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MyScaleGPT is an innovative tool designed to enhance your conversational experience by integrating external knowledge from ArXiv and Wikipedia with the MyScale vector database. This powerful combination allows you to access a wealth of academic papers and informative articles seamlessly. With the capability to retrieve related research papers through the get_related_arxiv feature, you can easily explore topics like Generative Adversarial Networks (GANs) or NeRF, and discover significant publications post-2021. Additionally, the get_related_wiki function provides relevant Wikipedia pages, enriching your understanding of complex subjects, such as mathematical rings and their properties. The user-friendly interface encourages you to engage in insightful discussions, making it an invaluable resource for students, researchers, and anyone seeking knowledge. By leveraging the extensive databases of ArXiv and Wikipedia, MyScaleGPT ensures that you are always informed and equipped with the most pertinent information at your fingertips. Experience a new dimension of learning and inquiry with MyScaleGPT, where academic exploration meets conversational AI. For more information, visit https://chat.openai.com/g/g-193M4NO0q-chat-with-free-knowledge-base.
Quickly retrieve related academic papers from ArXiv using the get_related_arxiv feature, enhancing your research with relevant studies and insights from a vast database.
Utilize the get_related_wiki function to discover pertinent Wikipedia pages, enriching your understanding of topics with reliable information from a well-respected source.
Benefit from the synergy between ArXiv and Wikipedia, allowing you to cross-reference information and deepen your knowledge in various fields with ease.
Find the latest papers on specific topics, like GANs or NeRF, ensuring your research is current and informed by the most recent developments in technology and science.
Engage in natural conversations with MyScaleGPT, where you can ask specific questions and receive tailored responses, making your learning experience both efficient and enjoyable.
Enhance Your Journey with Cutting-Edge Features and Functions
Get some related papers.\nYou should use schema here:\n\nCREATE TABLE ArXiv (\n `id` String,\n `abstract` String, \n `pubdate` DateTime, \n `title` String, \n `categories` Array(String), -- arxiv category\n `authors` Array(String),\n `comment` String,\nORDER BY id
Get some related wiki pages.\nYou should use schema here:\n\nCREATE TABLE Wikipedia (\n `id` String,\n `text` String,\n `title` String,\n `view` Float32,\n `url` String, -- URL to this wiki page\nORDER BY id\n\nYou should avoid using LIKE on long text columns.
You can upload files to this GPT.
Unleash your creativity with our prompt starters, sparking ideas and inspiration right from the start.
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