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 help with the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are specified in [AI](https://theboss.wesupportrajini.com) research study, making published research more quickly reproducible [24] [144] while supplying users with a basic interface for interacting with these environments. In 2022, brand-new developments of Gym have been relocated to the [library Gymnasium](https://akinsemployment.ca). [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] using RL algorithms and study generalization. Prior RL research [focused](https://community.cathome.pet) mainly on enhancing agents to fix single tasks. Gym Retro gives the capability to generalize in between video games with comparable principles however different 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 agents at first lack knowledge of how to even stroll, however are given the goals of finding out to move and to press the opposing representative out of the ring. [148] Through this adversarial learning procedure, the agents discover how to adjust to altering conditions. When a representative is then gotten rid of from this virtual environment and placed in a new virtual environment with high winds, [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1073113) the [agent braces](http://193.105.6.1673000) to remain upright, recommending it had actually found out how to stabilize in a [generalized method](https://thedatingpage.com). [148] [149] OpenAI's Igor Mordatch argued that competitors between agents could develop an intelligence "arms race" that could increase a representative's capability to work even outside the [context](https://git.sitenevis.com) of the [competition](http://124.222.6.973000). [148]
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<br>OpenAI 5<br>
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<br>OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that learn to play against human gamers at a high skill level entirely through trial-and-error algorithms. Before ending up being a group of 5, the first public demonstration took place at The International 2017, the yearly best champion competition for the 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](http://dkjournal.co.kr) that the bot had actually found out by playing against itself for 2 weeks of genuine time, which the knowing software was a step in the instructions of developing software application that can manage complicated tasks like a cosmetic surgeon. [152] [153] The system uses a kind of support knowing, as the bots discover in time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing 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 group of 5, and they were able to defeat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against expert players, but 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 that month, where they played in 42,729 total video games in a four-day open online competitors, winning 99.4% of those games. [165]
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<br>OpenAI 5's mechanisms in Dota 2's bot gamer reveals the difficulties of [AI](https://church.ibible.hk) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated making use of deep support knowing (DRL) representatives to attain superhuman skills in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:FlorianHoutz6) Dactyl utilizes [machine discovering](https://thebigme.cc3000) to train a Shadow Hand, a [human-like robotic](http://git.jcode.net) hand, to [control physical](http://git.yang800.cn) items. [167] It finds out totally in simulation utilizing the same RL algorithms and training code as OpenAI Five. OpenAI took on the item orientation problem by utilizing domain randomization, a simulation technique which exposes the learner to a range of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having motion tracking cams, likewise has RGB video cameras to enable the robot to manipulate an [approximate item](https://radi8tv.com) by seeing it. In 2018, OpenAI revealed that the system had the ability to [control](https://pakfindjob.com) a cube and an [octagonal prism](https://centraldasbiblias.com.br). [168]
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<br>In 2019, OpenAI demonstrated that Dactyl could [resolve](https://thebigme.cc3000) a Rubik's Cube. The [robotic](http://112.125.122.2143000) was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce intricate physics that is harder to design. OpenAI did this by enhancing the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating progressively more difficult environments. ADR differs from manual domain randomization by not needing a human to specify randomization ranges. [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](http://git.sanshuiqing.cn) models developed by OpenAI" to let designers call on it for "any English language [AI](http://47.108.140.33) 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](http://app.vellorepropertybazaar.in) GPT model ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language design was composed by Alec Radford and his coworkers, and released in preprint on OpenAI's site on June 11, 2018. [173] It showed how a generative model 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 a without supervision transformer language design and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative versions at first released to the public. The complete variation of GPT-2 was not right away released due to issue about possible abuse, consisting of applications for writing fake news. [174] Some specialists revealed uncertainty that GPT-2 posed a significant threat.<br>
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<br>In action to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to discover "neural phony news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the complete variation of the GPT-2 language model. [177] Several sites host interactive demonstrations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180]
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<br>GPT-2's authors argue unsupervised language designs to be general-purpose students, highlighted by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot jobs (i.e. the design 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 slightly 40 gigabytes of text from URLs shared in Reddit submissions with a minimum of 3 upvotes. It prevents 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 [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:LindaIsenberg91) multiple-character tokens. [181]
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<br>GPT-3<br>
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<br>First explained in May 2020, [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:Pauline9514) Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being watched transformer language model and the successor to GPT-2. [182] [183] [184] [OpenAI stated](https://gold8899.online) that the complete version of GPT-3 contained 175 billion parameters, [184] two orders of magnitude larger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 designs with as couple of as 125 million parameters were also trained). [186]
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<br>OpenAI specified that GPT-3 was successful at certain "meta-learning" jobs 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, [wavedream.wiki](https://wavedream.wiki/index.php/User:AdriannaBranch) and in between English and German. [184]
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<br>GPT-3 drastically enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language designs might be approaching or coming across the essential capability constraints of predictive language designs. [187] Pre-training GPT-3 [required](https://career.webhelp.pk) a number of thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not right away released to the general public for concerns of possible abuse, although OpenAI prepared to enable gain access to through a paid cloud API after a two-month complimentary private beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed 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 additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://git.lovestrong.top) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in personal beta. [194] According to OpenAI, the model can create working code in over a dozen programming languages, a lot of successfully in Python. [192]
