to permit the robot to control an approximate things by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism. [168]
<br>In 2019, OpenAI demonstrated that Dactyl could resolve a Rubik's Cube. The robot had the ability 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](https://spiritustv.com) the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating gradually more challenging environments. ADR differs from manual domain randomization by not requiring a human to specify randomization varieties. [169]
<br>API<br>
<br>In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new [AI](http://bolsatrabajo.cusur.udg.mx) models established by OpenAI" to let designers call on it for "any English language [AI](https://gitea.imwangzhiyu.xyz) task". [170] [171]
<br>Text generation<br>
<br>The company has popularized generative pretrained transformers (GPT). [172]
<br> GPT design ("GPT-1")<br>
<br>The initial paper on generative pre-training of a transformer-based language model was written by Alec Radford and his coworkers, and released in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative design of [language](https://gitlab.dev.cpscz.site) might obtain world knowledge and process long-range dependences by pre-training on a diverse corpus with long stretches of adjoining text.<br>
<br>GPT-2<br>
<br>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 just restricted demonstrative variations initially launched to the public. The full variation of GPT-2 was not instantly launched due to issue about potential misuse, including applications for composing phony news. [174] Some professionals expressed uncertainty that GPT-2 postured a considerable threat.<br>
<br>In action to GPT-2, the Allen Institute for Artificial Intelligence [responded](http://208.167.242.1503000) with a tool to spot "neural phony news". [175] Other researchers, such as Jeremy Howard, alerted of "the technology to totally 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 launched the total version of the GPT-2 language design. [177] Several sites host interactive presentations of different circumstances of GPT-2 and other transformer models. [178] [179] [180]
<br>GPT-2's authors argue without [supervision language](https://www.dutchsportsagency.com) designs to be general-purpose learners, highlighted by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not more trained on any task-specific input-output examples).<br>
<br>The corpus it was trained on, called WebText, contains a little 40 [gigabytes](https://noxxxx.com) of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both private characters and multiple-character tokens. [181]
<br>GPT-3<br>
<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 contained 175 billion criteria, [184] 2 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 specifications were also trained). [186]
<br>OpenAI specified that GPT-3 was successful at certain "meta-learning" tasks and might generalize the purpose of a [single input-output](http://git.hsgames.top3000) pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning in between English and Romanian, and between English and German. [184]
<br>GPT-3 considerably improved benchmark results over GPT-2. OpenAI warned that such [scaling-up](https://code.dev.beejee.org) of language designs could be approaching or coming across the essential capability constraints of predictive language designs. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the full 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://www.srapo.com) to permit gain access to through a paid cloud API after a two-month totally free [private](https://gitlab.keysmith.bz) beta that started in June 2020. [170] [189]
<br>On September 23, 2020, GPT-3 was licensed exclusively to Microsoft. [190] [191]
<br>Codex<br>
<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.logicp.ca) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) an API was released in private beta. [194] According to OpenAI, the design can create working code in over a lots shows languages, most successfully in Python. [192]
<br>Several concerns with problems, style defects and security vulnerabilities were cited. [195] [196]
<br>GitHub Copilot has been implicated of giving off copyrighted code, without any author attribution or license. [197]
<br>OpenAI announced that they would stop support for Codex API on March 23, 2023. [198]
<br>GPT-4<br>
<br>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 revealed that the upgraded innovation passed a simulated law school bar test with a score around the leading 10% of test takers. (By contrast, [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:KatrinaPolding1) GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, evaluate or create as much as 25,000 words of text, and write code in all significant programs languages. [200]
<br>Observers reported that the iteration of ChatGPT utilizing 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 modifications. [201] GPT-4 is likewise capable of taking images as input on [ChatGPT](http://208.167.242.1503000). [202] OpenAI has [decreased](https://encone.com) to reveal various technical details and data about GPT-4, such as the exact size of the model. [203]
<br>GPT-4o<br>
<br>On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained cutting edge lead to 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]
<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller [sized variation](http://www.chinajobbox.com) of GPT-4o changing 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 it to be particularly beneficial for enterprises, start-ups and developers seeking to automate services with [AI](https://git.fandiyuan.com) agents. [208]
<br>o1<br>
<br>On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, [larsaluarna.se](http://www.larsaluarna.se/index.php/User:NicholeCoffman) which have been developed to take more time to think of their actions, leading to higher accuracy. These models are especially efficient in science, coding, and [reasoning](https://remote-life.de) tasks, and were made available to ChatGPT Plus and Staff member. [209] [210] In December 2024, o1-preview was replaced by o1. [211]
<br>o3<br>
