From 065d51e399ff6412058364ea690702e61b58df60 Mon Sep 17 00:00:00 2001 From: Albertina Mauldon Date: Sun, 23 Feb 2025 00:18:00 +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..4ade814 --- /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 designed to assist in the advancement of support knowing algorithms. It aimed to standardize how environments are defined in [AI](http://150.158.93.145:3000) research study, making published research study more easily reproducible [24] [144] while providing users with an easy interface for interacting with these environments. In 2022, brand-new developments of Gym have actually been moved to the library Gymnasium. [145] [146] +
Gym Retro
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Released in 2018, Gym Retro is a [platform](https://git.bugi.si) for support learning (RL) research on video games [147] using RL algorithms and study generalization. Prior RL research focused mainly on enhancing representatives to resolve single jobs. Gym Retro provides the capability to generalize between video games with similar ideas but various looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents initially lack understanding of how to even stroll, but are offered the objectives of finding out to move and to push the opposing agent out of the ring. [148] Through this adversarial learning procedure, the agents learn how to adjust to altering conditions. When an agent is then eliminated from this virtual environment and positioned in a new virtual environment with high winds, the representative braces to remain upright, recommending it had found out how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that [competitors](https://gitea.lelespace.top) in between representatives might create 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 team of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that learn to play against human gamers at a high skill level totally through trial-and-error algorithms. Before ending up being a group of 5, the very first public presentation occurred at The International 2017, the yearly premiere championship competition for the video game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live one-on-one [matchup](http://193.200.130.1863000). [150] [151] After the match, CTO Greg [Brockman explained](https://git.buzhishi.com14433) that the bot had learned by playing against itself for 2 weeks of genuine time, and that the learning software application was a step in the direction of producing software application that can handle intricate tasks like a surgeon. [152] [153] The system utilizes a form of support learning, as the bots learn over time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an enemy and taking map goals. [154] [155] [156] +
By June 2018, the ability of the bots broadened to play together as a complete team of 5, and they had the ability to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two [exhibition matches](http://osbzr.com) against expert gamers, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champions of the video game 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 overall games in a four-day open online competitors, winning 99.4% of those video games. [165] +
OpenAI 5['s systems](http://www.hydrionlab.com) in Dota 2's bot gamer shows the difficulties of [AI](https://gitea.evo-labs.org) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has actually shown making use of deep reinforcement knowing (DRL) agents to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses machine discovering to train a Shadow Hand, a human-like robot hand, to manipulate physical things. [167] It finds out completely in simulation using the very same RL algorithms and [training code](https://hitechjobs.me) as OpenAI Five. OpenAI tackled the object orientation problem by using domain randomization, a simulation technique which exposes the [student](https://ukcarers.co.uk) to a range of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking cameras, also has RGB electronic cameras to enable the robotic to manipulate an arbitrary things by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robotic was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present complicated physics that is harder to design. OpenAI did this by improving the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation approach of generating progressively 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 announced a multi-purpose API which it said was "for accessing new [AI](https://projobs.dk) designs established by OpenAI" to let designers call on it for "any English language [AI](https://jamboz.com) job". [170] [171] +
Text generation
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The company has promoted 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](https://www.womplaz.com) design was composed by Alec Radford and his colleagues, and released in preprint on OpenAI's site on June 11, 2018. [173] It showed how a generative design of language could obtain world knowledge and procedure long-range dependences by pre-training on a varied 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 a without supervision transformer language design and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only minimal demonstrative variations at first released to the general public. The complete version of GPT-2 was not right away released due to issue about prospective misuse, consisting of applications for [composing fake](https://bd.cane-recruitment.com) news. [174] Some experts expressed uncertainty that GPT-2 [postured](https://www.mafiscotek.com) a significant hazard.
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In action to GPT-2, the Allen [Institute](https://convia.gt) for Artificial Intelligence responded with a tool to [discover](http://13.213.171.1363000) "neural phony news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation to totally 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 released the complete version of the GPT-2 language design. [177] Several websites host interactive demonstrations of different circumstances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue without supervision 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 design was not additional trained on any task-specific input-output examples).
