commit 283e2b5f3e7b4ac727e3d1eadceb8fe5356da1ab Author: stevehumffray Date: Tue Feb 18 03:48:44 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..74119d5 --- /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 [support knowing](http://okosg.co.kr) algorithms. It aimed to standardize how environments are defined in [AI](https://gantnews.com) research, making released research more quickly reproducible [24] [144] while offering users with an easy interface for interacting with these environments. In 2022, new advancements of Gym have actually been transferred to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for support knowing (RL) research on computer game [147] using RL algorithms and research study generalization. Prior RL research focused mainly on [enhancing agents](https://swahilihome.tv) to solve single tasks. Gym Retro provides the capability to generalize between games with similar ideas but various looks.
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RoboSumo
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Released in 2017, [surgiteams.com](https://surgiteams.com/index.php/User:BertHowden) RoboSumo is a [virtual](https://daystalkers.us) world where humanoid metalearning robotic representatives initially lack knowledge of how to even stroll, however are offered the goals of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial learning procedure, the representatives discover how to adjust to altering conditions. When an agent is then removed from this virtual environment and placed in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had learned how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives might produce an intelligence "arms race" that could increase an agent's capability to function even outside the context of the competition. [148] +
OpenAI 5
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OpenAI Five is a group of 5 OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that learn to play against [human gamers](https://www.suntool.top) at a high skill level completely through trial-and-error [algorithms](http://www.thehispanicamerican.com). Before ending up being a group of 5, the first public presentation occurred at The [International](http://121.199.172.2383000) 2017, the yearly best championship competition for the game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg [Brockman](https://dirkohlmeier.de) explained that the bot had learned by playing against itself for 2 weeks of actual time, which the knowing software [application](https://aiviu.app) was an action 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 knowing, as the bots find out 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 objectives. [154] [155] [156] +
By June 2018, the capability of the bots broadened to play together as a complete group of 5, and they were able to defeat 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 video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs of the video game at the time, 2:0 in a live exhibit match in [San Francisco](https://trulymet.com). [163] [164] The bots' last public look 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](http://120.46.37.2433000). [165] +
OpenAI 5's systems in Dota 2's bot gamer shows the difficulties of [AI](https://aiviu.app) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually demonstrated making use of deep support knowing (DRL) [representatives](https://solegeekz.com) to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes machine discovering to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It learns totally in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI took on the things orientation problem by utilizing domain randomization, a simulation technique which exposes the learner to a [variety](https://laviesound.com) of experiences instead of attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking cams, also has RGB electronic cameras to enable the robot to manipulate an approximate 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 demonstrated that Dactyl could fix a Rubik's Cube. The robotic 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 robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating progressively more difficult environments. ADR differs from manual [domain randomization](http://101.43.248.1843000) by not requiring a human to define randomization varieties. [169] +
API
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In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](http://www.chemimart.kr) designs developed by OpenAI" to let [developers](http://cjma.kr) call on it for "any English language [AI](http://n-f-l.jp) task". [170] [171] +
Text generation
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The business has actually promoted generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT model ("GPT-1")
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The original paper on generative pre-training of a [transformer-based language](https://villahandle.com) model was composed by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world knowledge and process long-range dependencies by pre-training on a varied corpus with long stretches of adjoining text.
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GPT-2
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Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language model and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative variations at first launched to the general public. The full version of GPT-2 was not immediately released due to concern about potential misuse, including applications for writing fake news. [174] Some professionals [revealed uncertainty](https://www.guidancetaxdebt.com) that GPT-2 posed a substantial danger.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence [responded](http://www.carnevalecommunity.it) with a tool to detect "neural fake news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be difficult to filter". [176] In November 2019, OpenAI released the complete version of the GPT-2 language model. [177] Several sites host interactive presentations of different instances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue without supervision language designs to be general-purpose students, shown by GPT-2 attaining cutting edge accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not more trained on any task-specific input-output examples).
