Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library developed to assist in the development of reinforcement learning algorithms. It aimed to standardize how environments are specified in [AI](http://xn--o39aoby1e85nw4rx0fwvcmubsl71ekzf4w4a.kr) research study, making published research more easily reproducible [24] [144] while supplying users with an easy interface for interacting with these environments. In 2022, new developments of Gym have 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 (RL) research on video games [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on [enhancing representatives](https://www.niveza.co.in) to fix single jobs. Gym Retro offers the ability to generalize between games with comparable principles however various appearances.<br>
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<br>RoboSumo<br>
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<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially do not have understanding of how to even stroll, but are offered the objectives of [discovering](https://abcdsuppermarket.com) to move and to press the opposing agent out of the ring. [148] Through this adversarial knowing process, the agents [discover](http://git.lai-tech.group8099) how to adjust to changing conditions. When an agent is then removed from this virtual environment and put in a brand-new [virtual environment](https://hlatube.com) with high winds, the agent braces to remain upright, suggesting it had actually found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives could produce an intelligence "arms race" that could increase a representative's ability to function even outside the context of the competitors. [148]
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<br>OpenAI 5<br>
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<br>OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that discover to play against human players at a high ability level entirely through trial-and-error algorithms. Before ending up being a team of 5, the very first public demonstration happened at The International 2017, the annual premiere championship competition for the video game, where Dendi, an expert Ukrainian player, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for 2 weeks of real time, and that the knowing software application was a step in the instructions of creating software application that can handle complicated tasks like a cosmetic surgeon. [152] [153] The system uses a type of reinforcement knowing, as the bots discover gradually by playing 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]
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<br>By June 2018, the ability of the bots expanded to play together as a complete team of 5, and they had the ability to beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against [professional](https://git.parat.swiss) players, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' [final public](https://git.whistledev.com) look came later 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 systems in Dota 2's bot player reveals the obstacles of [AI](http://code.qutaovip.com) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated using deep reinforcement knowing (DRL) representatives to attain superhuman competence in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl utilizes maker finding out to train a Shadow Hand, a human-like robotic hand, to manipulate physical objects. [167] It finds out entirely in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation problem by utilizing domain randomization, a simulation technique which exposes the learner to a variety of experiences instead of trying to fit to reality. The set-up for Dactyl, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11860868) aside from having movement tracking video cameras, also has RGB cameras to enable the robotic to manipulate an approximate things by seeing it. In 2018, OpenAI showed that the system was able to [manipulate](https://beta.talentfusion.vn) a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI demonstrated that Dactyl could solve a Rubik's Cube. The robot was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of creating gradually more tough environments. ADR differs from manual domain [randomization](https://truejob.co) by not needing a human to specify randomization varieties. [169]
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<br>API<br>
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<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](https://git.smartenergi.org) models established by OpenAI" to let designers call on it for "any English language [AI](https://gogs.dzyhc.com) task". [170] [171]
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<br>Text generation<br>
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<br>The [company](http://valueadd.kr) has popularized generative pretrained transformers (GPT). [172]
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<br>OpenAI's initial 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 associates, and released in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world knowledge and process long-range dependencies 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 without [supervision transformer](https://social.midnightdreamsreborns.com) language model and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative versions [initially released](http://47.101.187.298081) to the general public. The full variation of GPT-2 was not right away launched due to issue about potential misuse, including applications for [writing](http://anggrek.aplikasi.web.id3000) fake news. [174] Some professionals revealed uncertainty that GPT-2 postured a substantial danger.<br>
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<br>In action to GPT-2, the Allen Institute for [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1089696) Artificial Intelligence reacted with a tool to discover "neural fake news". [175] Other scientists, such as Jeremy Howard, cautioned of "the innovation to absolutely 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 launched the total variation of the GPT-2 language design. [177] Several sites host interactive presentations of different instances of GPT-2 and other transformer models. [178] [179] [180]
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<br>GPT-2's authors argue unsupervised language models to be general-purpose learners, shown by GPT-2 [attaining modern](https://www.philthejob.nl) accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further 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 problems encoding vocabulary with word tokens by [utilizing byte](http://gitlab.gomoretech.com) pair encoding. This permits representing any string of characters by [encoding](http://www.vpsguards.co) both private 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 a not being watched transformer language model and the follower to GPT-2. [182] [183] [184] [OpenAI mentioned](https://choosy.cc) that the complete variation of GPT-3 contained 175 billion criteria, [184] two orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as few as 125 million parameters were also trained). [186]
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<br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" tasks and could generalize the purpose of a single input-output pair. The GPT-3 release paper offered 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 significantly enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models might be [approaching](http://120.77.205.309998) or encountering the essential capability constraints of predictive language designs. [187] Pre-training GPT-3 needed several thousand petaflop/s-days [b] of calculate, compared 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 [launched](https://git.xutils.co) to the public for concerns of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a [two-month free](https://git.iws.uni-stuttgart.de) private beta that started in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed specifically 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 additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.angevinepromotions.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [private](http://175.6.40.688081) beta. [194] According to OpenAI, the model can develop working code in over a dozen shows languages, a lot of effectively in Python. [192]
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<br>Several issues with glitches, design flaws and security vulnerabilities were pointed out. [195] [196]
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<br>GitHub Copilot has actually been accused of discharging copyrighted code, without any author attribution or license. [197]
