From 6f7bd4d5bac9429bd04e041c4b0334677b6d9b6e Mon Sep 17 00:00:00 2001 From: Aidan Kleiman Date: Mon, 7 Apr 2025 12:15:59 +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..537672f --- /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 developed to assist in the development of support knowing algorithms. It aimed to standardize how environments are specified in [AI](http://209.141.61.26:3000) research study, making published research more quickly reproducible [24] [144] while supplying users with a [simple interface](https://pipewiki.org) for [interacting](https://gitea.baxir.fr) with these environments. In 2022, brand-new advancements of Gym have been moved to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research on computer game [147] using RL algorithms and research study generalization. Prior RL research focused mainly on optimizing agents to resolve single tasks. Gym Retro offers the [capability](http://47.99.119.17313000) to generalize between video games with comparable ideas however different looks.
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RoboSumo
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Released in 2017, RoboSumo is a [virtual](https://jobs.fabumama.com) world where humanoid metalearning robot representatives initially lack understanding of how to even walk, however are provided the goals of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the representatives learn how to adjust to altering conditions. When an agent is then removed from this virtual environment and placed in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had actually learned how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that [competition](https://partyandeventjobs.com) in between representatives could [develop](https://skillfilltalent.com) an intelligence "arms race" that could increase an agent's ability to work even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that find out to play against human gamers at a high skill level totally through experimental algorithms. Before becoming a group of 5, the very first public presentation occurred at The International 2017, the annual best [champion tournament](https://dztrader.com) for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for two weeks of actual time, and that the learning software was an action in the direction of producing software application that can handle complicated jobs like a surgeon. [152] [153] The system uses a kind of support learning, as the bots discover gradually by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an opponent and taking map objectives. [154] [155] [156] +
By June 2018, the capability of the bots expanded to play together as a complete team of 5, and they were able 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, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champs of the [video game](http://www.mitt-slide.com) at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public look came later on that month, where they played in 42,729 total video games in a [four-day](https://macphersonwiki.mywikis.wiki) open online competitors, winning 99.4% of those video games. [165] +
OpenAI 5's systems in Dota 2's bot gamer reveals the challenges of [AI](https://letustalk.co.in) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has demonstrated making use of deep support knowing (DRL) agents to attain superhuman skills in Dota 2 [matches](http://www.xyais.cn). [166] +
Dactyl
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[Developed](http://www.s-golflex.kr) in 2018, Dactyl uses maker discovering to train a Shadow Hand, [christianpedia.com](http://christianpedia.com/index.php?title=User:KeishaClifton49) a human-like robotic hand, to manipulate physical items. [167] It learns entirely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI tackled the [object orientation](http://124.222.85.1393000) issue by using domain randomization, a simulation technique which exposes the learner to a variety of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having movement tracking cameras, also has RGB video cameras to permit the robot to control an approximate object 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 solve a Rubik's Cube. The robot had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated [physics](https://deadlocked.wiki) 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 creating gradually harder environments. ADR differs from manual domain randomization by not needing a human to specify randomization ranges. [169] +
API
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In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](https://somalibidders.com) models developed by OpenAI" to let [designers](http://118.89.58.193000) get in touch with it for "any English language [AI](https://hub.tkgamestudios.com) job". [170] [171] +
Text generation
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The business has promoted generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT design ("GPT-1")
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The original paper on generative pre-training of a transformer-based language design was written by Alec Radford and his coworkers, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world understanding and process 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 design and the successor to OpenAI's initial GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative versions initially launched to the public. The full variation of GPT-2 was not immediately launched due to concern about potential misuse, consisting of applications for writing fake news. [174] Some professionals revealed uncertainty that GPT-2 posed a considerable danger.
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In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "neural fake news". [175] Other researchers, such as Jeremy Howard, cautioned of "the innovation to absolutely 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 design. [177] Several sites host interactive demonstrations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being watched language models to be general-purpose students, shown by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not additional trained on any task-specific input-output examples).
