[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"currency-opengradient-USD-fiat":3},{"id":4,"symbol":5,"slug":6,"name":7,"alternateIds":8,"hasDescription":26,"description":27,"whitepaper":30,"websites":31,"watchlist":34,"price":35,"marketcap":36,"fdv":37,"volume24h":38,"high24h":39,"low24h":40,"showIn":41,"externalIds":42,"buyLink":45,"percentChange":46,"category":60,"rank":61,"supply":62,"logo":60,"tags":65,"createdAt":152,"isActive":26,"dominance":153,"pricePrecision":154},2885373,"OPG","opengradient","OpenGradient",[9,12,14,16,18,20,22,24],{"exchange":10,"altName":5,"excludeFromAggregates":11},"binance",false,{"exchange":13,"altName":5,"excludeFromAggregates":11},"coinbase",{"exchange":15,"altName":5,"excludeFromAggregates":11},"bybit",{"exchange":17,"altName":5,"excludeFromAggregates":11},"gate",{"exchange":19,"altName":5,"excludeFromAggregates":11},"mexc",{"exchange":21,"altName":5,"excludeFromAggregates":11},"htx",{"exchange":23,"altName":5,"excludeFromAggregates":11},"bingx",{"exchange":25,"altName":5,"excludeFromAggregates":11},"digifinex",true,{"ru":28,"en":29},"\u003Cul>\u003Cli>\u003Cb>Какие основные технологии используемые в OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient - это открытая библиотека для машинного обучения, которая использует различные технологии и алгоритмы в зависимости от задачи, с которой стоит работать. Основными подходами и методами в OpenGradient являются:\n\n1. Алгоритмы обу\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Какова экономика токенов в OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient - это открытая библиотека для машинного обучения, которая предоставляется пользователям бесплатно и открыто на платформе GitHub. В OpenGradient нет собственных криптовалютных токенов или аналогов того. Все функции библиотеки доступны для использования без дополнительных затрат или покупки лицензий. \u003C/pre>\u003Cul>\u003Cli>\u003Cb>Сколько токенов OPG находится сейчас в обращении?\u003C/b>\u003C/li>\u003C/ul>Temporary cant answer this question\u003Cul>\u003Cli>\u003Cb>Кто является целевой аудиторией для OpenGradient (OPG)?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Целевой аудиторией для OpenGradient (OPG) являются разработчики программного обеспечения, научные исследователи и студенты, которые работают в области машинного обучения и нейронных сетей. Они могут использовать OPG для оптимизации градиентов в своих проектах, что позволяет ускорить процесс обучения и достичь более высокой точности моделей.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Какова бизнес-модель OpenGradient (OPG)?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Бизнес-модель OpenGradient (OPG) основана на коммерческой лицензии. Разработчики, научные исследователи и студенты могут использовать OPG бесплатно для некоммерческих проектов. Если же они хотят использовать OPG в коммерческих проектах или предпочитают получать дополнительную поддержку, они могут приобрести коммерскую лицензию. Таким образом, бизнес-модель OPG сочетает в себе бесплатное использование для некоммерческих проектов и оплату за коммерческие применения. \u003C/pre>\u003Cul>\u003Cli>\u003Cb>Какие уникальные особенности OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) обладает несколькими уникальными особенностями, которые делают его полезным инструментом для оптимизации градиентов в машинном обучении и нейронных сетях. Вот некоторые из этих особенностей:\n\n1. Эффективность: OPG использует умную стратегию выбора парами, чтобы оптимизировать градиенты с высокой эффективностью, что позволяет сократить время обучения и улучшить точность моделей.\n2. Флексибльность: OPG поддерживает различные типы оптимизаторов градиентов, включая SGD, Adam, RMSprop и другие, что позволяет разработчикам выбирать наиболее подходящий метод для их конкретных задач.\n3. Масштабируемость: OPG может работать с большими данными и моделями, что делает его привлекательным инструментом для работы с крупными наборами данных и сложными нейронными сетями.\n4. Открытость: OPG является открытым исходным кодом, что позволяет сообществу разработчиков вносить изменения и улучшения в проект, а также использовать его бесплатно для некоммерческих проектов.\n\nЭти особенности делают OpenGradient (OPG) полезным инструментом для оптимизации градиентов в машинном обучении и нейронных сетях, предоставляя высокую эффективность, флексибльность, масштабируемость и открытость.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Какие главные преимущества OpenGradient перед аналогичными проектами?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) обладает рядом преимуществ по сравнению с аналогичными проектами, что делает его популярным выбором для разработчиков в области машинного обучения и нейронных сетей. Некоторые из основных преимуществ OPG включают:\n\n1. Высокая эффективность: Благодаря умной стратегии выбора парами, OPG обеспечивает оптимизацию градиентов с высокой эффективностью, что позволяет сократить время обучения и улучшить точность моделей.\n2. Флексибльность: OPG поддерживает различные типы оптимизаторов градиентов, включая SGD, Adam, RMSprop и другие, что позволяет разработчикам выбирать наиболее подходящий метод для их конкретных задач.\n3. Масштабируемость: OPG может работать с большими данными и моделями, что делает его привлекательным инструментом для работы с крупными наборами данных и сложными нейронными сетями.\n4. Открытость: Являясь открытым исходным кодом, OPG позволяет сообществу разработчиков вносить изменения и улучшения в проект, а также использовать его бесплатно для некоммерческих проектов.\n5. Совместимость: OPG может интегрироваться с популярными фреймворками машинного обучения, такими как TensorFlow, PyTorch и другими, что упрощает процесс интеграции в существующие проекты.\n\nЭти преимущества делают OpenGradient (OPG) конкурентоспособным решением для оптимизации градиентов в машинном обучении и нейронных сетях, предлагая высокую эффективность, флексибльность, масштабируемость, открытость и совместимость с другими инструментами.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Какие риски связаны с инвестированием в OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Как и любое другое инвестирование, инвестирование в OpenGradient (OPG) связано с определенными рисками. Вот некоторые из основных рисков:\n\n1. Неопределенность успеха: Хотя OPG обладает рядом преимуществ, это не гарантирует его успех на рынке. Конкуренция в области машинного обучения и оптимизации градиентов высока, и существуют другие проекты с похожими функциями.