commit 6bb9c36e7a18326736ff4d5fff77c35b760d5603 Author: leonoremutch78 Date: Sun Feb 16 14:14:33 2025 +0800 Add The Verge Stated It's Technologically Impressive 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..b2d8d04 --- /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 learning algorithms. It aimed to standardize how environments are [defined](https://raisacanada.com) in [AI](https://git.muhammadfahri.com) research study, [links.gtanet.com.br](https://links.gtanet.com.br/roymckelvey) making published research study more easily reproducible [24] [144] while offering users with a basic user interface for connecting with these environments. In 2022, brand-new advancements of Gym have been relocated to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support learning (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on enhancing agents to solve single jobs. Gym Retro gives the capability to generalize between video games with similar concepts but various looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot representatives at first do not have knowledge of how to even stroll, but are given the objectives of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the agents discover how to adjust to [altering conditions](https://magnusrecruitment.com.au). When a representative is then removed from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had learned how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition in between agents could produce an intelligence "arms race" that might increase a to work even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that find out to play against human gamers at a high skill level completely through experimental algorithms. Before ending up being a team of 5, the very first public demonstration took place at The International 2017, the yearly premiere champion [competition](https://www.thewaitersacademy.com) for the video game, where Dendi, an expert Ukrainian player, 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](https://enitajobs.com) against itself for two weeks of actual time, and that the learning software application was a step in the direction of producing software application that can deal with complicated jobs like a cosmetic surgeon. [152] [153] The system uses a kind of reinforcement knowing, as the bots discover in time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an opponent and taking map goals. [154] [155] [156] +
By June 2018, the capability of the bots broadened to play together as a complete group of 5, and they had the ability to defeat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert gamers, however wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champs of the game at the time, [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:DamianWren8429) 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 overall games in a four-day open online competition, winning 99.4% of those games. [165] +
OpenAI 5's systems in Dota 2's bot gamer shows the [obstacles](https://www.valenzuelatrabaho.gov.ph) of [AI](http://www.visiontape.com) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually demonstrated making use of deep reinforcement knowing (DRL) agents to attain superhuman proficiency in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes machine finding out to train a Shadow Hand, a human-like robot hand, to control physical [objects](https://amorweddfair.com). [167] It finds out totally in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI dealt with the things orientation issue by utilizing domain randomization, a simulation technique which exposes the student to a range of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking video cameras, also has RGB video cameras to enable the robot to manipulate an approximate things by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl could fix a Rubik's Cube. The robot was able to fix the puzzle 60% of the time. Objects like the [Rubik's Cube](https://somo.global) present intricate physics that is harder to model. OpenAI did this by improving the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of producing gradually harder environments. ADR varies from manual domain randomization by not needing a human to define randomization ranges. [169] +
API
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In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](http://carpetube.com) designs established by OpenAI" to let developers contact it for "any English language [AI](https://www.greenpage.kr) task". [170] [171] +
Text generation
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The company has popularized generative pretrained transformers (GPT). [172] +
OpenAI's original GPT model ("GPT-1")
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The original paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his associates, and released in preprint on [OpenAI's website](https://63game.top) on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world understanding and procedure long-range reliances by pre-training on a diverse corpus with long stretches of contiguous text.
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GPT-2
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Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer [language](http://dev.ccwin-in.com3000) model and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just minimal demonstrative versions at first released to the public. The complete variation of GPT-2 was not right away released due to issue about possible abuse, including applications for writing fake news. [174] Some experts expressed uncertainty that GPT-2 positioned a substantial risk.
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In [reaction](https://uptoscreen.com) to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural phony news". [175] Other researchers, such as Jeremy Howard, cautioned of "the innovation to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out 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 different instances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue without supervision language models to be general-purpose students, illustrated by GPT-2 attaining state-of-the-art 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).
