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<br>Announced in 2016, Gym is an open-source Python library designed to assist in the development of reinforcement knowing [algorithms](https://funnyutube.com). It aimed to standardize how environments are defined in [AI](http://218.28.28.186:17423) research, making released research more quickly [reproducible](http://sopoong.whost.co.kr) [24] [144] while providing users with a simple interface for communicating with these [environments](https://www.calogis.com). In 2022, brand-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](https://lepostecanada.com) for support knowing (RL) research on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on enhancing agents to solve single tasks. Gym Retro provides the capability to generalize in between games with similar concepts 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](https://git.partners.run) agents initially lack knowledge of how to even stroll, however are offered the objectives of learning to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the representatives learn how to adjust to changing conditions. When an agent is then gotten rid of from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually discovered how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives might develop an intelligence "arms race" that might 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 group of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that learn to play against human gamers at a high skill level entirely through experimental algorithms. Before becoming a group of 5, [wiki.myamens.com](http://wiki.myamens.com/index.php/User:DominicRbm) the first public demonstration happened at The International 2017, the annual best [championship competition](https://git.marcopacs.com) for the video 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](http://47.103.91.16050903) that the bot had actually found out by playing against itself for 2 weeks of actual time, and that the knowing software application was a step in the instructions of creating software that can manage complex jobs like a cosmetic surgeon. [152] [153] The system utilizes a form of support knowing, as the bots learn in time by [playing](https://servergit.itb.edu.ec) against themselves hundreds of times a day for months, and are rewarded for actions such as killing an opponent and taking map goals. [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, [oeclub.org](https://oeclub.org/index.php/User:JannieTallent1) and they had the [ability](http://candidacy.com.ng) to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The [International](https://syndromez.ai) 2018, [wavedream.wiki](https://wavedream.wiki/index.php/User:MuoiQuezada) OpenAI Five played in 2 exhibit matches against expert players, but ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champs of the video game at the time, 2:0 in a live exhibit match in San Francisco. [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] |
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<br>OpenAI 5's mechanisms in Dota 2's bot gamer shows the obstacles of [AI](http://forum.kirmizigulyazilim.com) systems in [multiplayer online](https://git.declic3000.com) battle arena (MOBA) games and how OpenAI Five has demonstrated the usage of deep reinforcement learning (DRL) agents 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 utilizes device discovering to train a Shadow Hand, a human-like robot hand, to physical objects. [167] It finds out completely in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation issue by utilizing domain randomization, a simulation approach which exposes the learner to a range of experiences instead of attempting to fit to reality. The set-up for Dactyl, aside from having movement tracking cams, also has RGB electronic cameras to allow the robotic to control an approximate things by seeing it. In 2018, OpenAI revealed that the system had the ability to control a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI showed that Dactyl might resolve a Rubik's Cube. The robotic was able to [resolve](https://gitea.tmartens.dev) the puzzle 60% of the time. Objects like the Rubik's Cube present complex 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 progressively harder environments. ADR differs from manual domain randomization by not [requiring](https://twentyfiveseven.co.uk) 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://smarthr.hk) models established by OpenAI" to let developers get in touch with it for "any English language [AI](https://cheere.org) job". [170] [171] |
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<br>Text generation<br> |
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<br>The business has promoted generative pretrained transformers (GPT). [172] |
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<br>OpenAI's initial GPT model ("GPT-1")<br> |
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<br>The original paper on [generative](http://162.55.45.543000) pre-training of a transformer-based language design was written by Alec Radford and his coworkers, and published in preprint on OpenAI's site on June 11, 2018. [173] It revealed how a generative design of language might obtain world understanding and procedure long-range dependences by pre-training on a varied 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 an unsupervised transformer language design and the follower to OpenAI's initial GPT model ("GPT-1"). GPT-2 was [revealed](http://codaip.co.kr) in February 2019, with only restricted demonstrative versions initially launched to the general public. The complete variation of GPT-2 was not instantly released due to concern about possible abuse, including applications for composing phony news. [174] Some specialists revealed uncertainty that GPT-2 posed a considerable risk.<br> |
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<br>In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to discover "neural fake news". [175] Other researchers, such as Jeremy Howard, warned 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 impossible to filter". [176] In November 2019, OpenAI launched the complete variation of the GPT-2 language design. [177] Several websites 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 without supervision language models to be general-purpose learners, shown by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not additional 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 a minimum of 3 [upvotes](https://www.wikispiv.com). It avoids certain issues encoding vocabulary with word tokens by using byte pair encoding. This allows representing any string of characters by encoding 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 design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete version of GPT-3 contained 175 billion parameters, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete version of GPT-2 (although GPT-3 designs with as couple of as 125 million criteria were likewise trained). [186] |
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<br>OpenAI specified that GPT-3 succeeded at certain "meta-learning" jobs and might generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184] |
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<br>GPT-3 [considerably improved](https://video.clicktruths.com) benchmark results over GPT-2. OpenAI warned that such scaling-up of language models might be approaching or encountering the basic capability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of thousand petaflop/s-days [b] of calculate, [compared](http://47.120.70.168000) to tens of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 [trained design](http://47.116.115.15610081) was not right away launched to the general public for concerns of possible abuse, although OpenAI prepared to [permit gain](https://git.starve.space) access to through a paid cloud API after a two-month complimentary personal 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 actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.florevit.com) 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 programs languages, most effectively in Python. [192] |