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<br>Several concerns with glitches, design defects and security vulnerabilities were cited. [195] [196]
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<br>[GitHub Copilot](https://gitlab.lizhiyuedong.com) has been accused of discharging copyrighted code, without any author attribution or license. [197]
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<br>OpenAI announced that they would stop 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 announced the [release](http://124.16.139.223000) of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the upgraded innovation passed a simulated law school bar examination with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could likewise check out, examine or [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:DewittMosely09) create approximately 25,000 words of text, and write code in all major programming languages. [200]
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<br>Observers reported that the iteration of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caution that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has decreased to expose various technical details and statistics about GPT-4, such as the precise size of the design. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, OpenAI revealed and released GPT-4o, which can process and [generate](https://ttemployment.com) text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision criteria, setting new in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask [Language Understanding](http://solefire.net) (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 variation of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. [OpenAI anticipates](http://124.70.149.1810880) it to be particularly helpful for enterprises, startups and developers seeking to automate services with [AI](https://cbfacilitiesmanagement.ie) representatives. [208]
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<br>o1<br>
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<br>On September 12, 2024, OpenAI launched the o1[-preview](https://posthaos.ru) and o1-mini models, which have been developed to take more time to think about their reactions, resulting in higher accuracy. These designs are especially effective in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Employee. [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 revealed o3, the successor of the o1 reasoning model. OpenAI likewise revealed o3-mini, a [lighter](https://wheeoo.com) and faster variation 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, 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 telecommunications services supplier O2. [215]
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<br>Deep research<br>
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<br>Deep research study is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of [OpenAI's](https://subemultimedia.com) o3 design to perform extensive web surfing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With [searching](http://37.187.2.253000) and Python tools enabled, it reached a precision 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 analyze the semantic resemblance 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 design that produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to translate natural [language inputs](https://www.teacircle.co.in) (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate matching images. It can develop pictures of realistic things ("a stained-glass window with an image of a blue strawberry") along with items that do not exist in truth ("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 revealed](https://maibuzz.com) DALL-E 2, an [updated](https://code.flyingtop.cn) version of the model with more practical outcomes. [219] In December 2022, OpenAI published on GitHub software for Point-E, a brand-new basic system for converting a text description into a 3-dimensional design. [220]
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<br>DALL-E 3<br>
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<br>In September 2023, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:TraceyPrell3) OpenAI revealed DALL-E 3, a more powerful model better able to create images from complicated descriptions without manual timely engineering and [render complicated](https://linkpiz.com) details like hands and text. [221] It was released 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 on short detailed triggers [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 created videos is unknown.<br>
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<br>Sora's development group called it after the Japanese word for "sky", to represent its "endless imaginative capacity". [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 certified for that function, however did not reveal the number or the specific sources of the videos. [223]
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<br>OpenAI demonstrated some Sora-created high-definition videos to the public on February 15, 2024, mentioning that it could create videos up to one minute long. It also shared a technical report highlighting the approaches utilized to train the model, and the model's capabilities. [225] It acknowledged some of its shortcomings, consisting of struggles mimicing complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", however noted that they should have been cherry-picked and might not represent Sora's common output. [225]
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<br>Despite uncertainty from some scholastic leaders following Sora's public demo, noteworthy entertainment-industry figures have revealed significant interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his awe at the technology's capability to create realistic video from text descriptions, citing its potential to transform storytelling and material development. He said that his enjoyment about [Sora's possibilities](http://test.wefanbot.com3000) was so strong that he had decided to stop briefly prepare 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 [recognition model](https://droidt99.com). [228] It is trained on a big dataset of [diverse audio](http://revoltsoft.ru3000) and is likewise a multi-task model that can carry out multilingual speech recognition as well as speech translation and [language identification](http://ieye.xyz5080). [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 forecast subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a song created by [MuseNet](https://centerdb.makorang.com) tends to begin fairly however then fall under mayhem the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the internet 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 music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs tune [samples](https://revinr.site). OpenAI specified the songs "reveal local musical coherence [and] follow standard chord patterns" but acknowledged that the songs lack "familiar larger musical structures such as choruses that duplicate" which "there is a substantial space" in between Jukebox and human-generated music. The Verge specified "It's technologically remarkable, even if the outcomes sound like mushy versions of songs that may feel familiar", while Business Insider mentioned "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, OpenAI introduced the Debate Game, which teaches makers to discuss toy problems in front of a human judge. The [function](http://47.100.17.114) is to research study whether such a method might help in auditing [AI](http://gitfrieds.nackenbox.xyz) decisions and in establishing explainable [AI](https://talento50zaragoza.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 significant layer and nerve cell of 8 neural network designs which are typically studied in interpretability. [240] Microscope was created to evaluate the functions that form inside these neural networks quickly. The designs consisted of 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 offers a conversational interface that allows users to ask concerns in natural language. The system then responds with a response within seconds.<br>
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