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The corpus it was trained on, [wiki.whenparked.com](https://wiki.whenparked.com/User:Bernadette71H) 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 [a] Transformer 3 (GPT-3) is a not being watched transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI specified that the full variation of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as few as 125 million parameters were also trained). [186] +
[OpenAI stated](http://barungogi.com) that GPT-3 was successful at certain "meta-learning" jobs and could generalize the purpose of a single input-output 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 improved [benchmark](https://employmentabroad.com) outcomes over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or experiencing the fundamental ability constraints of predictive language models. [187] [Pre-training](https://pelangideco.com) GPT-3 required numerous thousand petaflop/s-days [b] of compute, compared to tens 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](https://swaggspot.com) to allow gain access to through a paid cloud API after a two-month free personal beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed exclusively 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](https://yourgreendaily.com) [powering](https://owangee.com) the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can produce working code in over a dozen programs languages, a lot of efficiently in Python. [192] +
Several concerns with glitches, style defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has actually been implicated of releasing copyrighted code, with no author attribution or license. [197] +
OpenAI revealed that they would cease support for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI announced the [release](https://wiki.atlantia.sca.org) of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school [bar test](http://update.zgkw.cn8585) with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, examine or [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:Natisha96L) produce up to 25,000 words of text, and write code in all significant programming languages. [200] +
Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based model, with the caveat that GPT-4 [retained](http://121.40.81.1163000) some of the problems with earlier [revisions](http://117.72.39.1253000). [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has actually decreased to expose various 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, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2684771) OpenAI announced and released GPT-4o, which can process and produce text, images and audio. [204] GPT-4o [attained cutting](https://www.frigorista.org) edge lead to voice, multilingual, and vision standards, setting brand-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] +
On July 18, 2024, OpenAI launched GPT-4o mini, a smaller sized variation of GPT-4o changing 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 beneficial for enterprises, startups and developers seeking to automate services with [AI](http://enhr.com.tr) representatives. [208] +
o1
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On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have actually been created to take more time to believe about their reactions, causing greater precision. These designs are particularly effective in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [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 design. OpenAI likewise unveiled o3-mini, a lighter and [quicker variation](http://maitri.adaptiveit.net) 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, security and security researchers had the opportunity to obtain early access to these designs. [214] The model is called o3 rather than o2 to avoid confusion with telecommunications providers O2. [215] +
Deep research
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Deep research is a representative established by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform comprehensive web browsing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] +
Image category
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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 between text and images. It can especially 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 utilizes a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather purse formed like a pentagon" or "an isometric view of a sad capybara") and produce corresponding images. It can develop pictures of practical things ("a stained-glass window with a picture of a blue strawberry") in addition to items that do not exist in reality ("a cube with the texture of a porcupine"). As of March 2021, no API or [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:SashaJ9843126) code is available.
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DALL-E 2
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In April 2022, [OpenAI revealed](https://cello.cnu.ac.kr) DALL-E 2, [disgaeawiki.info](https://disgaeawiki.info/index.php/User:AntoinetteLizott) an upgraded variation of the design with more practical results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new basic system for [converting](http://27.154.233.18610080) a text description into a 3-dimensional model. [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more effective model better able to create images from intricate descriptions without manual prompt engineering and render complex details like hands and text. [221] It was released to the general public as a ChatGPT Plus feature in October. [222] +
Text-to-video
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Sora
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Sora is a [text-to-video model](https://wp.nootheme.com) that can produce videos based on short detailed prompts [223] along with extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of created videos is unidentified.
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Sora's advancement team named it after the Japanese word for "sky", to represent its "limitless creative potential". [223] Sora's technology is an adaptation of the innovation behind the DALL ยท E 3 [text-to-image design](https://iadgroup.co.uk). [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos [licensed](https://ouptel.com) for that function, but did not expose the number or the exact 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 generate videos approximately one minute long. It likewise shared a technical report highlighting the approaches utilized to train the design, and the model's capabilities. [225] It acknowledged a few of its shortcomings, consisting of struggles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "remarkable", but noted that they should have been cherry-picked and may not represent Sora's typical output. [225] +
Despite [uncertainty](https://samisg.eu8443) from some scholastic leaders following Sora's public demo, noteworthy entertainment-industry figures have actually shown considerable interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's ability to generate practical video from text descriptions, citing its prospective to change storytelling and content creation. He said that his enjoyment about Sora's possibilities was so strong that he had decided to stop briefly prepare for expanding his [Atlanta-based movie](https://talentsplendor.com) studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, [Whisper](https://aidesadomicile.ca) is a general-purpose speech recognition design. [228] It is trained on a large dataset of diverse audio and is also a multi-task design that can carry out multilingual speech acknowledgment as well as speech translation and language identification. [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 generate tunes with 10 instruments in 15 designs. According to The Verge, a song generated by MuseNet tends to [start fairly](https://woowsent.com) however then fall into chaos the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the internet mental thriller Ben [Drowned](https://comunidadebrasilbr.com) to develop 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 genre, artist, and a bit of lyrics and outputs song samples. OpenAI specified the tunes "show local musical coherence [and] follow conventional chord patterns" however 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 specified "It's technically outstanding, even if the results sound like mushy versions of songs that might feel familiar", while Business Insider 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 makers to dispute toy problems in front of a human judge. The function is to research whether such a method may help in auditing [AI](http://123.207.52.103:3000) decisions and in establishing explainable [AI](https://asesordocente.com). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of 8 neural network models which are frequently studied in interpretability. [240] Microscope was created to [analyze](http://www.jacksonhampton.com3000) the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various versions of Inception, and various versions of CLIP Resnet. [241] +
ChatGPT
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Launched in November 2022, ChatGPT is an artificial intelligence tool built on top of GPT-3 that supplies 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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