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The corpus it was trained on, called WebText, contains somewhat 40 gigabytes of text from URLs shared in Reddit submissions with at least 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 specific characters and multiple-character tokens. [181] +
GPT-3
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First explained in May 2020, [Generative Pre-trained](https://globalhospitalitycareer.com) [a] Transformer 3 (GPT-3) is a not being watched transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI stated that the full version of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as couple of as 125 million parameters were also trained). [186] +
OpenAI mentioned that GPT-3 prospered at certain "meta-learning" tasks and might [generalize](https://homejobs.today) 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 significantly [improved benchmark](https://skillfilltalent.com) results over GPT-2. OpenAI cautioned that such scaling-up of language models might be approaching or encountering the essential ability constraints of predictive language models. [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 model. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly released to the general public for concerns of possible abuse, although OpenAI planned 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](http://git.agdatatec.com) exclusively to Microsoft. [190] [191] +
Codex
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Announced in mid-2021, Codex is a descendant of GPT-3 that has additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://innovator24.com) 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 create working code in over a dozen shows languages, a lot of effectively in Python. [192] +
Several issues with glitches, design flaws and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been accused of producing copyrighted code, without any author attribution or license. [197] +
OpenAI revealed 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 or image inputs. [199] They revealed that the upgraded innovation passed a simulated law school bar exam with a rating around the leading 10% of [test takers](https://18plus.fun). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, analyze or create approximately 25,000 words of text, and compose code in all significant programs languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 retained some of the problems with earlier revisions. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has decreased to reveal different 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 generate text, images and audio. [204] GPT-4o attained state-of-the-art lead to voice, multilingual, and vision benchmarks, setting new records in audio speech acknowledgment and . [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 version 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 business, startups and developers seeking to automate services with [AI](http://travelandfood.ru) agents. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have actually been created to take more time to think of their actions, resulting in greater precision. These designs are particularly effective in science, coding, and reasoning jobs, 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 unveiled o3, the follower of the o1 thinking model. OpenAI also revealed o3-mini, a lighter and much [faster variation](https://quikconnect.us) of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the opportunity to obtain early access to these models. [214] The design is called o3 instead of o2 to avoid confusion with telecoms providers O2. [215] +
Deep research study
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Deep research study is an [agent established](http://49.235.101.2443001) by OpenAI, unveiled on February 2, 2025. It leverages the abilities 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 searching and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [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](https://git.sitenevis.com) to examine the semantic similarity in between text and images. It can notably be utilized for image category. [217] +
Text-to-image
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DALL-E
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Revealed in 2021, DALL-E is a Transformer model that creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and generate corresponding images. It can produce pictures of realistic things ("a stained-glass window with an image of a blue strawberry") along with things that do not exist in reality ("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 version of the design with more practical outcomes. [219] In December 2022, OpenAI released 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 model much better able to produce images from intricate descriptions without manual prompt engineering and render complex details like hands and text. [221] It was launched to the 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 design that can create videos based on brief detailed triggers [223] as well as extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of generated videos is unknown.
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Sora's development group called it after the Japanese word for "sky", to signify its "unlimited innovative potential". [223] Sora's innovation is an adaptation of the innovation behind the DALL ยท E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos certified for that purpose, however did not expose the number or the precise 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 produce videos approximately one minute long. It likewise shared a technical report highlighting the methods used to train the model, and the design's abilities. [225] It acknowledged some of its imperfections, including battles replicating intricate physics. [226] Will Douglas Heaven of the MIT [Technology Review](https://www.codple.com) called the presentation videos "excellent", however kept in mind that they must have been [cherry-picked](http://www.chinajobbox.com) and may not represent Sora's typical output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demonstration, notable entertainment-industry figures have actually shown substantial interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his awe at the [technology's capability](http://gitlab.ds-s.cn30000) to produce practical video from text descriptions, citing its prospective to reinvent storytelling and material development. He said that his excitement about Sora's possibilities was so strong that he had chosen to pause 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 recognition design. [228] It is trained on a large dataset of diverse audio and is also a multi-task model that can carry out multilingual speech recognition 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 tunes with 10 instruments in 15 designs. According to The Verge, a tune produced by MuseNet tends to [start fairly](https://memorial-genweb.org) but then fall into chaos the longer it plays. [230] [231] In popular culture, [initial applications](https://www.h2hexchange.com) of this tool were utilized as early as 2020 for the web psychological 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 create music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs song samples. OpenAI stated the songs "show regional musical coherence [and] follow conventional chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that duplicate" which "there is a considerable space" between Jukebox and human-generated music. The Verge stated "It's highly remarkable, even if the results sound like mushy versions of songs that may feel familiar", while [Business Insider](http://drive.ru-drive.com) mentioned "surprisingly, a few of the resulting songs are memorable and sound legitimate". [234] [235] [236] +
Interface
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Debate Game
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In 2018, OpenAI introduced the Debate Game, which teaches devices to discuss toy problems in front of a human judge. The purpose is to research study whether such a method may help in auditing [AI](https://centerfairstaffing.com) choices and in establishing explainable [AI](https://japapmessenger.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of [visualizations](https://joydil.com) of every substantial layer and nerve cell of eight neural network designs which are frequently studied in interpretability. [240] Microscope was produced to examine the features that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, various versions of Inception, and various variations of [CLIP Resnet](https://owangee.com). [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that provides a conversational interface that allows users to ask questions in natural language. The system then reacts with an answer within seconds.
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