commit dc2c27a9c3f22af51e69d0aa1ffa78e977d2a53b Author: Carmen Menkens Date: Sun Apr 6 16:21:48 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..05d436c --- /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 reinforcement learning algorithms. It aimed to standardize how environments are defined in [AI](https://www.olsitec.de) research study, making published research study more quickly reproducible [24] [144] while providing users with a basic user interface for communicating with these environments. In 2022, brand-new advancements of Gym have actually been relocated to the library Gymnasium. [145] [146] +
Gym Retro
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[Released](http://47.108.140.33) in 2018, Gym Retro is a platform for reinforcement knowing (RL) research study on video games [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing agents to resolve single jobs. Gym Retro gives the capability to generalize between games with similar concepts but various looks.
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RoboSumo
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Released in 2017, RoboSumo is a virtual world where [humanoid metalearning](https://noxxxx.com) robotic agents initially do not have understanding of how to even walk, however are provided the objectives of learning to move and to push the [opposing representative](http://66.85.76.1223000) out of the ring. [148] Through this adversarial learning process, the agents learn how to adjust to changing conditions. When an agent is then removed from this virtual environment and put in a brand-new virtual environment with high winds, the [agent braces](http://www.colegio-sanandres.cl) to remain upright, suggesting it had learned how to [stabilize](https://www.koumii.com) in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition in between agents could create an intelligence "arms race" that might increase an agent's ability to operate even outside the context of the competitors. [148] +
OpenAI 5
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OpenAI Five is a team of 5 OpenAI-curated bots used in the competitive [five-on-five video](http://47.99.119.17313000) game Dota 2, that discover to play against human gamers at a high skill level entirely through trial-and-error algorithms. Before becoming a group of 5, the first public demonstration happened at The International 2017, the yearly best champion tournament for the video game, where Dendi, a professional 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 actually discovered by playing against itself for 2 weeks of actual time, and that the [learning software](https://kahkaham.net) application was a step in the instructions of creating software application that can manage complex jobs like a cosmetic surgeon. [152] [153] The system [utilizes](http://94.191.100.41) a kind of reinforcement learning, as the bots discover with time by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an enemy and taking map objectives. [154] [155] [156] +
By June 2018, the [capability](https://gitlab.zogop.com) of the bots broadened to play together as a full group of 5, and they were able to defeat teams of [amateur](http://git.anyh5.com) and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against professional gamers, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the video game at the time, 2:0 in a live exhibit match in [San Francisco](https://vagyonor.hu). [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 open online competition, winning 99.4% of those video games. [165] +
OpenAI 5's systems in Dota 2's bot player shows the difficulties of [AI](https://kryza.network) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has shown the usage of deep reinforcement knowing (DRL) agents to attain superhuman skills in Dota 2 matches. [166] +
Dactyl
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Developed in 2018, Dactyl utilizes maker finding out to train a Shadow Hand, a human-like robotic hand, to [control physical](http://bolsatrabajo.cusur.udg.mx) things. [167] It discovers entirely in simulation utilizing the same RL algorithms and [pipewiki.org](https://pipewiki.org/wiki/index.php/User:VRMOlen9473913) training code as OpenAI Five. OpenAI took on the item orientation issue by utilizing domain randomization, a simulation method 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 cameras, also has RGB cameras to enable the robot to control an arbitrary 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 showed that Dactyl could fix a Rubik's Cube. The robot had the [ability](https://celflicks.com) to fix the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to model. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of producing progressively harder environments. ADR differs from manual domain randomization by not requiring 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 brand-new [AI](https://viddertube.com) designs established by OpenAI" to let designers get in touch with it for "any English language [AI](http://krzsyjtj.zlongame.co.kr:9004) task". [170] [171] +
Text generation
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The business has popularized generative pretrained transformers (GPT). [172] +
OpenAI's initial GPT design ("GPT-1")
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The [original paper](https://git.qiucl.cn) 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 website on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world knowledge and procedure long-range dependencies by pre-training on a diverse corpus with long [stretches](https://wiki.vifm.info) of [adjoining text](https://dubaijobzone.com).
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GPT-2
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Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised [transformer language](https://my-sugar.co.il) design and the follower to [OpenAI's original](https://hortpeople.com) GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only restricted demonstrative versions at first launched to the public. The full version of GPT-2 was not right away launched due to concern about possible abuse, including applications for writing phony news. [174] Some specialists expressed uncertainty that GPT-2 posed a substantial threat.
