From d410b9a64cc825591f388f48cfc37fc70702a13b Mon Sep 17 00:00:00 2001 From: katherinabrein Date: Mon, 7 Apr 2025 19:59:33 +0000 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..c70c93f --- /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 how environments are defined in [AI](http://47.108.78.218:28999) research, making published research more easily reproducible [24] [144] while supplying users with an easy user interface for [engaging](https://hafrikplay.com) with these environments. In 2022, brand-new advancements of Gym have been relocated to the library Gymnasium. [145] [146] +
Gym Retro
+
Released in 2018, Gym Retro is a platform for support learning (RL) research study on video games [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on enhancing representatives to resolve [single jobs](https://jobs.alibeyk.com). Gym Retro offers the ability to generalize between games with similar ideas but various looks.
+
RoboSumo
+
Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot representatives initially lack knowledge of how to even stroll, but are offered the objectives of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial learning process, the representatives learn how to adjust to changing conditions. When a representative is then gotten rid of from this virtual environment and positioned in a brand-new virtual environment with high winds, the representative braces to remain upright, suggesting it had actually found out how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives 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
+
OpenAI Five is a team of five OpenAI-curated bots [utilized](http://47.92.149.1533000) in the [competitive five-on-five](https://gitea.winet.space) video game Dota 2, that find out to play against human players at a high ability level entirely through trial-and-error algorithms. Before becoming a team of 5, the first public presentation happened at The International 2017, the yearly best championship tournament 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](https://wiki.asexuality.org) against itself for 2 weeks of actual time, which the knowing software application was an action in the direction of creating software that can deal with complex tasks like a [surgeon](http://118.25.96.1183000). [152] [153] The system utilizes a kind of support knowing, as the bots find out in time by [playing](http://git.7doc.com.cn) against themselves hundreds of 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 ability of the bots broadened to play together as a complete team of 5, and they were able to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against professional players, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the [reigning](https://gitlab.cloud.bjewaytek.com) world champs of the video game at the time, 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 total video games in a four-day open online competition, winning 99.4% of those video games. [165] +
OpenAI 5's mechanisms in Dota 2's bot player shows the challenges of [AI](http://47.92.218.215:3000) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has shown making use of deep reinforcement learning (DRL) agents to attain superhuman proficiency in Dota 2 matches. [166] +
Dactyl
+
Developed in 2018, Dactyl utilizes maker finding out to train a Shadow Hand, a human-like robotic hand, to control physical objects. [167] It learns entirely in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI dealt with the item orientation issue by utilizing domain randomization, a simulation technique which exposes the student to a variety of experiences instead of attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking cameras, also has RGB video cameras to permit the robot to control an arbitrary object by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168] +
In 2019, OpenAI demonstrated that Dactyl might resolve a Rubik's Cube. The robotic was able to [resolve](http://okna-samara.com.ru) the puzzle 60% of the time. Objects like the Rubik's Cube present intricate [physics](https://lius.familyds.org3000) that is harder to design. OpenAI did this by enhancing the robustness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation technique of creating progressively more tough environments. ADR differs from manual domain randomization by not requiring a human to specify randomization varieties. [169] +
API
+
In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](https://surmodels.com) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](https://www.suyun.store) job". [170] [171] +
Text generation
+
The company has popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT design ("GPT-1")
+
The [original paper](https://www.ukdemolitionjobs.co.uk) on generative pre-training of a transformer-based language design was written by Alec Radford and his colleagues, and published in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative design of language could obtain world understanding and process long-range dependences by pre-training on a diverse corpus with long stretches of contiguous text.
+
GPT-2
+
Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer [language](http://59.110.162.918081) model and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative variations initially released to the public. The complete variation of GPT-2 was not instantly launched due to concern about prospective abuse, including applications for composing phony news. [174] Some professionals expressed uncertainty that GPT-2 presented a significant threat.
+
In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural fake news". [175] Other researchers, such as Jeremy Howard, alerted of "the technology to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". [176] In November 2019, OpenAI released the complete version of the GPT-2 language design. [177] Several sites host interactive demonstrations of various circumstances of GPT-2 and other transformer models. [178] [179] [180] +
GPT-2's authors argue not being watched language models to be general-purpose students, illustrated by GPT-2 attaining cutting [edge accuracy](https://lidoo.com.br) and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not further trained on any task-specific input-output examples).