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The corpus it was trained on, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain issues encoding vocabulary with word tokens by using byte pair encoding. This permits representing any string of characters by encoding both individual 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 language model and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full version of GPT-3 [contained](https://followgrown.com) 175 billion criteria, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as few as 125 million parameters were also trained). [186] +
OpenAI specified that GPT-3 prospered at certain "meta-learning" jobs and could generalize the function 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 between English and German. [184] +
GPT-3 considerably improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or coming across the fundamental capability constraints of predictive language models. [187] Pre-training GPT-3 needed numerous 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 model was not right away launched to the public for concerns of possible abuse, although OpenAI planned to allow gain access to through a [paid cloud](https://heovktgame.club) API after a two-month complimentary personal beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was [certified](https://git.numa.jku.at) solely to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://tigg.1212321.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can develop working code in over a dozen shows languages, most effectively in Python. [192] +
Several concerns with problems, design flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been accused of producing copyrighted code, without any author [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11861831) attribution or license. [197] +
OpenAI revealed that they would terminate assistance for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text 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 approximately 25,000 words of text, and compose code in all major programs languages. [200] +
Observers reported that the iteration of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based model, with the caveat 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 actually declined to reveal different technical details and data 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 launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained advanced outcomes in voice, multilingual, and vision criteria, setting brand-new records in audio speech acknowledgment and [translation](https://galmudugjobs.com). [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, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:LoisHuntley) OpenAI released GPT-4o mini, a smaller sized variation of GPT-4o [replacing](https://ysa.sa) 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, startups and developers looking for to automate services with [AI](https://www.assistantcareer.com) agents. [208] +
o1
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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 reactions, resulting in higher precision. These designs are especially reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was changed by o1. [211] +
o3
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On December 20, 2024, OpenAI revealed o3, the successor of the o1 [thinking design](http://47.93.56.668080). OpenAI also revealed o3-mini, a lighter and much faster version of OpenAI o3. As of December 21, 2024, this model is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the chance to obtain early access to these designs. [214] The model is called o3 instead of o2 to avoid confusion with [telecoms providers](http://107.172.157.443000) O2. [215] +
Deep research study
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Deep research study is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to perform extensive web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and [wiki.rolandradio.net](https://wiki.rolandradio.net/index.php?title=User:MaxMcAulay008) Python tools made it possible for, it reached an accuracy 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 evaluate 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 model](https://jobs.com.bn) that creates images from textual descriptions. [218] DALL-E uses 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 a sad capybara") and generate matching images. It can produce pictures of realistic things ("a stained-glass window with an image of a blue strawberry") along with [objects](https://laviesound.com) that do not exist in truth ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.
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DALL-E 2
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In April 2022, OpenAI revealed DALL-E 2, an upgraded variation of the design with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new basic system for transforming a text description into a 3[-dimensional model](https://wiki.contextgarden.net). [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more effective model better able to produce images from intricate descriptions without manual prompt engineering and render intricate details like hands and text. [221] It was launched to the general public as a ChatGPT Plus function in October. [222] +
Text-to-video
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Sora
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Sora is a text-to-video model that can generate videos based upon brief detailed triggers [223] in addition to extend existing videos forwards or in [reverse](https://www.cvgods.com) in time. [224] It can create videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of created videos is unknown.
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Sora's development group called it after the Japanese word for "sky", to [signify](http://154.40.47.1873000) its "endless imaginative capacity". [223] Sora's technology is an adaptation of the technology behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos along with certified for that purpose, however did not expose the number or the [precise sources](http://www.book-os.com3000) of the videos. [223] +
OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it could generate videos approximately one minute long. It also shared a technical report highlighting the techniques used to train the model, and the [design's capabilities](https://www.sportfansunite.com). [225] It acknowledged some of its imperfections, consisting of struggles replicating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", but kept in mind that they need to have been cherry-picked and may not represent Sora's common output. [225] +
Despite uncertainty from some academic leaders following Sora's public demonstration, notable entertainment-industry [figures](https://www.xcoder.one) have revealed considerable interest in the [technology's](https://bvbborussiadortmundfansclub.com) capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the [technology's ability](http://47.94.142.23510230) to create reasonable video from text descriptions, mentioning its prospective to [transform storytelling](http://81.70.25.1443000) and content creation. He said that his excitement about Sora's possibilities was so strong that he had chosen to stop briefly prepare for broadening his Atlanta-based film studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, Whisper is a general-purpose speech [acknowledgment](https://talentrendezvous.com) design. [228] It is trained on a large dataset of diverse audio and is likewise a multi-task model that can perform 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 anticipate subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to begin fairly however then fall under mayhem the longer it plays. [230] [231] In pop culture, initial applications of this tool were used as early as 2020 for the internet mental thriller Ben Drowned to create music for the titular character. [232] [233] +
Jukebox
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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 tune samples. OpenAI mentioned the tunes "show local musical coherence [and] follow traditional chord patterns" however 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 mentioned "It's technologically excellent, even if the results seem like mushy versions of songs that may feel familiar", while [Business Insider](http://team.pocketuniversity.cn) stated "surprisingly, some of the resulting tunes are appealing and sound genuine". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, OpenAI launched the Debate Game, which teaches makers to discuss toy problems in front of a human judge. The function is to research study whether such a method might help in auditing [AI](http://gitea.anomalistdesign.com) choices and in establishing explainable [AI](https://git.clicknpush.ca). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every significant layer and nerve cell of eight neural network models which are frequently studied in interpretability. [240] Microscope was developed to analyze the features that form inside these neural networks easily. The designs included are AlexNet, VGG-19, different versions of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is a synthetic intelligence tool built on top of GPT-3 that provides a conversational user interface that permits users to ask concerns in natural language. The system then responds with a response within seconds.
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