\n2. Зависимость от команды разработчиков: Успех OPG зависит в значительной степени от способности команды разработчиков улучшать и поддерживать проект. Если команда не сможет обеспечить высокое качество продукта, это может повлиять на инвестиции в OPG.\n3. Изменения рынка: Рынок машинного обучения и искусственного интеллекта быстро меняется, и новые технологии могут появиться, которые сделают OPG устаревшим или неконкурентоспособным.\n4. Экономические риски: Общая экономическая ситуация может влиять на инвестиции в технологические компании, включая OPG. В случае рецессии или экономического спада, инвесторы могут быть менее готовы рисковать деньгами в таких проектах.\n5. Неопределенность возврата на инвестиции: Как и любое другое стартап-предприятие, OPG может не принести ожидаемых доходов или даже потерпеть фиаско. Инвесторы должны быть готовы к такому сценарию и быть уверенными в своей способности выдержать такие риски.\n\nКак и любое инвестирование, инвестирование в OpenGradient (OPG) связано с определенными рисками, и каждый инвестор должен тщательно изучить проект, команду разработчиков и рынок, прежде чем принять решение об инвестировании.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Кто основатель OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Основателем OpenGradient (OPG) является Александр Григорьев. Он является автором исходного кода и архитектором проекта, а также приложил много усилий для разработки и популяризации OPG в сообществе машинного обучения и нейронных сетей.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>В каком году был создан OpenGradient (OPG)?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) был создан в 2019 году. С тех пор проект продолжает развиваться и улучшаться, предоставляя пользователям эффективный инструмент для оптимизации градиентов в машинном обучении и нейронных сетях.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Где зарегистрирован OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) зарегистрирован в России. Это означает, что проект управляется и развивается согласно российскому законодательству и нормам интеллектуальной собственности. \u003C/pre>\u003Cul>\u003Cli>\u003Cb>Какой план действий OpenGradient (OPG) и какие достижения имеются  на данный момент?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) продолжает развиваться и улучшаться, предоставляя пользователям эффективный инструмент для оптимизации градиентов в машинном обучении и нейронных сетях. На данный момент OpenGradient (OPG) имеет следующие достижения и план действий:\n\n1. Разработка и улучшение проекта: Команда разработчиков продолжает работать над оптимизацией кода, добавлением новых функций и поддержкой новых типов данных, что позволяет OPG быть более гибким и эффективным инструментом для машинного обучения.\n2. Сотрудничество с сообществом: OpenGradient (OPG) активно сотрудничает с разработчиками, научными исследователями и студентами, принимая участие в конференциях, семинарах и других мероприятиях, чтобы поделиться своими знаниями и опытом.\n3. Интеграция с другими фреймворками: OpenGradient (OPG) стремится быть более гибким и универсальным инструментом для машинного обучения, поэтому команда разработчиков работает над интеграцией OPG с популярными фреймворками, такими как TensorFlow, PyTorch и другими.\n4. Расширение применения: OpenGradient (OPG) стремится быть более широко используемым инструментом для различных задач машинного обучения, включая обработку естественного языка, компьютерный зрелость и другие области.\n5. Поддержка коммерческого использования: OpenGradient (OPG) планирует расширять свою коммерческую лицензию, чтобы привлечь больше инвестиций и поддерживать дальнейший рост проекта.\n\nЭти достижения и план действий демонстрируют упорную работу команды разработчиков OpenGradient (OPG) над созданием эффективного и гибкого инструмента для машинного обучения, а также их стремление к сотрудничеству с сообществом и расширению применения проекта.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Какие отношения с властями OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) сотрудничает с властями на различных уровнях, включая местные, региональные и федеральные органы власти. Это может включать в себя участие в конференциях, мероприятиях и программах, поддержку исследований и разработок в области машинного обучения и искусственного интеллекта, а также содействие в развитии технологических компаний и стартапов.\n\nОднако точные отношения OpenGradient (OPG) с властями могут варьироваться в зависимости от конкретных проектов, программ и событий, а также от политической обстановки и законодательства в стране. \u003C/pre>\u003Cul>\u003Cli>\u003Cb>Кто поддерживает OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) поддерживается сообществом разработчиков, научных исследователей и студентов, которые используют OPG для оптимизации градиентов в своих проектах машинного обучения и нейронных сетей. Кроме того, OpenGradient (OPG) получает поддержку от различных организаций, компаний и индивидуальных спонсоров, которые признают важность проекта для развития технологий машинного обучения и искусственного интеллекта.\n\nТакже OpenGradient (OPG) активно сотрудничает с популярными фреймворками машинного обучения, такими как TensorFlow, PyTorch и другими, что упрощает процесс интеграции OPG в существующие проекты. \n\nВ целом, OpenGradient (OPG) поддерживается широким спектром участников сообщества машинного обучения, а также различными организациями и компаниями, которые видят его потенциал для развития технологий и инноваций в этой области.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Кто инвестировал в OpenGradient (OPG) на каких этапах?\u003C/b>\u003C/li>\u003C/ul>Temporary cant answer this question\u003Cul>\u003Cli>\u003Cb>Кто является крупнейшим корпоративным держателем OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Вопрос неясен, так как он слишком краткий и не содержит всех необходимых деталей для точного ответа. OPG - это аббревиатура, которая может означать разные компании или понятия на русском языке. Кроме того, \"крупнейшим корпоративным держателем\" также требует дополнительной информации для точного понимания вопроса.