From 407ef8ea78b7d48b07a85d04df068991be18f5b8 Mon Sep 17 00:00:00 2001 From: Adeline Charteris Date: Fri, 11 Apr 2025 07:01:13 +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..c595a67 --- /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 advancement of reinforcement learning algorithms. It aimed to [standardize](https://playvideoo.com) how environments are defined in [AI](http://dev.onstyler.net:30300) research, making released research study more quickly reproducible [24] [144] while providing users with an easy user interface for interacting with these environments. In 2022, new advancements of Gym have been [transferred](https://adrian.copii.md) 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 on video games [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on enhancing agents to resolve single tasks. Gym Retro offers the capability to generalize between video games with similar ideas however various appearances.
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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 understanding of how to even walk, but are given the objectives of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing process, the representatives learn how to adapt to altering conditions. When an agent is then eliminated from this virtual environment and placed in a brand-new virtual environment with high winds, the agent braces to remain upright, recommending it had actually [learned](https://choosy.cc) how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between agents could develop an intelligence "arms race" that could increase an agent's ability to function even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a team of 5 OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that learn to play against [human gamers](https://radicaltarot.com) at a high ability level completely through trial-and-error algorithms. Before ending up being a group of 5, the very first public presentation took place at The International 2017, the annual premiere champion competition for the video game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live one-on-one matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for two weeks of actual time, and that the knowing software was an action in the direction of developing software application that can handle complex jobs like a surgeon. [152] [153] The system utilizes a kind of reinforcement knowing, as the bots learn with time by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an opponent and taking map goals. [154] [155] [156] +
By June 2018, the ability of the bots broadened to play together as a full team of 5, and they had the ability to defeat teams of [amateur](http://gitlab.hanhezy.com) and [pipewiki.org](https://pipewiki.org/wiki/index.php/User:AurelioHamlin79) semi-professional players. [157] [154] [158] [159] At The [International](http://34.81.52.16) 2018, OpenAI Five played in two exhibit matches against expert gamers, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champs 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 competitors, winning 99.4% of those video games. [165] +
OpenAI 5's systems in Dota 2's bot gamer reveals the challenges of [AI](http://47.93.156.192:7006) systems in multiplayer online [battle arena](http://47.100.81.115) (MOBA) video games and how OpenAI Five has actually shown the usage of deep support knowing (DRL) representatives to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl uses [device discovering](https://earlyyearsjob.com) to train a Shadow Hand, a human-like robotic hand, to manipulate physical items. [167] It learns entirely in simulation using the exact same [RL algorithms](https://akrs.ae) and training code as OpenAI Five. OpenAI tackled the item orientation issue by utilizing domain randomization, a simulation approach which exposes the student to a variety of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having motion tracking electronic cameras, also has RGB video cameras to allow the robotic to manipulate an arbitrary item by seeing it. In 2018, OpenAI revealed that the system had the ability to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI showed that Dactyl might resolve a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to design. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation technique of generating [progressively](https://oyotunji.site) more hard environments. ADR varies from manual domain randomization by not requiring a human to define randomization [varieties](https://fototik.com). [169] +
API
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In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](http://43.136.17.142:3000) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](http://mpowerstaffing.com) job". [170] [171] +
Text generation
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The company has actually popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT model ("GPT-1")
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The initial paper on generative pre-training of a transformer-based language design was written by Alec Radford and his colleagues, and released in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world understanding and procedure 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 a without supervision transformer language design and the successor to OpenAI's initial GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only minimal demonstrative versions initially launched to the public. The full version of GPT-2 was not right away launched due to concern about potential misuse, including applications for writing fake news. [174] Some experts revealed uncertainty that GPT-2 postured a considerable threat.