+
The corpus it was trained on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It avoids certain issues encoding vocabulary with word tokens by [utilizing byte](https://avpro.cc) pair encoding. This permits representing any string of characters by encoding both individual characters and multiple-character tokens. [181] +
GPT-3
+
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 specified that the complete version of GPT-3 contained 175 billion specifications, [184] two orders of magnitude larger 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 stated that GPT-3 prospered at certain "meta-learning" jobs and could generalize the purpose of a single input-output pair. The GPT-3 release paper [offered](https://awaz.cc) examples of [translation](https://videopromotor.com) and cross-linguistic transfer knowing between English and Romanian, and in between [English](https://followmylive.com) and German. [184] +
GPT-3 significantly improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or experiencing the essential ability constraints of predictive language models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately launched to the general public for issues of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month totally free private beta that started in June 2020. [170] [189] +
On September 23, 2020, GPT-3 was certified solely to Microsoft. [190] [191] +
Codex
+
Announced in mid-2021, Codex is a descendant of GPT-3 that has actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://duniareligi.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can create working code in over a dozen shows languages, a lot of efficiently in Python. [192] +
Several concerns with glitches, design defects and security vulnerabilities were cited. [195] [196] +
GitHub Copilot has been accused of discharging copyrighted code, with no author attribution or license. [197] +
OpenAI announced that they would discontinue assistance for Codex API on March 23, 2023. [198] +
GPT-4
+
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 announced that the [upgraded innovation](https://www.ksqa-contest.kr) passed a simulated law school bar test 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 also check out, analyze or generate as much as 25,000 words of text, and write code in all significant programming languages. [200] +
Observers reported that the version of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained some of the issues with earlier revisions. [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has declined to reveal various technical details and data about GPT-4, such as the precise size of the design. [203] +
GPT-4o
+
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 new records in audio speech recognition 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 variation 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 especially useful for business, startups and developers seeking to [automate](http://jobsgo.co.za) services with [AI](https://newnormalnetwork.me) agents. [208] +
o1
+
On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been designed to take more time to consider their responses, causing higher precision. These designs are especially 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
+
On December 20, 2024, OpenAI unveiled o3, the successor of the o1 thinking model. OpenAI likewise revealed o3-mini, a lighter and much faster version of OpenAI o3. As of December 21, 2024, this model is not available for public use. According to OpenAI, they are evaluating 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 instead of o2 to prevent confusion with telecommunications companies O2. [215] +
Deep research
+
Deep research is an agent established by OpenAI, unveiled on February 2, [pediascape.science](https://pediascape.science/wiki/User:PearlNqi45856054) 2025. It leverages the capabilities of OpenAI's o3 model to carry out [comprehensive web](https://meephoo.com) surfing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools enabled, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] +
Image classification
+
CLIP
+
[Revealed](https://taar.me) in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is [trained](https://www.jpaik.com) to examine the [semantic similarity](https://tintinger.org) between text and images. It can significantly be used for image classification. [217] +
Text-to-image
+
DALL-E
+
Revealed in 2021, DALL-E is a [Transformer model](https://tangguifang.dreamhosters.com) 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 bag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and produce matching images. It can produce images of reasonable things ("a stained-glass window with an image of a blue strawberry") as well as objects that do not exist in truth ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.
+
DALL-E 2
+
In April 2022, OpenAI announced DALL-E 2, an upgraded variation of the model with more reasonable results. [219] In December 2022, OpenAI published on GitHub software for Point-E, a brand-new simple system for converting a text description into a 3-dimensional design. [220] +
DALL-E 3
+
In September 2023, OpenAI announced DALL-E 3, a more powerful design much better able to create images from complex descriptions without manual timely engineering and render intricate details like hands and text. [221] It was released to the public as a ChatGPT Plus feature in October. [222] +
Text-to-video
+
Sora
+
Sora is a text-to-video model that can generate videos based upon brief detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution up to 1920x1080 or 1080x1920. The maximal length of generated videos is unidentified.
+
Sora's advancement team called it after the Japanese word for "sky", to symbolize its "endless innovative capacity". [223] [Sora's technology](https://gitea.chenbingyuan.com) 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 function, but did not expose the number or the exact sources of the videos. [223] +
OpenAI demonstrated some [Sora-created](http://git.z-lucky.com90) high-definition videos to the general public on February 15, 2024, stating that it could generate videos up to one minute long. It also shared a technical report highlighting the techniques used to train the model, and the design's capabilities. [225] It acknowledged some of its imperfections, consisting of battles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but noted that they should have been cherry-picked and might not represent Sora's normal output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have actually revealed considerable interest in the [technology's potential](http://101.34.228.453000). In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's capability to generate sensible video from text descriptions, citing its prospective to revolutionize storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had actually decided to stop briefly plans for broadening his Atlanta-based movie studio. [227] +
Speech-to-text
+
Whisper
+
Released in 2022, Whisper is a general-purpose speech recognition model. [228] It is trained on a large dataset of diverse audio and is also a multi-task design that can perform multilingual speech acknowledgment as well as speech translation and language identification. [229] +
Music generation
+
MuseNet
+
Released in 2019, MuseNet is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 designs. According to The Verge, a tune created by MuseNet tends to begin fairly however then fall into [turmoil](https://dngeislgeijx.homes) the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the web psychological thriller Ben Drowned to produce music for the titular character. [232] [233] +
Jukebox
+
Released in 2020, Jukebox is an open-sourced algorithm to generate music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs tune samples. OpenAI mentioned the songs "show regional musical coherence [and] follow standard chord patterns" but acknowledged that the songs do not have "familiar bigger musical structures such as choruses that repeat" which "there is a substantial gap" in between Jukebox and human-generated music. The Verge stated "It's technically outstanding, even if the results seem like mushy variations of songs that may feel familiar", while Business Insider specified "remarkably, a few of the resulting tunes are catchy and sound legitimate". [234] [235] [236] +
User interfaces
+
Debate Game
+
In 2018, OpenAI released the Debate Game, which teaches devices to debate toy issues in front of a human judge. The purpose is to research whether such a method may help in auditing [AI](https://duniareligi.com) decisions and in developing explainable [AI](https://www.refermee.com). [237] [238] +
Microscope
+
[Released](https://git.micahmoore.io) in 2020, Microscope [239] is a collection of visualizations of every substantial layer and neuron of 8 neural network models which are frequently studied in interpretability. [240] Microscope was produced to examine the functions that form inside these neural networks easily. The designs included are AlexNet, VGG-19, various variations of Inception, and different versions of [CLIP Resnet](https://jobs.ethio-academy.com). [241] +
ChatGPT
+
Launched in November 2022, ChatGPT is a synthetic intelligence tool constructed on top of GPT-3 that offers a conversational user interface that allows users to ask concerns in natural language. The system then reacts with an answer within seconds.
\ No newline at end of file