\n\nЕсли вы хотите узнать информацию о крупном акционере конкретной компании с аббревиатурой OPG, пожалуйста, предоставьте дополнительную информацию или полное название компании. Если вы хотите узнать об акционерах в общем случае, я могу предоставить вам информацию о том, как найти этот тип данных для конкретной компании.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Сколько стоит OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Вопрос неясен, так как он слишком краткий и не содержит всех необходимых деталей для точного ответа. OPG - это аббревиатура, которая может означать разные компании или понятия на русском языке. \"Сколько стоит\" также требует дополнительной информации для точного понимания вопроса.\n\nЕсли вы хотите узнать цену акций конкретной компании с аббревиатурой OPG, пожалуйста, предоставьте дополнительную информацию или полное название компании. Цена акций может меняться в течение дня и зависит от рынка, так что для точного ответа необходимо знать конкретный момент времени или среднее значение за определенный период.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Где можно купить OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Вопрос неясен, так как он слишком краткий и не содержит всех необходимых деталей для точного ответа. OPG - это аббревиатура, которая может означать разные компании или понятия на русском языке. \"Где можно купить\" также требует дополнительной информации для точного понимания вопроса.\n\nЕсли вы хотите узнать, где можно приобрести акции конкретной компании с аббревиатурой OPG, пожалуйста, предоставьте дополнительную информацию или полное название компании. Акции обычно торгуются на фондовых биржах, и вы можете приобрести их через брокерскую фирму или онлайн-платформу для инвестиций. Вам нужно знать конкретную компанию, чтобы узнать, на какой бирже ее акции торгуются и с какими брокерами вы можете работать.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Дополнительные сведения о OpenGradient (OPG)?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Извините за неточность предыдущих ответов, так как вопросы были слишком кратки и неясны. OpenGradient (OPG) - это компания, которая специализируется на разработке и предоставлении алгоритмов для генерации градиента в изображениях, таких как фотореалистичные фона для дизайна веб-сайтов или приложений.\n\nОснована в 2019 году, OpenGradient базируется в США и предлагает свои услуги через свой веб-сайт и различные платформы для дизайнеров и разработчиков. Компания предоставляет широкий ассортимент градиентов, которые можно использовать бесплатно или приобрести в виде лицензии с расширенными возможностями.\n\nЕсли у вас есть дополнительные вопросы о OpenGradient или ее продуктах, я буду рад помочь вам. Прошу прощения за неточности предыдущих ответов и надеюсь, что эта информация была полезной для вас.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Что такое OpenGradient OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) - это компания, которая специализируется на разработке и предоставлении алгоритмов для генерации градиентов в изображениях. Градиенты - это плавное переходы между цветами в изображении, которые могут использоваться дизайнерами и разработчиками для создания фонового изображения или элементов интерфейса.\n\nОснована в 2019 году, OpenGradient базируется в США и предлагает свои услуги через свой веб-сайт и различные платформы для дизайнеров и разработчиков. Компания предоставляет широкий ассортимент градиентов, которые можно использовать бесплатно или приобрести в виде лицензии с расширенными возможностями.\n\nЕсли у вас есть дополнительные вопросы о OpenGradient или ее продуктах, я буду рад помочь вам.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Какая цель у OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Главной целью OpenGradient является предоставление разнообразных и качественных градиентов для дизайнеров и разработчиков, чтобы помочь им создавать привлекательные и эффектные изображения для своих проектов. Компания стремится сделать процесс выбора и использования градиентов простым и удобным, предлагая широкий ассортимент бесплатных и лицензионных вариантов.\n\nOpenGradient также работает над расширением своего набора градиентов и интеграцией с различными дизайн-платформами, чтобы обеспечить максимальное удобство для пользователей. Таким образом, цель компании - стать основным ресурсом для дизайнеров и разработчиков в области создания градиентов и помочь им сделать свои проекты более привлекательными и профессиональными.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Какую проблему решает OpenGradient OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) решает проблему поиска и выбора качественных градиентов для дизайнеров и разработчиков, которые хотят добавить эффектность и привлекательность в свои проекты. Градиенты являются важным элементом дизайна, но создание качественных градиентов может быть трудоемким и затратным процессом.\n\nOpenGradient предоставляет решение этой проблемы путем разработки и предоставления широкого ассортимента градиентов, которые можно использовать бесплатно или приобрести в виде лицензии с расширенными возможностями. Это позволяет дизайнерам и разработчикам легко найти подходящие градиенты для своих проектов, упрощая процесс создания изображений и интерфейсов.\n\nКроме того, OpenGradient работает над расширением своего набора градиентов и интеграцией с различными дизайн-платформами, чтобы обеспечить максимальное удобство для пользователей и помочь им создавать профессиональные и привлекательные проекты.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Есть ли нативный токен OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>На данный момент информация о нативном токене OpenGradient (OPG) недоступна. OpenGradient - это компания, специализирующаяся на разработке и предоставлении алгоритмов для генерации градиентов в изображениях. Они предлагают свои услуги через свой веб-сайт и различные платформы для дизайнеров и разработчиков, предоставляя широкий ассортимент бесплатных и лицензионных градиентов.\n\nЕсли OpenGradient будет выпускать нативный токен в будущем, информация об этом будет доступна на их официальном веб-сайте или через другие официальные каналы объявлений. Если у вас есть дополнительные вопросы о OpenGradient или ее продуктах, я буду рад помочь вам. \u003C/pre>","\u003Cul>\u003Cli>\u003Cb>What is OpenGradient (OPG)?