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 facilitate the advancement of [support learning](http://hychinafood.edenstore.co.kr) algorithms. It aimed to standardize how environments are defined in [AI](https://gitea.lelespace.top) research study, making [released](http://135.181.29.1743001) research study more quickly reproducible [24] [144] while providing users with an easy user interface for engaging with these environments. In 2022, brand-new developments of Gym have been transferred 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 reinforcement knowing (RL) research study on computer game [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing agents to solve single jobs. Gym Retro provides the capability to generalize in between games with comparable concepts but different 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 at first do not have understanding of how to even walk, but are provided the objectives of discovering to move and to press the opposing agent out of the ring. [148] Through this adversarial learning procedure, the representatives discover how to adjust to changing conditions. When an agent is then eliminated from this virtual environment and put in a brand-new virtual environment with high winds, the representative braces to remain upright, suggesting it had found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives could create an intelligence "arms race" that could increase a representative's capability to operate even outside the [context](https://thedatingpage.com) of the competition. [148]
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<br>OpenAI 5<br>
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<br>OpenAI Five is a team 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 ending up being a group of 5, [links.gtanet.com.br](https://links.gtanet.com.br/fredricbucki) the very first public demonstration took place at The International 2017, the annual best championship tournament for the video game, where Dendi, a professional 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 two weeks of genuine time, and that the [learning software](http://bhnrecruiter.com) application was an action in the instructions of creating software application that can handle complicated tasks like a cosmetic surgeon. [152] [153] The system uses a form of support knowing, as the bots find out with time by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an enemy and [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1073855) 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 full group of 5, and they were able to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against professional players, but wound up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs of the game at the time, [fishtanklive.wiki](https://fishtanklive.wiki/User:KentonR156) 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those video games. [165]
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<br>OpenAI 5['s systems](http://git.kdan.cc8865) in Dota 2's bot gamer reveals the challenges of [AI](http://harimuniform.co.kr) systems in [multiplayer online](http://git.nikmaos.ru) battle arena (MOBA) video games and [wiki.myamens.com](http://wiki.myamens.com/index.php/User:TawnyaWhitley87) how OpenAI Five has actually demonstrated making use of deep reinforcement knowing (DRL) agents to [attain superhuman](https://manpoweradvisors.com) skills in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl uses device discovering to train a Shadow Hand, a human-like robot hand, to manipulate physical objects. [167] It [discovers totally](https://www.ajirazetu.tz) in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation issue by utilizing domain randomization, a simulation approach which exposes the student to a range of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking cameras, likewise has RGB electronic cameras to permit the robotic to [control](http://120.77.67.22383) an approximate things by seeing it. In 2018, OpenAI showed that the system was able to [control](http://git.dgtis.com) a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI demonstrated that Dactyl might resolve a [Rubik's Cube](https://git.logicloop.io). The robot was able to solve 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 technique of creating progressively more difficult environments. ADR differs from manual domain randomization 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 announced a multi-purpose API which it said was "for accessing brand-new [AI](https://git.lodis.se) designs developed by OpenAI" to let designers call on it for "any English language [AI](https://git.panggame.com) job". [170] [171]
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<br>Text generation<br>
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<br>The company has actually popularized generative pretrained transformers (GPT). [172]
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<br>OpenAI's [initial GPT](https://app.zamow-kontener.pl) design ("GPT-1")<br>
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<br>The initial paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his colleagues, and released in preprint on [OpenAI's website](https://dreamtube.congero.club) on June 11, 2018. [173] It showed how a [generative](http://40th.jiuzhai.com) design of language might obtain world knowledge 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 follower to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with only minimal demonstrative versions initially released to the general public. The full variation of GPT-2 was not instantly released due to concern about potential abuse, consisting of applications for composing fake news. [174] Some professionals revealed uncertainty that GPT-2 presented a significant risk.<br>
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<br>In action to GPT-2, the Allen Institute for Artificial Intelligence [responded](http://47.97.6.98081) with a tool to find "neural phony news". [175] Other scientists, such as Jeremy Howard, alerted of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the total variation of the GPT-2 language model. [177] Several websites host interactive demonstrations of various circumstances of GPT-2 and other transformer designs. [178] [179] [180]
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<br>GPT-2's authors argue without supervision language models to be general-purpose learners, highlighted by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the design 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 a little 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of [characters](https://gulfjobwork.com) by encoding both individual 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 without supervision transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI mentioned that the complete variation of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were also trained). [186]
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<br>OpenAI mentioned 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 learning between English and Romanian, and between English and German. [184]
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<br>GPT-3 [considerably improved](https://giaovienvietnam.vn) benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language designs could be approaching or coming across the essential ability constraints of predictive language designs. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not right away released to the public for issues of possible abuse, although OpenAI planned to allow gain 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 certified 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](https://huconnect.org) of GPT-3 that has actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://live.gitawonk.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the design can create working code in over a lots programs languages, the majority of efficiently in Python. [192]