<br>On December 20, 2024, [it-viking.ch](http://it-viking.ch/index.php/User:TamLivingston31) OpenAI revealed o3, the successor of the o1 thinking model. OpenAI likewise revealed o3-mini, a lighter and much faster variation 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, safety and security scientists had the chance to obtain early access to these models. [214] The design is called o3 rather than o2 to avoid confusion with telecoms providers O2. [215]
<br>Deep research study<br>
<br>Deep research study is an agent developed by OpenAI, unveiled on February 2, 2025. It leverages the abilities of [OpenAI's](https://git.thatsverys.us) o3 model to perform comprehensive web browsing, [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1085161) information analysis, and synthesis, providing 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) criteria. [120]
<br>Image category<br>
<br>CLIP<br>
<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to examine the semantic similarity in between text and images. It can significantly be utilized for image classification. [217]
<br>Text-to-image<br>
<br>DALL-E<br>
<br>Revealed in 2021, DALL-E is a Transformer design that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of a sad capybara") and produce corresponding images. It can produce images of reasonable things ("a stained-glass window with an image of a blue strawberry") as well as [objects](http://115.29.202.2468888) that do not exist in truth ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.<br>
<br>DALL-E 2<br>
<br>In April 2022, OpenAI announced DALL-E 2, an updated variation of the model with more practical results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new fundamental system for transforming a text description into a 3-dimensional model. [220]
<br>DALL-E 3<br>
<br>In September 2023, OpenAI revealed DALL-E 3, a more effective design much better able to produce images from intricate descriptions without manual timely engineering and render intricate details like hands and text. [221] It was [launched](https://www.e-vinil.ro) to the general public as a ChatGPT Plus function in October. [222]
<br>Text-to-video<br>
<br>Sora<br>
<br>Sora is a text-to-video model that can generate videos based on short detailed prompts [223] as well as extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of produced videos is unidentified.<br>
<br>Sora's development team named it after the Japanese word for "sky", to represent its "endless creative potential". [223] Sora's innovation is an adjustment of the technology behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos certified for that purpose, but did not expose the number or the exact sources of the videos. [223]
<br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it could create videos up to one minute long. It also shared a technical report highlighting the techniques utilized to train the model, and the design's capabilities. [225] It acknowledged some of its drawbacks, consisting of struggles imitating intricate physics. [226] Will [Douglas Heaven](https://setiathome.berkeley.edu) of the MIT Technology Review called the demonstration videos "excellent", but noted that they need to have been cherry-picked and might not represent Sora's normal output. [225]
<br>Despite uncertainty from some academic leaders following Sora's public demo, noteworthy entertainment-industry figures have [revealed](http://39.96.8.15010080) significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to generate practical video from text descriptions, mentioning its possible to transform storytelling and content production. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to pause prepare for broadening his Atlanta-based movie studio. [227]
<br>Speech-to-text<br>
<br>Whisper<br>
<br>Released in 2022, Whisper is a general-purpose speech [acknowledgment](http://xn--mf0bm6uh9iu3avi400g.kr) model. [228] It is trained on a large dataset of varied audio and is also a multi-task design that can carry out multilingual speech recognition in addition to speech translation and language recognition. [229]
<br>Music generation<br>
<br>MuseNet<br>
<br>Released in 2019, MuseNet is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can create tunes with 10 instruments in 15 styles. According to The Verge, a [tune produced](https://gitea.evo-labs.org) by MuseNet tends to begin fairly but then fall into chaos the longer it plays. [230] [231] In [popular](https://git.andy.lgbt) culture, preliminary applications of this tool were used as early as 2020 for the web mental thriller Ben Drowned to produce music for the titular character. [232] [233]
<br>Jukebox<br>
<br>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 specified the songs "show regional 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 significant gap" in between [Jukebox](http://gitfrieds.nackenbox.xyz) and human-generated music. The Verge mentioned "It's technically excellent, even if the results sound like mushy versions of songs that might feel familiar", while [Business Insider](https://www.trabahopilipinas.com) stated "surprisingly, a few of the resulting songs are appealing and sound legitimate". [234] [235] [236]
<br>Interface<br>
<br>Debate Game<br>
<br>In 2018, [OpenAI released](https://www.apkjobs.site) the Debate Game, which [teaches machines](https://sossphoto.com) to debate toy problems in front of a human judge. The function is to research whether such a method might assist in auditing [AI](https://git.caraus.tech) choices and in establishing explainable [AI](http://103.77.166.198:3000). [237] [238]
<br>Microscope<br>
<br>Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and nerve cell of eight neural network designs which are typically studied in interpretability. [240] Microscope was created to evaluate the functions that form inside these neural networks easily. The designs included are AlexNet, VGG-19, various variations of Inception, and various variations of CLIP Resnet. [241]
<br>ChatGPT<br>
<br>[Launched](http://82.156.184.993000) in November 2022, [surgiteams.com](https://surgiteams.com/index.php/User:CathleenMadison) ChatGPT is a synthetic intelligence tool built on top of GPT-3 that offers a conversational interface that enables users to ask questions in natural language. The system then responds with a response within seconds.<br>