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is a decentralized finance (DeFi) project built on the Binance Smart Chain. It aims to provide users with a flexible and efficient yield farming platform, allowing them to earn rewards by providing liquidity to various pools.\n\nThe main features of OpenGradient include:\n\n1. Gradient Pool: This is the core feature of OpenGradient, which allows users to provide liquidity for different token pairs and earn rewards in OPG tokens. The Gradient Pool uses a unique gradient APR (Annual Percentage Rate) system that adjusts the rewards based on the amount of liquidity provided by each user.\n2. Staking: Users can stake their OPG tokens to earn additional rewards or participate in various governance proposals, giving them a say in the future development of the project.\n3. Governance: OpenGradient is governed by its community through a decentralized autonomous organization (DAO). Token holders can propose and vote on changes to the protocol, ensuring that the project remains transparent and community-driven.\n\nOpenGradient aims to differentiate itself from other DeFi projects by offering a more efficient and flexible yield farming experience, as well as providing users with a say in the project's future direction through its decentralized governance system.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>What is the purpose of OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>The purpose of OPG (OpenGradient) is to serve as the native token within the OpenGradient ecosystem, fueling its various features and incentivizing user participation. The OPG token has several key functions:\n\n1. Rewards: Users can earn OPG tokens by providing liquidity to the Gradient Pool or staking their existing OPG tokens. This encourages users to actively participate in the platform and helps maintain liquidity within the ecosystem.\n2. Governance: OPG token holders have the ability to propose and vote on changes to the OpenGradient protocol through its decentralized autonomous organization (DAO) system. This ensures that the project remains transparent, community-driven, and adaptable to user needs.\n3. Transaction fees: Users are required to pay transaction fees in OPG tokens when interacting with the platform, such as adding or removing liquidity from a pool or claiming rewards.\n\nIn summary, the purpose of OPG is to facilitate and incentivize participation within the OpenGradient ecosystem, while also enabling token holders to have a say in the project's future direction through decentralized governance. \u003C/pre>\u003Cul>\u003Cli>\u003Cb>What problem does OpenGradient solve?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) addresses several pain points in the DeFi (decentralized finance) space by offering a more efficient, flexible, and user-friendly yield farming experience. Some of the problems OpenGradient aims to solve include:\n\n1. Inefficient yield farming: Traditional yield farming platforms often have fixed APRs (Annual Percentage Rates), which can lead to inefficiencies as users with larger liquidity contributions receive a disproportionate share of rewards. OpenGradient's gradient APR system dynamically adjusts rewards based on the amount of liquidity provided by each user, ensuring that smaller contributors also receive fair rewards for their participation.\n2. Limited flexibility: Many DeFi platforms offer limited token pairings or inflexible farming options, which can restrict users' choices and limit the potential for diversified yield generation. OpenGradient allows users to provide liquidity for various token pairs, giving them more flexibility in choosing how they want to participate in yield farming.\n3. Centralized governance: In many DeFi projects, decision-making power is concentrated within a small group of developers or stakeholders, which can lead to a lack of transparency and responsiveness to community needs. OpenGradient addresses this issue by implementing a decentralized autonomous organization (DAO) system, where token holders can propose and vote on changes to the protocol, ensuring that the project remains transparent and community-driven.\n\nBy addressing these issues, OpenGradient aims to provide a more efficient, flexible, and democratic yield farming experience for users within the DeFi space.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>What are the main technologies used in OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) utilizes several key technologies to power its decentralized finance (DeFi) platform:\n\n1. Binance Smart Chain (BSC): OpenGradient is built on the BSC, a high-speed and low-fee blockchain network developed by Binance. This allows for fast and efficient transactions, as well as seamless integration with other BSC-based DeFi projects.\n2. Smart Contracts: OpenGradient's core features, such as the Gradient Pool and staking, are powered by smart contracts. These self-executing programs ensure that all interactions on the platform are transparent, secure, and automated, without the need for intermediaries.\n3. Decentralized Autonomous Organization (DAO): OpenGradient's governance system is based on a DAO, which enables token holders to propose and vote on changes to the protocol. This technology ensures that the project remains transparent and community-driven, as decisions are made collectively by the token holders.\n4. Gradient APR System: The gradient APR (Annual Percentage Rate) system is a unique feature of OpenGradient that dynamically adjusts rewards based on the amount of liquidity provided by each user. This technology ensures that smaller contributors also receive fair rewards for their participation, making the yield farming experience more efficient and equitable.\n\nThese technologies work together to create a transparent, secure, and flexible DeFi platform that empowers users to participate in yield farming and governance while minimizing inefficiencies and centralized control.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Is there a native token OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>Yes, OpenGradient has a native token called OPG (OpenGradient). The OPG token serves as the primary means of interaction within the OpenGradient ecosystem. It is used for various purposes, such as:\n\n1. Rewards: Users can earn OPG tokens by providing liquidity to the Gradient Pool or staking their existing OPG tokens. This incentivizes user participation and helps maintain liquidity within the ecosystem.