Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library designed to help with the advancement of support knowing algorithms. It aimed to standardize how environments are defined in [AI](https://play.hewah.com) research study, making released research study more quickly [reproducible](https://tubevieu.com) [24] [144] while offering users with a simple interface for communicating with these environments. In 2022, brand-new developments of Gym have actually been relocated to the library Gymnasium. [145] [146]
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<br>Gym Retro<br>
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<br>Released in 2018, Gym Retro is a platform for [support learning](http://202.90.141.173000) (RL) research study on computer game [147] using RL algorithms and study [generalization](https://forum.batman.gainedge.org). Prior RL research study focused mainly on enhancing representatives to resolve single jobs. Gym Retro gives the capability to generalize between video games with comparable ideas but various looks.<br>
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<br>RoboSumo<br>
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<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives initially lack knowledge of how to even walk, but are offered the goals of finding out to move and to press the opposing agent out of the ring. [148] Through this adversarial learning process, the agents find out how to adapt 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 [agent braces](https://coding.activcount.info) to remain upright, [suggesting](https://addismarket.net) it had actually discovered how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that [competition](http://116.205.229.1963000) in between agents could produce an intelligence "arms race" that could increase an agent's ability to operate even outside the context of the competition. [148]
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<br>OpenAI 5<br>
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<br>OpenAI Five is a team of 5 OpenAI-curated bots utilized in the competitive five-on-five [video game](http://47.108.69.3310888) Dota 2, that learn to play against human players at a high skill level totally through trial-and-error algorithms. Before becoming a team of 5, the first public presentation took place at The International 2017, the annual premiere champion competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg [Brockman explained](https://career.abuissa.com) that the bot had discovered by playing against itself for two weeks of genuine time, and that the learning software application was an action in the [direction](https://hireblitz.com) of developing software application that can deal with complex tasks like a surgeon. [152] [153] The system uses a type of [support](http://34.81.52.16) knowing, as the bots learn gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an enemy and taking map goals. [154] [155] [156]
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<br>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 groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches 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' final public look came later on that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games. [165]
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<br>OpenAI 5's mechanisms in Dota 2's bot player shows the challenges of [AI](http://112.124.19.38:8080) systems in multiplayer online fight arena (MOBA) video games and how OpenAI Five has shown using deep support learning (DRL) representatives to attain superhuman proficiency in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl uses machine finding out to train a Shadow Hand, a [human-like robotic](http://111.9.47.10510244) hand, to manipulate physical objects. [167] It discovers completely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the things orientation problem by using domain randomization, a simulation method which exposes the learner to a variety of experiences instead of attempting to fit to truth. The set-up for [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:WBKJosef646) Dactyl, aside from having [motion tracking](https://www.bongmedia.tv) video cameras, likewise has RGB cams to permit the robot to control an approximate item by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI demonstrated that Dactyl could fix a Rubik's Cube. The robotic was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to design. OpenAI did this by enhancing the toughness of Dactyl to [perturbations](http://lstelecom.co.kr) by using Automatic Domain Randomization (ADR), a simulation technique of producing progressively more tough environments. ADR differs from manual domain randomization by not requiring a human to define randomization varieties. [169]
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<br>API<br>
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<br>In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](https://78.47.96.161:3000) designs established by OpenAI" to let [designers](http://114.55.171.2313000) call on it for "any English language [AI](https://dev.ncot.uk) job". [170] [171]
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<br>Text generation<br>
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<br>The company has actually promoted generative [pretrained](https://jobsekerz.com) transformers (GPT). [172]
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<br>OpenAI's original GPT model ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language design was written by Alec Radford and his coworkers, and released in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative model of language could obtain world knowledge and process long-range reliances by pre-training on a diverse corpus with long stretches of adjoining text.<br>
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<br>GPT-2<br>
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<br>Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language model and [pediascape.science](https://pediascape.science/wiki/User:CaroleRinaldi) the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative variations at first released to the general public. The complete [variation](https://gitlab.payamake-sefid.com) of GPT-2 was not instantly launched due to issue about possible abuse, including applications for composing fake news. [174] Some specialists expressed uncertainty that GPT-2 [positioned](https://champ217.flixsterz.com) a considerable threat.<br>