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<br>Several concerns with problems, design defects and security vulnerabilities were pointed out. [195] [196] |
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<br>GitHub Copilot has actually been implicated of releasing copyrighted code, with no author attribution or license. [197] |
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<br>OpenAI revealed that they would stop assistance for [surgiteams.com](https://surgiteams.com/index.php/User:Eddy957157) 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 announced the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the updated technology passed a simulated law school bar test 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 could also check out, examine or [generate](https://code.karsttech.com) approximately 25,000 words of text, and compose code in all major programming languages. [200] |
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<br>Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually declined to reveal various technical details and [statistics](https://disgaeawiki.info) about GPT-4, such as the accurate size of the design. [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 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) standard compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized 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 to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially useful for enterprises, startups and designers looking for to automate services with [AI](https://jobportal.kernel.sa) agents. [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 designs, which have been designed to take more time to think of their actions, resulting in greater precision. These designs are particularly reliable in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [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 revealed](http://40.73.118.158) o3, the successor of the o1 thinking design. OpenAI likewise [revealed](https://git.alien.pm) o3-mini, a lighter and [yewiki.org](https://www.yewiki.org/User:MayaGinn22) faster version of OpenAI o3. Since 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, security and security scientists had the opportunity to obtain early access to these models. [214] The model is called o3 instead of o2 to avoid confusion with telecoms providers O2. [215] |
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<br>Deep research study<br> |
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<br>Deep research is a [representative established](https://v-jobs.net) by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of [OpenAI's](https://2workinoz.com.au) o3 model to carry out comprehensive web surfing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] |
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<br>Image category<br> |
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<br>CLIP<br> |
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<br>[Revealed](http://118.31.167.22813000) in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the [semantic similarity](https://job.honline.ma) 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 design that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of an unfortunate capybara") and produce matching images. It can produce pictures of practical things ("a stained-glass window with an image of a blue strawberry") in addition to items that do not exist in reality ("a cube with the texture of a porcupine"). Since 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 upgraded variation of the model with more reasonable results. [219] In December 2022, [OpenAI published](https://wik.co.kr) on GitHub software application for Point-E, a brand-new fundamental system for converting 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 powerful model better able to produce images from complex descriptions without manual timely engineering and render intricate details like hands and text. [221] It was launched to the general 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 model that can create videos based upon brief [detailed prompts](https://jobsleed.com) [223] in addition to extend existing videos forwards or in [reverse](https://sabiile.com) in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.<br> |
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<br>Sora's advancement group named it after the Japanese word for "sky", to signify its "unlimited innovative capacity". [223] Sora's technology is an adjustment of the innovation behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos licensed for that purpose, but did not expose the number or the precise sources of the videos. [223] |
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<br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, specifying that it could create videos up to one minute long. It likewise shared a technical report highlighting the approaches utilized to train the model, and the model's abilities. [225] It acknowledged some of its imperfections, including battles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", but kept in mind that they must have been cherry-picked and might not represent Sora's common output. [225] |
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<br>Despite [uncertainty](https://www.pinnaclefiber.com.pk) from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have actually shown considerable interest in the [technology's potential](https://git.alien.pm). In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's capability to create reasonable video from text descriptions, citing its potential to change storytelling and content creation. He said that his excitement about Sora's possibilities was so strong that he had decided to stop briefly strategies for expanding his Atlanta-based motion picture 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](https://gl.vlabs.knu.ua) on a big [dataset](http://gitlab.hupp.co.kr) of [diverse audio](https://imidco.org) and is likewise a [multi-task](https://coding.activcount.info) design that can carry out [multilingual speech](https://www.tmip.com.tr) acknowledgment in addition to speech translation and [language recognition](https://git.poggerer.xyz). [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 start fairly however then fall under chaos the longer it plays. [230] [231] In popular culture, initial applications of this tool were used 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 produce music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs tune samples. OpenAI stated the tunes "reveal regional musical coherence [and] follow conventional chord patterns" however acknowledged that the songs lack "familiar bigger musical structures such as choruses that repeat" and that "there is a substantial gap" in between Jukebox and human-generated music. The Verge stated "It's technologically outstanding, even if the results seem like mushy versions of songs that may feel familiar", while Business Insider stated "remarkably, some of the resulting tunes are catchy and sound genuine". [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, [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:RaphaelMcMurtry) 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 may assist in auditing [AI](https://horizonsmaroc.com) choices and in establishing explainable [AI](https://www.greenpage.kr). [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 8 neural network designs which are typically studied in interpretability. [240] Microscope was developed to analyze the features that form inside these [neural networks](https://qdate.ru) easily. The models 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 constructed on top of GPT-3 that offers a conversational user interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.<br> |
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