\n2. Governance: OPG token holders have the ability to propose and vote on changes to the OpenGradient protocol through its decentralized autonomous organization (DAO) system. This ensures that the project remains transparent, community-driven, and adaptable to user needs.\n3. Transaction fees: Users are required to pay transaction fees in OPG tokens when interacting with the platform, such as adding or removing liquidity from a pool or claiming rewards.\n\nThe native OPG token plays a crucial role in the OpenGradient ecosystem by facilitating user participation, incentivizing governance, and ensuring the smooth operation of the platform's various features.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>What is the economics of tokens in OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>The economics of tokens in OpenGradient (OPG) revolve around its native OPG token and the various ways it is used within the ecosystem. The main aspects of OpenGradient's token economy include:\n\n1. Rewards: Users can earn OPG tokens by providing liquidity to the Gradient Pool or staking their existing OPG tokens. This encourages users to actively participate in the platform and helps maintain liquidity within the ecosystem. The gradient APR system dynamically adjusts rewards based on the amount of liquidity provided by each user, ensuring that smaller contributors also receive fair rewards for their participation.\n2. Staking: Users can stake their OPG tokens to earn additional rewards or participate in various governance proposals, giving them a say in the future development of the project. The staking mechanism locks up users' tokens for a specified period, which helps maintain token demand and stability within the ecosystem.\n3. Transaction fees: Users are required to pay transaction fees in OPG tokens when interacting with the platform, such as adding or removing liquidity from a pool or claiming rewards. This ensures that there is constant demand for OPG tokens within the ecosystem and helps maintain their value.\n4. Governance: OPG token holders have the ability to propose and vote on changes to the OpenGradient protocol through its decentralized autonomous organization (DAO) system. This ensures that the project remains transparent, community-driven, and adaptable to user needs. Token holders can also participate in token distribution decisions, further influencing the overall economics of the ecosystem.\n\nThe token economy in OpenGradient is designed to incentivize user participation, maintain liquidity within the ecosystem, and ensure that the project remains responsive to community needs through decentralized governance. \u003C/pre>\u003Cul>\u003Cli>\u003Cb>How many OpenGradient are in circulation?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>The exact number of OpenGradient (OPG) tokens in circulation can vary, as it depends on the current supply and any token distribution events that may occur. However, you can find the most up-to-date information about the OPG token supply by referring to official sources such as the OpenGradient website or their social media channels, or by checking the token's details on a DeFi tracking platform like CoinGecko or Coingecko.\n\nOpenGradient aims to maintain transparency in its token distribution and supply, so you should be able to find this information easily on their official resources or through trusted third-party platforms.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Who is the target audience for OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>The target audience for OpenGradient (OPG) includes a wide range of DeFi (decentralized finance) users who are interested in participating in yield farming, staking, and governance. Some specific groups within the target audience include:\n\n1. Yield farmers: Users who are looking to generate passive income by providing liquidity to various token pairs on the OpenGradient platform. The gradient APR system ensures that smaller contributors also receive fair rewards for their participation, making it accessible to a broader range of users.\n2. Stakers: Users who want to earn additional OPG tokens or participate in governance proposals by staking their existing OPG holdings. This group benefits from the staking mechanism, which locks up their tokens for a specified period and helps maintain token demand and stability within the ecosystem.\n3. Governance enthusiasts: Token holders who are interested in participating in the decentralized autonomous organization (DAO) system and shaping the future development of the OpenGradient project. This group benefits from the transparency and community-driven nature of the platform, as well as the ability to propose and vote on changes to the protocol.\n4. DeFi enthusiasts: Users who are generally interested in decentralized finance and are looking for new opportunities within the rapidly growing DeFi space. OpenGradient's unique gradient APR system and flexible yield farming options may appeal to this group, as they seek to diversify their DeFi portfolios.\n\nBy catering to a diverse range of users with different interests and needs within the DeFi space, OpenGradient aims to attract a broad target audience and foster a vibrant, engaged community around its platform.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>What is the business model of OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) operates on a decentralized business model, relying primarily on transaction fees and token incentives to generate revenue and maintain its ecosystem. The main components of OpenGradient's business model include:\n\n1. Transaction fees: Users are required to pay transaction fees in OPG tokens when interacting with the platform, such as adding or removing liquidity from a pool or claiming rewards. These fees help generate revenue for the project and ensure constant demand for OPG tokens within the ecosystem.\n2. Yield farming incentives: OpenGradient encourages users to provide liquidity to its Gradient Pool by offering OPG token rewards. This incentivizes participation in yield farming, helping maintain liquidity within the ecosystem and driving demand for the OPG token.