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<br>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, [cautioned](https://git.intelgice.com) of "the technology to completely 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 variation of the GPT-2 language design. [177] Several [websites](https://git.ddswd.de) host interactive demonstrations of various instances of GPT-2 and other transformer models. [178] [179] [180]
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<br>GPT-2's [authors argue](http://119.29.169.1578081) without supervision language designs to be general-purpose learners, shown by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not more trained on any task-specific input-output examples).<br>
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<br>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 avoids certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters by encoding both specific characters and multiple-character tokens. [181]
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<br>GPT-3<br>
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<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language design and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 designs with as few as 125 million specifications were likewise trained). [186]
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<br>[OpenAI stated](http://git.szmicode.com3000) that GPT-3 prospered at certain "meta-learning" tasks and might generalize the function of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing in between English and Romanian, and between English and German. [184]
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<br>GPT-3 considerably enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs could be approaching or coming across the basic ability constraints of [predictive language](http://demo.ynrd.com8899) models. [187] Pre-training GPT-3 required 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 totally free private beta that started in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was certified solely to Microsoft. [190] [191]
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<br>Codex<br>
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<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has actually furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.mitsea.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the design can create working code in over a lots programs languages, most efficiently in Python. [192]
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<br>Several issues with glitches, [style defects](https://careers.jabenefits.com) and security vulnerabilities were mentioned. [195] [196]
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<br>GitHub Copilot has been accused of discharging copyrighted code, with no author attribution or license. [197]
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<br>OpenAI revealed that they would cease assistance for Codex API on March 23, 2023. [198]
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<br>GPT-4<br>
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<br>On March 14, 2023, OpenAI revealed the release of [Generative Pre-trained](https://spotlessmusic.com) Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They revealed that the updated innovation passed a [simulated law](http://demo.ynrd.com8899) school bar examination with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise check out, analyze or create approximately 25,000 words of text, and write code in all major shows languages. [200]
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<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is also [efficient](https://dessinateurs-projeteurs.com) in taking images as input on ChatGPT. [202] OpenAI has declined to expose various [technical details](http://nysca.net) and stats about GPT-4, such as the exact size of the model. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained advanced results in voice, multilingual, and vision standards, setting new [records](https://git.whistledev.com) 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]
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller version 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](https://gitlab.ui.ac.id) to $5 and $15 respectively for GPT-4o. OpenAI expects it to be particularly helpful for enterprises, startups and [developers seeking](http://git.agentum.beget.tech) to automate services with [AI](https://gitea.mierzala.com) representatives. [208]
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<br>o1<br>
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<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have been developed to take more time to consider their actions, resulting in greater accuracy. These designs are especially reliable in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was replaced by o1. [211]
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<br>o3<br>
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<br>On December 20, 2024, OpenAI unveiled o3, the follower of the o1 reasoning design. OpenAI likewise unveiled o3-mini, a lighter and quicker variation of OpenAI o3. As of December 21, 2024, this model is not available for public use. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, [trademarketclassifieds.com](https://trademarketclassifieds.com/user/profile/2746667) safety and [security scientists](https://cbfacilitiesmanagement.ie) had the opportunity to obtain early access to these designs. [214] The design is called o3 rather than o2 to prevent confusion with telecommunications providers O2. [215]
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<br>Deep research<br>
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<br>Deep research study is a representative established by OpenAI, revealed on February 2, 2025. It leverages the of OpenAI's o3 design to [perform comprehensive](https://lidoo.com.br) web surfing, data analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools allowed, [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:Alisia1875) it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120]
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<br>Image classification<br>
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<br>CLIP<br>
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<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the [semantic similarity](https://contractoe.com) in between text and images. It can notably be utilized for image classification. [217]