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<br>OpenAI revealed that they would terminate support 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 Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They revealed that the upgraded innovation passed a simulated law school bar examination 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, [examine](http://repo.magicbane.com) or [produce](http://git.indep.gob.mx) up to 25,000 words of text, and compose code in all significant shows languages. [200]
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<br>Observers reported that the version of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the problems with earlier revisions. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has declined to expose numerous technical details and stats about GPT-4, such as the accurate size of the model. [203]
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<br>GPT-4o<br>
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<br>On May 13, [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:SamualGuillen) 2024, OpenAI announced and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o [attained cutting](https://wik.co.kr) edge results in 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]
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<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller sized version of GPT-4o changing GPT-3.5 Turbo on the ChatGPT user interface. Its API costs $0.15 per million [input tokens](https://speeddating.co.il) and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially useful for enterprises, start-ups and developers looking for to automate services with [AI](https://git.lazyka.ru) agents. [208]
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<br>o1<br>
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<br>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, resulting in greater 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]
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<br>o3<br>
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<br>On December 20, 2024, OpenAI unveiled o3, the successor of the o1 thinking design. OpenAI also unveiled o3-mini, a lighter and faster variation of OpenAI o3. As of December 21, 2024, this model is not available for public usage. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the chance to obtain early access to these models. [214] The model is called o3 instead of o2 to avoid confusion with telecoms companies O2. [215]
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<br>Deep research study<br>
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<br>Deep research is an agent established by OpenAI, [unveiled](https://git.iws.uni-stuttgart.de) on February 2, 2025. It leverages the [capabilities](https://japapmessenger.com) of OpenAI's o3 model to perform comprehensive web browsing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120]
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<br>Image category<br>
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<br>CLIP<br>
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<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to analyze the semantic resemblance between text and images. It can significantly be utilized for image category. [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 design that produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of an unfortunate capybara") and [produce matching](http://82.156.194.323000) images. It can create images of practical things ("a stained-glass window with a picture of a blue strawberry") along with things that do not exist in truth ("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 revealed DALL-E 2, an version of the design with more sensible results. [219] In December 2022, OpenAI published on GitHub software for Point-E, [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:JulieOfficer27) a brand-new rudimentary 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, OpenAI revealed DALL-E 3, a more effective design better able to create images from complicated descriptions without manual timely engineering and render intricate [details](https://gitstud.cunbm.utcluj.ro) like hands and text. [221] It was [launched](https://job-maniak.com) 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](https://video.emcd.ro) that can generate videos based upon brief detailed prompts [223] as well as extend existing videos forwards or backwards in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of produced videos is unidentified.<br>
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<br>Sora's development group called it after the Japanese word for "sky", to signify its "unlimited innovative capacity". [223] Sora's technology is an adaptation of the technology behind the DALL · E 3 [text-to-image](https://tayseerconsultants.com) design. [225] OpenAI trained the system [utilizing publicly-available](https://storymaps.nhmc.uoc.gr) videos along with copyrighted [videos licensed](https://git.esc-plus.com) for [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:ShaniBagshaw2) that function, but did not expose the number or the exact sources of the videos. [223]
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<br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it might create videos approximately one minute long. It likewise shared a technical report highlighting the approaches utilized to train the design, and the model's abilities. [225] It acknowledged a few of its drawbacks, consisting of struggles mimicing complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "remarkable", however noted that they must have been cherry-picked and might not represent Sora's typical output. [225]
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<br>Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have revealed substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's ability to create reasonable video from text descriptions, citing its prospective to reinvent storytelling and material development. He said that his excitement about Sora's possibilities was so strong that he had chosen to stop briefly plans for expanding 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 recognition design. [228] It is trained on a large dataset of varied audio and is likewise a multi-task model that can carry out multilingual speech acknowledgment as well as speech translation and language recognition. [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 predict subsequent musical notes in MIDI music files. It can produce songs with 10 instruments in 15 designs. According to The Verge, a tune produced by MuseNet tends to begin fairly however then fall under turmoil the longer it plays. [230] [231] In pop culture, initial applications of this tool were [utilized](http://www.kotlinx.com3000) as early as 2020 for the internet psychological thriller Ben Drowned to produce 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 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 specified the tunes "show local musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes lack "familiar larger musical structures such as choruses that repeat" which "there is a significant space" between Jukebox and human-generated music. The Verge stated "It's highly outstanding, even if the outcomes sound like mushy versions of tunes that might feel familiar", while [Business Insider](https://twoo.tr) stated "surprisingly, a few of the resulting tunes are catchy and sound legitimate". [234] [235] [236]
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<br>Interface<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI introduced the Debate Game, which teaches makers to debate toy issues in front of a human judge. The function is to research study whether such a method might assist in auditing [AI](http://103.197.204.163:3025) decisions and in developing explainable [AI](https://www.ignitionadvertising.com). [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 substantial layer and nerve cell of eight neural network models which are often studied in interpretability. [240] Microscope was created to evaluate the [features](http://64.227.136.170) that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, various variations of Inception, and various versions of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>[Launched](http://59.110.162.918081) in November 2022, ChatGPT is a synthetic intelligence [tool constructed](http://peterlevi.com) on top of GPT-3 that offers a conversational interface that allows users to ask [questions](https://ssh.joshuakmckelvey.com) in [natural language](https://social.ppmandi.com). The system then responds with an answer within seconds.<br>
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