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In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to identify "neural phony news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to completely 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 variation of the GPT-2 [language model](https://www.finceptives.com). [177] Several sites host interactive demonstrations of different [instances](https://meebeek.com) of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being watched language designs to be general-purpose students, shown by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot jobs (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, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents certain issues 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](https://jobs.alibeyk.com) 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 stated that the complete version of GPT-3 contained 175 billion specifications, [184] two orders of [magnitude bigger](https://rugraf.ru) than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as few as 125 million specifications were likewise trained). [186] +
OpenAI stated that GPT-3 [prospered](https://gitea.freshbrewed.science) at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer knowing between English and Romanian, and in between [English](https://1samdigitalvision.com) and German. [184] +
GPT-3 significantly improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or experiencing the essential ability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of compute, [compared](http://carecall.co.kr) to 10s of petaflop/s-days for the complete GPT-2 model. [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 to access to through a paid cloud API after a two-month totally free private beta that began in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was licensed 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](http://valueadd.kr) [powering](http://39.96.8.15010080) the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can produce working code in over a lots programs languages, a lot of efficiently in Python. [192] +
Several issues with glitches, design flaws and security vulnerabilities were mentioned. [195] [196] +
GitHub Copilot has been accused of emitting copyrighted code, [wiki.asexuality.org](https://wiki.asexuality.org/w/index.php?title=User_talk:WilliamsMichaels) without any author attribution or license. [197] +
OpenAI revealed that they would stop support for Codex API on March 23, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:LeannaMagoffin) 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI announced 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 read, examine or create as much as 25,000 words of text, and write code in all significant shows languages. [200] +
[Observers](https://dimension-gaming.nl) reported that the model of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has declined to expose various technical details and stats about GPT-4, such as the exact size of the design. [203] +
GPT-4o
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On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision benchmarks, 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 released GPT-4o mini, a smaller sized version 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 expects it to be especially beneficial for enterprises, start-ups and designers seeking to automate services with [AI](https://gitea.eggtech.net) representatives. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have actually been created to take more time to think of their reactions, [causing](http://git.info666.com) higher precision. These designs are especially efficient in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Staff member. [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 successor of the o1 [reasoning model](https://washcareer.com). OpenAI also [revealed](https://quickdatescript.com) o3-mini, a lighter and quicker version of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, [it-viking.ch](http://it-viking.ch/index.php/User:EltonBromby) they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, [security](https://git.wheeparam.com) and security researchers had the chance to obtain early access to these designs. [214] The design is called o3 instead of o2 to prevent confusion with telecommunications services supplier O2. [215] +
Deep research
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Deep research is a representative established by OpenAI, unveiled 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 thirty minutes. [216] With browsing and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [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 examine the semantic resemblance between text and images. It can significantly be used 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 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 handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and generate corresponding images. It can create pictures of sensible things ("a stained-glass window with a picture of a blue strawberry") along with items that do not exist in truth ("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 revealed DALL-E 2, an [updated](https://gitlab.innive.com) version of the model with more [realistic](https://local.wuanwanghao.top3000) results. [219] In December 2022, OpenAI released on GitHub software application for [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:GroverDejesus) Point-E, a new basic system for [transforming](https://signedsociety.com) a text description into a 3-dimensional design. [220] +
DALL-E 3
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In September 2023, OpenAI announced DALL-E 3, a more effective design 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 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 on short detailed triggers [223] as well as extend existing videos forwards or backwards in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.
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Sora's advancement group named it after the Japanese word for "sky", to represent its "unlimited imaginative capacity". [223] Sora's technology 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 as well as copyrighted videos licensed for that function, but 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, mentioning that it might generate videos as much as one minute long. It likewise shared a [technical report](http://47.122.66.12910300) highlighting the techniques utilized to train the model, and the design's abilities. [225] It acknowledged some of its imperfections, including battles simulating complex physics. [226] Will [Douglas Heaven](http://47.93.156.1927006) of the MIT Technology Review called the presentation videos "excellent", but noted that they should have been cherry-picked and might not represent Sora's typical output. [225] +
Despite uncertainty from some academic leaders following Sora's public demo, significant entertainment-industry figures have shown considerable interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's ability to create sensible video from text descriptions, citing its [prospective](https://mysazle.com) to change storytelling and material development. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to stop briefly plans for expanding his Atlanta-based motion picture studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, [Whisper](http://101.33.234.2163000) is a general-purpose speech [acknowledgment](https://warleaks.net) design. [228] It is trained on a big dataset of diverse audio and is likewise a multi-task design that can perform multilingual speech recognition along with 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](http://182.92.202.1133000) to anticipate subsequent musical notes in MIDI music files. It can produce songs with 10 instruments in 15 designs. According to The Verge, a song created by MuseNet tends to begin fairly but then fall into 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 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 mentioned the songs "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the songs do not have "familiar bigger musical structures such as choruses that duplicate" which "there is a considerable gap" in between Jukebox and human-generated music. The Verge mentioned "It's highly outstanding, even if the results sound like mushy versions of songs that might feel familiar", while Business Insider stated "surprisingly, a few of the resulting songs are memorable and sound legitimate". [234] [235] [236] +
User interfaces
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Debate Game
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In 2018, OpenAI introduced the Debate Game, which teaches devices to discuss toy issues in front of a human judge. The purpose is to research whether such an approach might assist in auditing [AI](https://precise.co.za) choices and in developing explainable [AI](https://akrs.ae). [237] [238] +
Microscope
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Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of eight neural network models which are frequently studied in interpretability. [240] Microscope was produced to analyze the features that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, different variations of Inception, and different 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 offers a conversational user interface that allows users to ask questions in natural language. The system then responds with a response within seconds.
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