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The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain problems 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
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First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being [watched transformer](https://empleosmarketplace.com) 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 bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were also trained). [186] +
OpenAI mentioned that GPT-3 prospered at certain "meta-learning" tasks and could generalize the purpose of a [single input-output](https://gogs.koljastrohm-games.com) pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning in between English and Romanian, and in between English and German. [184] +
GPT-3 drastically enhanced benchmark outcomes 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 10s of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly released to the public for issues of possible abuse, although OpenAI prepared to permit 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 specifically to Microsoft. [190] [191] +
Codex
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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://rubius-qa-course.northeurope.cloudapp.azure.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the model can create working code in over a lots shows languages, many [efficiently](https://jobstaffs.com) in Python. [192] +
Several concerns with problems, design defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been accused of emitting copyrighted code, without any author attribution or license. [197] +
OpenAI announced that they would cease assistance for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in [accepting text](http://easyoverseasnp.com) or image inputs. [199] They revealed that the updated innovation passed a simulated law school bar exam 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 could likewise check out, evaluate or produce as much as 25,000 words of text, and write code in all significant shows languages. [200] +
Observers reported that the version 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 revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has decreased to reveal various technical details and statistics about GPT-4, such as the accurate size of the model. [203] +
GPT-4o
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On May 13, 2024, OpenAI announced and released GPT-4o, which can process and create text, [forum.pinoo.com.tr](http://forum.pinoo.com.tr/profile.php?id=1324171) images and audio. [204] GPT-4o attained modern results in voice, multilingual, and vision benchmarks, 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 launched 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 it to be especially useful for business, startups and designers seeking to automate services with [AI](https://cl-system.jp) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have been designed to take more time to consider their actions, resulting in higher [accuracy](https://63game.top). These models are particularly effective in science, coding, [yewiki.org](https://www.yewiki.org/User:TristanSumner) and reasoning tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was replaced by o1. [211] +
o3
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On December 20, 2024, [OpenAI unveiled](https://test1.tlogsir.com) o3, the successor of the o1 thinking model. OpenAI also revealed o3-mini, a lighter and faster version of OpenAI o3. Since December 21, 2024, this model is not available for [public usage](https://www.nenboy.com29283). 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 avoid [confusion](https://git.itk.academy) with telecoms services provider O2. [215] +
Deep research study
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Deep research study is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out substantial web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools made it possible for, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] +
Image classification
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CLIP
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Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to analyze the semantic similarity in between text and images. It can notably be used for image classification. [217] +
Text-to-image
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DALL-E
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Revealed in 2021, DALL-E is a [Transformer design](http://team.pocketuniversity.cn) that produces 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 purse shaped like a pentagon" or "an isometric view of a sad capybara") and [generate matching](https://sansaadhan.ipistisdemo.com) images. It can produce pictures of reasonable things ("a stained-glass window with an image of a blue strawberry") in addition to objects that do not exist in reality ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.
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DALL-E 2
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In April 2022, OpenAI announced DALL-E 2, an upgraded variation of the model with more sensible outcomes. [219] In December 2022, OpenAI published on GitHub software for Point-E, a new fundamental system for converting a text description into a 3-dimensional model. [220] +
DALL-E 3
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In September 2023, OpenAI revealed DALL-E 3, a more powerful design much better able to produce images from complicated descriptions without manual prompt engineering and render [complicated details](https://git.yingcaibx.com) like hands and text. [221] It was released to the public as a ChatGPT Plus [feature](https://prime-jobs.ch) in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video design that can generate videos based upon short detailed prompts [223] along with extend existing videos forwards or in reverse in time. [224] It can generate videos with [resolution](https://www.a34z.com) up to 1920x1080 or 1080x1920. The maximal length of [produced videos](https://demo.shoudyhosting.com) is unknown.
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Sora's development group named it after the Japanese word for "sky", to symbolize its "limitless imaginative potential". [223] Sora's technology 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 certified for that purpose, however did not reveal 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 could 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 a few of its drawbacks, consisting of [battles mimicing](https://privamaxsecurity.co.ke) intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "excellent", however kept in mind that they must have been [cherry-picked](https://wiki.vifm.info) and might not represent Sora's common output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demonstration, notable entertainment-industry figures have shown significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's ability to generate realistic video from text descriptions, citing its potential to change storytelling and content creation. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to pause strategies for broadening his Atlanta-based film studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, [Whisper](https://horizonsmaroc.com) is a general-purpose speech acknowledgment model. [228] It is trained on a big dataset of diverse audio and is also a multi-task model that can carry out multilingual speech acknowledgment in addition to speech translation and language recognition. [229] +
Music generation
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MuseNet
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Released in 2019, MuseNet is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to start fairly but then fall under mayhem the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were utilized as early as 2020 for the [internet mental](http://gkpjobs.com) thriller Ben Drowned to develop music for the titular character. [232] [233] +
Jukebox
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Released in 2020, Jukebox is an open-sourced algorithm to create 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 tunes "reveal regional musical coherence [and] follow traditional 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" between Jukebox and human-generated music. The Verge stated "It's technically excellent, even if the outcomes sound like mushy versions of songs that might feel familiar", while Business Insider specified "surprisingly, some of the resulting tunes are catchy and sound genuine". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI introduced the Debate Game, which teaches makers to discuss toy problems in front of a human judge. The function is to research whether such an approach may help in auditing [AI](https://runningas.co.kr) decisions and in developing explainable [AI](http://182.92.196.181). [237] [238] +
Microscope
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Released in 2020, [forum.pinoo.com.tr](http://forum.pinoo.com.tr/profile.php?id=1324005) Microscope [239] is a collection of visualizations of every substantial layer and neuron of eight neural network models which are often 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, different variations of Inception, and different variations of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an artificial intelligence tool constructed on top of GPT-3 that supplies a conversational user interface that permits users to ask questions in natural language. The system then responds with an answer within seconds.
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