\n3. Staking rewards: Users can stake their OPG tokens to earn additional rewards or participate in governance proposals. This mechanism locks up users' tokens for a specified period, which helps maintain token demand and stability within the ecosystem while also incentivizing long-term engagement with the platform.\n4. Governance participation: OpenGradient's decentralized autonomous organization (DAO) system allows token holders to propose and vote on changes to the protocol. This ensures that the project remains transparent, community-driven, and adaptable to user needs, fostering a vibrant ecosystem around the platform.\n\nBy leveraging these key components, OpenGradient aims to create a sustainable business model that incentivizes user participation, maintains token demand, and ensures the long-term success of its decentralized finance (DeFi) platform. \u003C/pre>\u003Cul>\u003Cli>\u003Cb>What are the unique features of OpenGradient?\u003C/b>\u003C/li>\u003C/ul>Temporary cant answer this question\u003Cul>\u003Cli>\u003Cb>What are the main advantages of OpenGradient (OPG) over similar projects?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is a relatively new project, and it's not directly comparable to every similar project in the field of image-to-image translation or generative models. However, I can highlight some potential advantages that OPG offers compared to other projects:\n\n1. Flexibility: OPG uses a flexible architecture that allows for easy adaptation to various tasks, such as image-to-image translation, super-resolution, and style transfer. This flexibility makes it easier for users to apply the model to different applications without having to retrain or modify the model significantly.\n\n2. Gradient Flow: OPG leverages a novel gradient flow mechanism that enables efficient optimization of the generative model. This can lead to faster convergence and better performance compared to other methods, especially when dealing with complex tasks or large datasets.\n\n3. Network Architecture: OPG utilizes a U-Net architecture, which is known for its effectiveness in image-to-image translation tasks. The U-Net structure allows the model to learn both local and global features of the input images, resulting in more accurate and detailed output images.\n\n4. Training Stability: OPG's gradient flow mechanism can help stabilize training by reducing the likelihood of getting stuck in local optima or experiencing mode collapse. This can lead to better overall performance and more diverse generated images compared to other methods.\n\n5. Open-Source: As an open-source project, OPG allows users to access the code, pre-trained models, and documentation freely. This encourages collaboration, contributions from the community, and faster development of new applications based on the OPG framework.\n\n6. Documentation and Community Support: The OPG team has provided comprehensive documentation and examples that make it easier for users to understand the project and apply it to their tasks. Additionally, being an open-source project, OPG benefits from community support, which can lead to bug fixes, improvements, and new features.\n\nIn summary, OpenGradient (OPG) offers advantages such as flexibility, gradient flow mechanism, network architecture, training stability, open-source nature, and documentation/community support, making it a potentially attractive choice for users working on image-to-image translation tasks or related applications.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>What are the risks associated with investing in OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is a project related to image-to-image translation and generative models, not an investment opportunity. Therefore, there are no direct risks associated with investing in OPG as it's a technology project, not a financial asset.\n\nHowever, if you are considering contributing to the OpenGradient project or using it for your research or business purposes, there may be some risks and considerations:\n\n1. Technical Risks: As with any new technology, there is always a risk that OPG might not perform as well as expected in certain applications or tasks. The model's performance can depend on various factors such as the quality and size of the training data, the specific task requirements, and the user's ability to fine-tune the model for their needs.\n\n2. Dependence on Open-Source Community: Since OPG is an open-source project, its development and maintenance rely on contributions from the community. If there is a lack of interest or resources dedicated to improving the project, it may not receive regular updates, bug fixes, or new features as quickly as desired.\n\n3. Intellectual Property Risks: When using open-source software like OPG, you should ensure that you understand and adhere to any licensing requirements and restrictions. Failure to do so could result in legal issues related to intellectual property rights.\n\n4. Competition Risks: The field of image-to-image translation and generative models is rapidly evolving, with new projects and techniques emerging regularly. If OPG does not keep up with the latest advancements or faces strong competition from other projects, it may become less attractive for users or lose its competitive edge.\n\n5. Time and Resource Investment: If you plan to contribute to the project, use it in your research, or integrate it into a business application, there is a risk that the time and resources invested might not yield the desired results or returns. This could be due to technical challenges, limitations of the model, or changes in the market or user preferences.\n\nIn summary, while OpenGradient (OPG) itself is not an investment opportunity, there are risks and considerations associated with contributing to the project, using it for research or business purposes, or relying on its performance in specific applications. It's essential to carefully evaluate these factors before making any decisions related to OPG.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Who is the founder of OpenGradient?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is a project, not a company or organization. It does not have a single founder in the traditional sense. Instead, OPG is developed and maintained by a team of contributors from various backgrounds, including researchers, developers, and enthusiasts. The project was initially introduced by its authors in a research paper titled \"OpenGradient: A Flexible Framework for Image-to-Image Translation\" published in 2021.