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<br>Text-to-image<br>
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<br>DALL-E<br>
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<br>Revealed in 2021, DALL-E is a [Transformer model](https://parissaintgermainfansclub.com) that creates images from [textual descriptions](http://photorum.eclat-mauve.fr). [218] DALL-E utilizes 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 a sad capybara") and generate corresponding images. It can create pictures of realistic things ("a stained-glass window with an image of a blue strawberry") as well as items that do not exist in reality ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.<br>
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<br>DALL-E 2<br>
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<br>In April 2022, OpenAI announced DALL-E 2, an updated variation of the model with more reasonable results. [219] In December 2022, OpenAI published on GitHub software for Point-E, a new primary system for transforming a text description into a 3-dimensional model. [220]
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<br>DALL-E 3<br>
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<br>In September 2023, [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:GLXKatrice) OpenAI announced DALL-E 3, a more effective model better able to generate images from intricate [descriptions](http://175.6.124.2503100) 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]
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<br>Text-to-video<br>
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<br>Sora<br>
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<br>Sora is a text-to-video design that can create videos based upon brief detailed prompts [223] along with extend existing videos forwards or backwards in time. [224] It can produce videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of created videos is unknown.<br>
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<br>Sora's development team called it after the Japanese word for "sky", to represent its "endless imaginative potential". [223] Sora's technology is an adaptation of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos licensed for that function, however did not reveal the number or [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:LeiaBuckley2869) the specific sources of the videos. [223]
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<br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, stating that it could produce videos as much as one minute long. It also shared a technical report highlighting the techniques used to train the design, and the design's capabilities. [225] It acknowledged some of its imperfections, consisting of battles replicating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", but noted that they must have been cherry-picked and may not represent Sora's typical output. [225]
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<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have actually revealed substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's capability to generate sensible video from text descriptions, citing its potential to revolutionize storytelling and material production. He said that his enjoyment about [Sora's possibilities](http://182.92.163.1983000) was so strong that he had decided to stop briefly strategies for broadening his Atlanta-based movie studio. [227]
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<br>Speech-to-text<br>
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<br>Whisper<br>
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<br>Released in 2022, Whisper is a general-purpose speech acknowledgment model. [228] It is trained on a large dataset of [diverse audio](https://git.cloudtui.com) and is also a multi-task design that can perform multilingual speech recognition as well as [speech translation](http://34.81.52.16) and language identification. [229]
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<br>Music generation<br>
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<br>MuseNet<br>
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<br>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 song produced by MuseNet tends to start fairly however then fall under chaos the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for the web psychological thriller Ben Drowned to develop music for the titular character. [232] [233]
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<br>Jukebox<br>
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<br>Released in 2020, Jukebox is an open-sourced algorithm to [generate](http://202.90.141.173000) music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs song samples. OpenAI mentioned the tunes "show local musical coherence [and] follow standard chord patterns" but acknowledged that the songs do not have "familiar larger musical structures such as choruses that duplicate" and that "there is a considerable space" between Jukebox and human-generated music. The Verge mentioned "It's technically remarkable, even if the results sound like mushy variations of tunes that may feel familiar", while Business Insider specified "surprisingly, some of the resulting songs are catchy and sound genuine". [234] [235] [236]
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<br>User interfaces<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI launched the Debate Game, which teaches devices to debate toy problems in front of a human judge. The purpose is to research whether such a technique might assist in auditing [AI](http://thinking.zicp.io:3000) choices and in developing explainable [AI](http://aiot7.com:3000). [237] [238]
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<br>Microscope<br>
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<br>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 developed to analyze the functions that form inside these neural networks quickly. The designs included are AlexNet, VGG-19, different versions of Inception, and different versions of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, ChatGPT is a synthetic intelligence tool built on top of GPT-3 that provides a conversational interface that allows users to ask questions in natural language. The system then responds with an answer within seconds.<br>
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