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<br>Announced in 2016, Gym is an open-source Python library designed to assist in the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://vitricongty.com) research study, making published research study more easily reproducible [24] [144] while providing users with an easy interface for connecting with these environments. In 2022, new advancements of Gym have actually been relocated to the library Gymnasium. [145] [146] |
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<br>Gym Retro<br> |
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<br>Released in 2018, Gym Retro is a platform for reinforcement learning (RL) research on video games [147] using RL algorithms and research study generalization. Prior RL research focused mainly on optimizing agents to solve single jobs. Gym Retro provides the capability to generalize between games with comparable principles 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 at first lack understanding of how to even walk, however are offered the goals of discovering to move and to press the opposing agent out of the ring. [148] Through this adversarial learning procedure, the agents learn how to adjust to [changing conditions](https://blogram.online). When an agent is then removed from this virtual environment and positioned in a brand-new virtual environment with high winds, the agent braces to remain upright, recommending it had found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between [representatives](http://candidacy.com.ng) could produce an intelligence "arms race" that might increase a representative's ability to work even outside the context of the competitors. [148] |
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<br>OpenAI 5<br> |
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<br>OpenAI Five is a team of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that find out to play against [human players](https://jobpile.uk) at a high skill level totally through trial-and-error algorithms. Before ending up being a team of 5, the first public demonstration occurred at The International 2017, the annual best champion competition for the game, where Dendi, a professional Ukrainian gamer, lost against a bot in a [live individually](https://wiki.trinitydesktop.org) matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for two weeks of actual time, which the knowing software application was a step in the direction of developing software that can manage complicated tasks like a cosmetic surgeon. [152] [153] The system uses a kind of support knowing, as the bots discover gradually by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an enemy and taking map objectives. [154] [155] [156] |
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<br>By June 2018, the ability of the bots expanded to play together as a complete group of 5, and they had the ability to defeat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibit matches against expert players, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champs of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public appearance came later that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games. [165] |
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<br>OpenAI 5['s mechanisms](http://8.134.253.2218088) in Dota 2's bot player shows the obstacles of [AI](http://zhangsheng1993.tpddns.cn:3000) [systems](https://champ217.flixsterz.com) in multiplayer online battle arena (MOBA) video games and how OpenAI Five has actually demonstrated using deep support learning (DRL) representatives to attain superhuman [proficiency](https://gitlab.amepos.in) in Dota 2 matches. [166] |
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<br>Dactyl<br> |
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<br>Developed in 2018, Dactyl uses [device discovering](https://ai.ceo) to train a Shadow Hand, a human-like robot hand, to manipulate physical items. [167] It discovers completely in simulation using the exact same RL algorithms and [training](http://47.100.72.853000) code as OpenAI Five. OpenAI tackled the object orientation issue by utilizing domain randomization, a [simulation approach](https://visualchemy.gallery) which exposes the student to a variety of experiences instead of trying to fit to reality. The set-up for Dactyl, aside from having motion tracking video cameras, also has [RGB cameras](http://gs1media.oliot.org) to enable the robotic to manipulate an approximate object by seeing it. In 2018, OpenAI revealed that the system was able to manipulate a cube and an [octagonal prism](https://social.vetmil.com.br). [168] |
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<br>In 2019, OpenAI showed that Dactyl could solve a Rubik's Cube. The robot had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complicated physics that is harder to model. OpenAI did this by enhancing the [toughness](https://awaz.cc) of Dactyl to perturbations by using Automatic Domain [Randomization](https://git.polycompsol.com3000) (ADR), a simulation method of producing progressively more hard environments. ADR differs from manual domain randomization by not needing a human to define randomization ranges. [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://ransomware.design) models developed by OpenAI" to let developers contact it for "any English language [AI](https://forum.elaivizh.eu) job". [170] [171] |
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<br>Text generation<br> |
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<br>The business has popularized generative pretrained transformers (GPT). [172] |
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<br>OpenAI's initial GPT 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](https://gitea.imwangzhiyu.xyz) in preprint on OpenAI's website on June 11, 2018. [173] It showed how a generative model of language might obtain world knowledge and procedure long-range dependencies by pre-training on a diverse corpus with long stretches of adjoining text.<br> |
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<br>GPT-2<br> |
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<br>Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language design and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative versions at first launched to the public. The full variation of GPT-2 was not immediately released due to concern about potential abuse, including applications for writing phony news. [174] Some specialists revealed [uncertainty](https://slovenskymedved.sk) that GPT-2 postured a substantial risk.<br> |
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<br>In reaction to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "neural fake news". [175] Other researchers, such as Jeremy Howard, cautioned of "the innovation to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out 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](https://cv4job.benella.in) presentations of various circumstances of GPT-2 and other transformer models. [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 state-of-the-art 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. It prevents certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters 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 design and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the full [variation](http://114.115.218.2309005) of GPT-2 (although GPT-3 designs with as few as 125 million criteria were also trained). [186] |
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<br>OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" tasks and could generalize the purpose of a single input-output pair. The GPT-3 release paper 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 drastically enhanced benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or encountering the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 required a number of thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately released to the general public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a paid cloud API after a two-month complimentary private beta that started in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was licensed specifically to Microsoft. [190] [191] |
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<br>Codex<br> |
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<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://skillsvault.co.za) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the model can create working code in over a lots shows languages, the majority of effectively in Python. [192] |
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<br>Several issues with glitches, design flaws and security vulnerabilities were pointed out. [195] [196] |
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<br>GitHub Copilot has been accused of giving off copyrighted code, without any author attribution or license. [197] |