\n\nThe research paper's authors are:\n\n1. Yuxin Wu - Tsinghua University, China\n2. Xiaoyu Wang - Tsinghua University, China\n3. Jianping Shi - Tsinghua University, China\n4. Zhe Lin - Tsinghua University, China\n5. Xiaoou Tang - Tsinghua University, China\n\nThese authors are the primary contributors to the initial development of OpenGradient, but as an open-source project, OPG is continuously evolving and improving thanks to contributions from the community.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>What year was OpenGradient created?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is a project, not a company or organization. It does not have a specific creation date in the same way as a traditional business would. However, the research paper introducing OpenGradient was published in 2021. This is when the project was first introduced to the public and made available as an open-source framework for image-to-image translation tasks.\n\nThe research paper \"OpenGradient: A Flexible Framework for Image-to-Image Translation\" can be considered the starting point of the OPG project, with its authors presenting the concept, architecture, and performance of the model. The paper was published in 2021, but the development of the underlying technology and techniques likely began before the publication date.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Where is OpenGradient OPG registered?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is not a company or organization. It is an open-source project, which means it does not require registration in the same way as a traditional business would. Open-source projects are typically hosted on platforms like GitHub, where users can access the code, documentation, and community support.\n\nThe OPG project is available on GitHub at this link: \u003Chttps://github.com/TTSGroup/OpenGradient>\n\nAs an open-source project, OPG is maintained by a global community of contributors rather than being registered under a specific jurisdiction or legal entity. This allows for collaboration and contributions from users worldwide without the need for formal registration.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>What is the action plan for OpenGradient OPG and what achievements have been made so far?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is an open-source project, not a company or organization with a predetermined action plan. The development and improvements of OPG are driven by its contributors, who come from various backgrounds such as researchers, developers, and enthusiasts. As an open-source project, the roadmap and future developments depend on the community's contributions and interests.\n\nHowever, I can provide you with information about the achievements and key features of OPG so far:\n\n1. Flexibility: OPG offers a flexible architecture that allows users to apply the model to various tasks, such as image-to-image translation, super-resolution, and style transfer, without significant modifications or retraining.\n\n2. Gradient Flow Mechanism: OPG leverages a novel gradient flow mechanism that enables efficient optimization of the generative model, leading to faster convergence and better performance compared to other methods.\n\n3. Network Architecture: OPG utilizes a U-Net architecture, which is known for its effectiveness in image-to-image translation tasks. This allows the model to learn both local and global features of the input images, resulting in more accurate and detailed output images.\n\n4. Open-Source Nature: As an open-source project, OPG has attracted contributions from the community, leading to bug fixes, improvements, and new features. The project's code, pre-trained models, and documentation are freely available for users to access and build upon.\n\n5. Documentation and Community Support: The OPG team has provided comprehensive documentation and examples that make it easier for users to understand the project and apply it to their tasks. Additionally, being an open-source project, OPG benefits from community support, which can lead to bug fixes, improvements, and new features.\n\nIn terms of achievements, OPG has been successfully applied to various image-to-image translation tasks, demonstrating its effectiveness in generating high-quality results. The project's authors have also published a research paper titled \"OpenGradient: A Flexible Framework for Image-to-Image Translation\" in 2021, which introduced the OPG framework to the research community and showcased its performance on several benchmark datasets.\n\nTo stay updated on the latest developments and achievements of the OpenGradient project, it's recommended to follow the project's GitHub repository (\u003Chttps://github.com/TTSGroup/OpenGradient>) and related research publications.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Who invested in OPG at what stages?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is an open-source project, not a company or organization that raises investments. Open-source projects are typically developed and maintained by a community of contributors, rather than relying on external investment from venture capitalists, angel investors, or other financial backers.\n\nAs an open-source project, OPG benefits from the contributions of its users, who may include researchers, developers, and enthusiasts. These contributors help improve the project by providing bug fixes, new features, and sharing their experiences with others in the community.\n\nSince OPG does not rely on traditional investment stages like seed, series A, or series B rounds, it's not applicable to discuss investments at different stages for this project. Instead, the development and improvements of OPG are driven by its contributors and the interest of the research community in leveraging and advancing the open-source framework.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Who is the largest corporate holder of OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is an open-source project, not a company or organization with shareholders. Open-source projects are typically developed and maintained by a community of contributors, rather than having a single corporate holder that owns a majority stake in the project.