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 reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://ipmanage.sumedangkab.go.id) research study, making released research more quickly reproducible [24] [144] while [providing](https://livy.biz) users with a basic user interface for interacting with these environments. In 2022, new [advancements](https://analyticsjobs.in) of Gym have been moved 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](http://124.71.134.1463000) for reinforcement learning (RL) research study on video games [147] using RL algorithms and study generalization. Prior RL research focused mainly on enhancing representatives to fix single tasks. Gym Retro provides the [capability](https://gitlab.liangzhicn.com) to generalize between games with similar concepts but 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 initially lack knowledge of how to even walk, however are given the goals of learning to move and to press the opposing agent out of the ring. [148] Through this adversarial learning process, the agents find out how to adjust to changing conditions. When a representative is then eliminated from this virtual environment and placed in a brand-new virtual environment with high winds, the agent braces to remain upright, recommending it had discovered how to balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competition between agents could create an intelligence "arms race" that could increase an agent's capability to function 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 totally through trial-and-error algorithms. Before becoming a team of 5, the first public presentation took place at The International 2017, the yearly premiere champion competition for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually found out by [playing](https://yourrecruitmentspecialists.co.uk) against itself for two weeks of real time, which the knowing software application was an action in the instructions of developing software application that can handle complex tasks like a surgeon. [152] [153] The system uses a type of [reinforcement](https://aladin.social) knowing, as the bots discover gradually by playing against themselves hundreds of times a day for [larsaluarna.se](http://www.larsaluarna.se/index.php/User:MaximoJauncey28) months, and are rewarded for actions such as killing an opponent and taking map objectives. [154] [155] [156]
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<br>By June 2018, the ability of the bots broadened to play together as a complete group of 5, and they were able to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against players, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated 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' last public look came later on that month, where they played in 42,729 overall 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](http://git.ningdatech.com) in Dota 2's bot player shows the challenges of [AI](https://video.clicktruths.com) systems in multiplayer online battle arena (MOBA) video games and how OpenAI Five has demonstrated making use of deep support learning (DRL) agents to attain superhuman [competence](http://101.43.151.1913000) in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl utilizes machine [finding](http://8.137.54.2139000) out to train a Shadow Hand, a human-like robot hand, to manipulate [physical items](https://video.emcd.ro). [167] It discovers totally in simulation utilizing the very same RL algorithms and training code as OpenAI Five. OpenAI tackled the item orientation issue by utilizing domain randomization, a simulation technique which exposes the learner to a variety of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having motion tracking cams, likewise has [RGB cameras](http://personal-view.com) to allow the robotic to control an arbitrary item by seeing it. In 2018, OpenAI revealed that the system had the ability 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 [resolve](http://8.134.253.2218088) the puzzle 60% of the time. Objects like the Rubik's Cube present complicated physics that is harder to model. OpenAI did this by improving the toughness of Dactyl to perturbations by utilizing Automatic [Domain Randomization](http://106.39.38.2421300) (ADR), a simulation method of creating progressively more hard environments. ADR differs from manual domain randomization by not requiring a human to define 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](https://writerunblocks.com) models established by OpenAI" to let developers contact it for "any English language [AI](https://demo.shoudyhosting.com) job". [170] [171]
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<br>Text generation<br>
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<br>The company has promoted generative pretrained transformers (GPT). [172]
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<br>OpenAI's initial GPT design ("GPT-1")<br>
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<br>The original paper on generative [pre-training](https://zenabifair.com) of a transformer-based language design was composed by Alec Radford and his coworkers, and published in preprint on [OpenAI's website](https://thenolugroup.co.za) on June 11, 2018. [173] It showed how a generative model of language might obtain world knowledge and procedure long-range reliances 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 original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only restricted demonstrative variations at first launched to the general public. The complete variation of GPT-2 was not instantly launched due to issue about possible abuse, consisting of [applications](https://mtglobalsolutionsinc.com) for composing fake news. [174] Some professionals revealed uncertainty that GPT-2 postured a considerable threat.<br>
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<br>In response 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 of "the innovation to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". [176] In November 2019, OpenAI released the complete variation of the GPT-2 language model. [177] Several sites host interactive presentations of various circumstances of GPT-2 and other transformer models. [178] [179] [180]
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<br>GPT-2's authors argue without supervision language designs to be general-purpose students, shown by GPT-2 attaining state-of-the-art 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 a little 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 permits 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 model and the follower to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion specifications, [184] 2 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 specifications were likewise trained). [186]
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<br>OpenAI mentioned that GPT-3 [prospered](https://thefreedommovement.ca) at certain "meta-learning" jobs 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 significantly improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models might be [approaching](https://www.postajob.in) or encountering the essential ability constraints of predictive language models. [187] Pre-training GPT-3 required a number of thousand [pipewiki.org](https://pipewiki.org/wiki/index.php/User:Shawnee3364) petaflop/s-days [b] of calculate, [wiki.myamens.com](http://wiki.myamens.com/index.php/User:DRHHudson883) compared to tens of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately launched to the general public for concerns of possible abuse, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11951897) although OpenAI planned to enable gain access to through a paid cloud API after a two-month complimentary personal beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was licensed exclusively 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://xn--mf0bm6uh9iu3avi400g.kr) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in private beta. [194] According to OpenAI, the design can create working code in over a dozen shows languages, a lot of efficiently in Python. [192]
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<br>Several issues with problems, design flaws and security vulnerabilities were mentioned. [195] [196]