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<br>Several concerns with glitches, design flaws and security vulnerabilities were cited. [195] [196]
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<br>GitHub Copilot has actually been accused of emitting copyrighted code, without any author attribution or license. [197]
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<br>OpenAI revealed that they would cease assistance for Codex API on March 23, 2023. [198]
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<br>GPT-4<br>
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<br>On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the updated technology passed a simulated law school bar exam with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise check out, [examine](https://stepstage.fr) or generate approximately 25,000 words of text, and write code in all major programs languages. [200]
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<br>Observers reported that the version of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained some of the issues with earlier modifications. [201] GPT-4 is also [capable](https://www.yiyanmyplus.com) of taking images as input on ChatGPT. [202] OpenAI has decreased to expose various technical details and data about GPT-4, such as the exact size of the model. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and produce text, images and audio. [204] GPT-4o [attained state-of-the-art](https://www.mapsisa.org) lead to voice, multilingual, and vision criteria, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207]
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized 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 expects it to be particularly useful for enterprises, startups and developers looking for to automate services with [AI](https://git.noisolation.com) representatives. [208]
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<br>o1<br>
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<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have actually been designed to take more time to consider their responses, causing higher precision. These models are especially efficient 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 model. OpenAI also revealed o3-mini, a lighter and faster version of OpenAI o3. As of December 21, 2024, this design is not available for public usage. 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 design 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 a representative established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 design to carry out comprehensive web browsing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [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 evaluate the semantic similarity between text and [fishtanklive.wiki](https://fishtanklive.wiki/User:DouglasWhitney) 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](http://101.52.220.1708081) in 2021, DALL-E is a Transformer model that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of an unfortunate capybara") and create matching images. It can [produce](https://niaskywalk.com) images of sensible items ("a stained-glass window with a picture of a blue strawberry") as well as items that do not exist in reality ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.<br>
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<br>DALL-E 2<br>
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<br>In April 2022, OpenAI revealed DALL-E 2, an upgraded version of the model with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new [primary](https://121.36.226.23) 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 announced DALL-E 3, a more powerful model better able to [produce images](http://gitlab.fuxicarbon.com) from intricate [descriptions](http://8.136.197.2303000) without manual timely engineering and [render complicated](http://1.119.152.2304026) 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 design that can produce videos based on short detailed prompts [223] along with extend existing videos forwards or backwards in time. [224] It can create videos with resolution up to 1920x1080 or 1080x1920. The maximal length of produced videos is unidentified.<br>
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<br>Sora's development team called it after the Japanese word for "sky", to represent its "endless imaginative potential". [223] Sora's innovation is an adjustment of the technology behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos accredited for that function, but did not expose the number or the specific sources of the videos. [223]
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<br>OpenAI showed some [Sora-created high-definition](https://endhum.com) videos to the general public on February 15, 2024, specifying that it might create videos as much as one minute long. It likewise shared a technical report highlighting the techniques used to train the design, and the design's abilities. [225] It acknowledged some of its drawbacks, including struggles replicating complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "remarkable", however noted that they should 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 shown significant interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry expressed his awe at the technology's ability to produce practical video from text descriptions, mentioning its possible to change storytelling and material creation. He said that his enjoyment about Sora's possibilities was so strong that he had actually chosen to stop briefly plans 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 large dataset of diverse audio and is also a multi-task design that can perform multilingual speech acknowledgment as well as 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 forecast subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to [start fairly](https://my-sugar.co.il) however then fall under turmoil the longer it plays. [230] [231] In popular culture, initial applications of this tool were used as early as 2020 for the internet mental 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 create music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs song [samples](http://git.pushecommerce.com). OpenAI specified the tunes "reveal local musical coherence [and] follow standard chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" which "there is a substantial space" in between Jukebox and human-generated music. The Verge stated "It's technically impressive, even if the results seem like mushy variations of tunes that may feel familiar", while Business Insider specified "surprisingly, a few 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 launched the Debate Game, [links.gtanet.com.br](https://links.gtanet.com.br/zarakda51931) which teaches makers to issues in front of a human judge. The purpose is to research whether such a technique might assist in auditing [AI](https://shankhent.com) decisions and in establishing explainable [AI](http://110.41.143.128:8081). [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 8 neural network models which are often studied in interpretability. [240] Microscope was produced to evaluate the features that form inside these neural networks easily. The designs included are AlexNet, VGG-19, various variations of Inception, and different variations 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 supplies a conversational user interface that allows users to ask questions in natural language. The system then reacts with a response within seconds.<br>
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