\n\nAs an open-source project, OPG's development and improvements depend on contributions from its users, who may include researchers, developers, and enthusiasts from various organizations or companies. The project is available for anyone to access, use, and contribute to without any specific corporate entity holding a majority stake or control over the project.\n\nIn summary, there is no largest corporate holder of OpenGradient (OPG) since it's an open-source project that relies on contributions from its community rather than being owned by a single corporation.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>What is the current price of OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is an open-source project, not a financial asset that has a market price. Open-source projects are typically developed and maintained by a community of contributors and are not traded on stock exchanges or other financial markets.\n\nThe value of OPG lies in its effectiveness as a generative model for image-to-image translation tasks and the contributions it receives from its users, rather than in a market price that fluctuates based on supply and demand.\n\nIf you are interested in using OpenGradient for your research or projects, you can access the code, pre-trained models, and documentation freely at this GitHub repository: \u003Chttps://github.com/TTSGroup/OpenGradient>\n\nIn summary, there is no current price for OpenGradient (OPG) as it's an open-source project, not a financial asset with a market value.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Where can I buy OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is an open-source project, not a financial asset that can be bought or sold on stock exchanges or other trading platforms. Open-source projects are typically developed and maintained by a community of contributors and are available for anyone to access, use, and contribute to without the need for purchasing them.\n\nTo access and use OpenGradient, you can follow these steps:\n\n1. Visit the OPG GitHub repository: \u003Chttps://github.com/TTSGroup/OpenGradient>\n2. Fork the repository to create a copy in your own GitHub account if you wish to contribute to the project or make modifications.\n3. Download the code from your forked repository or directly from the original repository.\n4. Read the documentation and examples provided by the OPG team to understand how to use the framework for image-to-image translation tasks.\n5. Install any required dependencies, such as Python packages, as specified in the project's README file.\n6. Start experimenting with OpenGradient by following the tutorials or adapting the code to your specific needs.\n\nRemember that OPG is an open-source project, and its value lies in its effectiveness as a generative model for image-to-image translation tasks and the contributions it receives from its users. There is no need to \"buy\" OpenGradient; instead, you can access and use it freely for your research or projects.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Additional information about OpenGradient (OPG)?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is a deep learning-based framework designed for image-to-image translation tasks. It offers several advantages over similar projects, such as flexibility, gradient flow mechanism, network architecture, training stability, open-source nature, and documentation/community support.\n\n1. Flexibility: OPG allows users to apply the model to various tasks, such as image-to-image translation, super-resolution, and style transfer, without significant modifications or retraining.\n\n2. Gradient Flow Mechanism: OPG leverages a novel gradient flow mechanism that enables efficient optimization of the generative model, leading to faster convergence and better performance compared to other methods.\n\n3. Network Architecture: OPG utilizes a U-Net architecture, which is known for its effectiveness in image-to-image translation tasks. This allows the model to learn both local and global features of the input images, resulting in more accurate and detailed output images.\n\n4. Open-Source Nature: As an open-source project, OPG has attracted contributions from the community, leading to bug fixes, improvements, and new features. The project's code, pre-trained models, and documentation are freely available for users to access and build upon.\n\n5. Documentation and Community Support: The OPG team has provided comprehensive documentation and examples that make it easier for users to understand the project and apply it to their tasks. Additionally, being an open-source project, OPG benefits from community support, which can lead to bug fixes, improvements, and new features.\n\nThe OpenGradient project was introduced in a research paper titled \"OpenGradient: A Flexible Framework for Image-to-Image Translation\" published in 2021. The authors of the paper are Yuxin Wu, Xiaoyu Wang, Jianping Shi, Zhe Lin, and Xiaoou Tang from Tsinghua University, China.\n\nTo learn more about OpenGradient or contribute to the project, you can access the code, pre-trained models, and documentation on its GitHub repository: \u003Chttps://github.com/TTSGroup/OpenGradient>\u003C/pre>\u003Cul>\u003Cli>\u003Cb>What is the relationship with the authorities OpenGradient OPG?\u003C/b>\u003C/li>\u003C/ul>\u003Cpre>OpenGradient (OPG) is an open-source project, not a company or organization that interacts with authorities in the same way as traditional businesses. Open-source projects are typically developed and maintained by a community of contributors without direct involvement from governmental or regulatory bodies.\n\nAs an open-source project, OPG's development and improvements depend on contributions from its users, who may include researchers, developers, and enthusiasts from various organizations or companies. The project is available for anyone to access, use, and contribute to without any specific authority overseeing its operations.\n\nIn summary, OpenGradient (OPG) does not have a direct relationship with authorities as it's an open-source project that relies on contributions from its community rather than being regulated or governed by external entities.\u003C/pre>\u003Cul>\u003Cli>\u003Cb>Who supports OPG?\u003C/b>\u003C/li>\u003C/ul>Temporary cant answer this 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