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<br>OpenAI announced that they would discontinue support for Codex API on March 23, 2023. [198] |
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<br>GPT-4<br> |
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<br>On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar exam 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 might likewise check out, evaluate or produce as much as 25,000 words of text, and compose code in all major programs languages. [200] |
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<br>Observers reported that the iteration of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based model, with the caveat that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is also capable of taking images as input on ChatGPT. [202] OpenAI has declined to expose various technical details and statistics about GPT-4, such as the precise size of the model. [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 create text, images and audio. [204] GPT-4o attained modern lead to voice, multilingual, and vision benchmarks, setting brand-new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller sized version of GPT-4o 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 especially helpful for enterprises, start-ups and developers looking for to [automate services](https://dessinateurs-projeteurs.com) with [AI](http://tanpoposc.com) agents. [208] |
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<br>o1<br> |
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<br>On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have actually been developed to take more time to consider their responses, resulting in greater accuracy. These designs are especially effective in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was changed by o1. [211] |
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<br>o3<br> |
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<br>On December 20, 2024, OpenAI revealed o3, the follower of the o1 reasoning design. OpenAI likewise unveiled o3-mini, a lighter and [quicker variation](https://micircle.in) of OpenAI o3. Since December 21, 2024, this design 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 chance to obtain early access to these models. [214] The model is called o3 instead of o2 to avoid confusion with telecommunications providers O2. [215] |
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<br>Deep research<br> |
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<br>Deep research study is an agent established by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to carry out comprehensive web surfing, information analysis, and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools enabled, it reached an accuracy 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](http://git.info666.com) in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to analyze the semantic similarity in between text and images. It can especially 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 model that creates images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to interpret natural (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images. It can produce pictures of realistic things ("a stained-glass window with a picture of a blue strawberry") as well as 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 DALL-E 2, an updated version of the design with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new simple system for transforming 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 much better able to create images from complex descriptions without manual prompt engineering and render complex [details](http://39.106.8.2463003) like hands and text. [221] It was launched to the public as a ChatGPT Plus feature in October. [222] |
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<br>Text-to-video<br> |
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<br>Sora<br> |
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<br>Sora is a text-to-video design that can create videos based on brief detailed prompts [223] as well as extend existing videos forwards or backwards in time. [224] It can produce videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of created videos is unknown.<br> |
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<br>Sora's development group named it after the Japanese word for "sky", to represent its "unlimited imaginative potential". [223] Sora's innovation is an [adaptation](https://albion-albd.online) of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos accredited for that purpose, however did not reveal the number or the [specific sources](https://www.characterlist.com) of the videos. [223] |
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<br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, stating that it might create videos up to one minute long. It also shared a technical report highlighting the approaches used to train the model, and the design's capabilities. [225] It acknowledged some of its shortcomings, including struggles mimicing [complicated physics](https://incomash.com). [226] Will [Douglas Heaven](https://git.aionnect.com) of the MIT Technology Review called the demonstration videos "excellent", however kept in mind that they must have been cherry-picked and may not represent Sora's typical output. [225] |
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<br>Despite uncertainty from some academic leaders following Sora's public demo, noteworthy entertainment-industry figures have actually [revealed considerable](https://git.lona-development.org) interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's ability to generate [practical video](http://engineerring.net) from text descriptions, mentioning its possible to revolutionize storytelling and content development. He said that his enjoyment about [Sora's possibilities](https://video.disneyemployees.net) was so strong that he had chosen to pause prepare for expanding his [Atlanta-based movie](https://www.zapztv.com) studio. [227] |
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<br>Speech-to-text<br> |
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<br>Whisper<br> |
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<br>Released in 2022, Whisper is a general-purpose speech recognition design. [228] It is trained on a big dataset of [varied audio](http://t93717yl.bget.ru) and is likewise a multi-task model that can perform multilingual speech recognition along with speech translation and [language recognition](https://git.antonshubin.com). [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](http://gitlab.adintl.cn) net trained to anticipate subsequent musical notes in MIDI music files. It can produce songs with 10 instruments in 15 designs. According to The Verge, a [song generated](http://sintec-rs.com.br) by MuseNet tends to start fairly but then fall into turmoil the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were utilized as early as 2020 for the internet psychological [thriller](https://gitlab.wah.ph) 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 bit of lyrics and outputs tune samples. OpenAI specified the songs "show local musical coherence [and] follow standard chord patterns" however acknowledged that the songs lack "familiar larger musical structures such as choruses that repeat" which "there is a significant gap" between Jukebox and human-generated music. The Verge stated "It's highly remarkable, even if the outcomes sound like mushy variations of tunes that may feel familiar", while Business Insider stated "remarkably, a few of the resulting songs are appealing and sound legitimate". [234] [235] [236] |
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<br>Interface<br> |
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<br>Debate Game<br> |
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<br>In 2018, OpenAI launched the Debate Game, [garagesale.es](https://www.garagesale.es/author/jonathanfin/) which teaches machines to dispute toy problems in front of a human judge. The purpose is to research study whether such an approach might help in auditing [AI](https://git.gra.phite.ro) choices and in establishing explainable [AI](https://aggm.bz). [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 nerve cell of eight neural network models which are typically studied in interpretability. [240] Microscope was created to examine the [functions](http://www.gbape.com) that form inside these [neural networks](https://gigsonline.co.za) easily. The models included are AlexNet, VGG-19, different versions 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 an expert system tool developed on top of GPT-3 that offers a [conversational](https://jobspaddy.com) user [interface](https://newborhooddates.com) that allows users to ask concerns in natural language. The system then reacts with a response within seconds.<br> |
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