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<br>GitHub Copilot has been implicated of emitting copyrighted code, without any author attribution or license. [197]
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<br>OpenAI revealed that they would discontinue support for Codex API on March 23, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:LeilaniCable73) 2023. [198]
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<br>GPT-4<br>
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<br>On March 14, 2023, OpenAI announced the [release](http://47.92.109.2308080) of [Generative Pre-trained](https://job.bzconsultant.in) Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They [revealed](http://47.92.109.2308080) that the upgraded innovation passed a simulated law school bar exam with a rating around the top 10% of [test takers](https://www.xafersjobs.com). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise check out, evaluate or generate approximately 25,000 words of text, and compose code in all major shows languages. [200]
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<br>Observers reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the issues with earlier modifications. [201] GPT-4 is also efficient in taking images as input on [ChatGPT](http://www.boot-gebraucht.de). [202] OpenAI has actually decreased to reveal numerous technical [details](https://schubach-websocket.hopto.org) and stats 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 produce text, images and audio. [204] GPT-4o attained state-of-the-art lead to voice, multilingual, and vision criteria, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) [standard](https://namesdev.com) 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 variation of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT user 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 expects it to be especially beneficial for business, startups and designers seeking to automate services with [AI](https://www.bjs-personal.hu) 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 models, which have actually been designed to take more time to think about their actions, causing greater accuracy. These designs are especially effective in science, coding, and reasoning tasks, 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 revealed o3, the successor of the o1 thinking design. OpenAI likewise [revealed](https://kahkaham.net) o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this design is not available for public use. According to OpenAI, they are [testing](http://47.103.108.263000) o3 and o3-mini. [212] [213] Until January 10, 2025, safety and [security scientists](https://gitea.lihaink.cn) had the chance to obtain early access to these designs. [214] The model is called o3 instead of o2 to avoid confusion with [telecoms providers](https://gitea.uchung.com) O2. [215]
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<br>Deep research<br>
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<br>Deep research is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities 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 enabled, it reached a precision 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](http://120.55.59.896023) in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the semantic resemblance between text and images. It can notably be used 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 develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to translate natural [language inputs](https://gitlab.profi.travel) (such as "a green leather purse formed like a pentagon" or "an isometric view of an unfortunate capybara") and generate corresponding images. It can produce pictures of sensible 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"). 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 version of the design with more reasonable results. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new rudimentary 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, OpenAI announced DALL-E 3, a more [powerful design](http://advance5.com.my) better able to create images from complicated 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 function 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 brief detailed triggers [223] as well as extend existing videos forwards or in reverse in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of generated videos is unidentified.<br>
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<br>Sora's advancement team named it after the Japanese word for "sky", to represent its "endless innovative capacity". [223] Sora's technology is an adjustment of the [innovation](http://gitlab.ideabeans.myds.me30000) behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos licensed for that purpose, however did not reveal the number or the precise 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, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:ChiquitaVeilleux) 2024, stating that it could create videos up to one minute long. It also shared a technical report highlighting the methods utilized to train the model, and the model's abilities. [225] It acknowledged some of its imperfections, consisting of struggles replicating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the [demonstration videos](https://feleempleo.es) "impressive", however noted that they need to 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 demo, notable entertainment-industry figures have actually [revealed](https://gitlab-zdmp.platform.zdmp.eu) substantial interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's ability to create reasonable video from text descriptions, mentioning its prospective to change storytelling and content creation. He said that his excitement about Sora's possibilities was so strong that he had chosen to pause 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 recognition model. [228] It is trained on a big dataset of diverse audio and is likewise a multi-task model that can carry out multilingual speech recognition in addition to speech translation 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 generated by MuseNet tends to start fairly however then fall into [turmoil](https://vibestream.tv) the longer it plays. [230] [231] In pop culture, initial applications of this tool were used 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 produce music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1078543) outputs tune samples. OpenAI stated the tunes "show regional musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that duplicate" and that "there is a considerable gap" in between Jukebox and human-generated music. The Verge specified "It's highly impressive, even if the outcomes seem like mushy variations of songs that might feel familiar", while Business Insider mentioned "surprisingly, a few of the resulting tunes are memorable and sound legitimate". [234] [235] [236]
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<br>User user interfaces<br>
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<br>Debate Game<br>
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<br>In 2018, OpenAI introduced the Debate Game, which teaches devices to dispute toy issues in front of a human judge. The function is to research study whether such a method may assist in auditing [AI](https://gitlab.reemii.cn) choices and in establishing explainable [AI](https://talentrendezvous.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 frequently studied in interpretability. [240] Microscope was created to analyze the [features](https://git.electrosoft.hr) that form inside these neural networks quickly. The models included are AlexNet, VGG-19, different variations of Inception, and various variations of CLIP Resnet. [241]
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<br>ChatGPT<br>
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<br>Launched in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that offers a conversational interface that enables users to ask concerns in natural language. The system then responds with an answer within seconds.<br>
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