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In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to spot "neural phony news". [175] Other researchers, such as Jeremy Howard, cautioned of "the technology to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the total version of the GPT-2 language design. [177] Several sites host [interactive](http://jobjungle.co.za) presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180] +
GPT-2's authors argue not being watched language designs to be general-purpose learners, illustrated by GPT-2 attaining state-of-the-art accuracy and perplexity on 7 of 8 zero-shot jobs (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 a little 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by [utilizing byte](https://suprabullion.com) pair encoding. This permits representing any string of characters by encoding both private 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 an unsupervised transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI stated that the full variation of GPT-3 [contained](http://47.94.142.23510230) 175 billion criteria, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as couple of as 125 million specifications were also trained). [186] +
OpenAI specified that GPT-3 prospered at certain "meta-learning" tasks and might generalize the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184] +
GPT-3 drastically improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or experiencing the essential capability constraints of [predictive language](https://galsenhiphop.com) models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately released to the general public for issues of possible abuse, although OpenAI prepared 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 certified exclusively 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://plus-tube.ru) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the design can develop working code in over a dozen programming languages, a lot of effectively in Python. [192] +
Several issues with problems, design defects and security vulnerabilities were pointed out. [195] [196] +
GitHub Copilot has been implicated of emitting copyrighted code, without any author attribution or license. [197] +
OpenAI revealed that they would stop assistance for Codex API on March 23, 2023. [198] +
GPT-4
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On March 14, 2023, OpenAI [revealed](https://dubai.risqueteam.com) the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar exam with a score around the leading 10% of [test takers](https://southwales.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also check out, analyze or produce approximately 25,000 words of text, and compose code in all major programming languages. [200] +
Observers reported that the model 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 problems with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has [decreased](https://www.outletrelogios.com.br) to expose various technical details and data about GPT-4, such as the [exact size](https://v-jobs.net) 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 state-of-the-art lead to voice, multilingual, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:TonyaBorowski04) 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) benchmark 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 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 anticipates it to be especially helpful for enterprises, start-ups and designers looking for to automate services with [AI](https://athleticbilbaofansclub.com) agents. [208] +
o1
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On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been designed to take more time to think of their actions, causing greater precision. These models 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](https://git.guildofwriters.org) by o1. [211] +
o3
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On December 20, 2024, OpenAI revealed o3, the [successor](http://47.109.24.444747) of the o1 [reasoning design](http://git.qwerin.cz). OpenAI likewise unveiled o3-mini, a lighter and faster variation of OpenAI o3. As of December 21, 2024, this design is not available for public usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the chance to obtain early access to these models. [214] The design is called o3 rather than o2 to prevent confusion with telecoms providers O2. [215] +
Deep research
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Deep research is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform extensive web surfing, information analysis, and synthesis, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2672496) providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools made it possible for, it reached a precision 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 to evaluate the semantic resemblance in between text and images. It can significantly 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://gitea.egyweb.se) that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to interpret natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of an unfortunate capybara") and generate matching images. It can produce pictures of practical objects ("a stained-glass window with an image of a blue strawberry") along with things that do not exist in [reality](https://git.camus.cat) ("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 upgraded variation of the design with more [reasonable outcomes](https://dispatchexpertscudo.org.uk). [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new basic 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 timely engineering and render complicated details like hands and text. [221] It was released 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 produce videos based on short detailed [prompts](https://git.connectplus.jp) [223] in addition to extend existing videos forwards or backwards in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The maximal length of generated videos is unknown.
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Sora's advancement team named it after the Japanese word for "sky", to symbolize its "limitless innovative capacity". [223] Sora's innovation is an adjustment of the technology behind the DALL ยท E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos licensed for that purpose, but did not expose the number or the precise sources of the videos. [223] +
OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, [mentioning](https://code.flyingtop.cn) that it could create videos approximately one minute long. It likewise shared a technical report highlighting the methods used to train the design, and the model's abilities. [225] It acknowledged a few of its imperfections, including struggles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", however kept in mind that they should have been cherry-picked and may not represent Sora's common output. [225] +
Despite uncertainty from some scholastic leaders following Sora's public demo, notable entertainment-industry figures have actually shown significant interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's capability to generate reasonable video from text descriptions, mentioning its possible to transform storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had decided to pause prepare for [larsaluarna.se](http://www.larsaluarna.se/index.php/User:CarriKirk4) broadening his Atlanta-based film studio. [227] +
Speech-to-text
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Whisper
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Released in 2022, [Whisper](https://truthbook.social) is a general-purpose speech recognition design. [228] It is trained on a big dataset of varied audio and is likewise a multi-task design that can carry out 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](https://zikorah.com) net trained to anticipate subsequent musical notes in MIDI music files. It can create songs with 10 instruments in 15 designs. According to The Verge, a song created by [MuseNet](https://gitea.lelespace.top) tends to begin fairly however then fall under mayhem the longer it plays. [230] [231] In pop culture, initial applications of this tool were [utilized](https://git.getmind.cn) 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 generate music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs song samples. OpenAI specified the songs "show regional musical coherence [and] follow standard chord patterns" but acknowledged that the tunes do not have "familiar larger musical structures such as choruses that repeat" which "there is a substantial space" between and human-generated music. The Verge mentioned "It's technologically outstanding, even if the outcomes sound like mushy versions of songs that might feel familiar", while Business Insider stated "surprisingly, some of the resulting songs are catchy 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 dispute toy issues in front of a human judge. The function is to research study whether such a method may help in auditing [AI](http://39.99.158.114:10080) choices and in establishing explainable [AI](http://www.evmarket.co.kr). [237] [238] +
Microscope
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Released in 2020, [Microscope](https://gitlab.vog.media) [239] is a collection of visualizations of every significant layer and neuron of eight neural network models which are often studied in interpretability. [240] Microscope was created to analyze the functions that form inside these neural networks quickly. The designs 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 expert system tool constructed on top of GPT-3 that offers a conversational interface that enables users to ask [concerns](https://taar.me) in natural language. The system then responds with an answer within seconds.
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