Chat with RTX
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Chat with RTX is a demo application from NVIDIA that enables users to develop a customized AI chatbot by linking it to their own data sources, like documents, notes, or video transcripts. The application employs retrieval-augmented generation (RAG), TensorRT-LLM, and RTX acceleration to deliver swift and contextually accurate responses from the tailored chatbot, operating locally on Windows RTX PCs or workstations for efficient and secure outcomes. This tool can be used to boost productivity, simplify information retrieval, or incorporate a tailored conversational AI into their workflows without relying on cloud processing.
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Cody is an AI-driven virtual assistant designed to aid businesses with a variety of tasks including answering inquiries, executing tasks, onboarding new employees, offering support, resolving issues, and generating innovative ideas and insights. It sifts through all of a company's collected data, such as articles, PowerPoint presentations, and PDFs, to deliver answers to questions in seconds. Additionally, it can be customized for specific business processes, enabling teams to troubleshoot efficiently, brainstorm effectively, and complete tasks more swiftly.
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Helix is a platform for AI chatbots that enables users to design personalized AI assistants trained using their own documentation. It is tailored for businesses to enhance their customer service efficiency and for individuals seeking quick and effective support. Users can also explore featured bots from Helix, including those associated with Ethereum, Uniswap, LangChain, Klaytn, and OKX Chain.
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Zep serves as a memory layer for AI assistants and agents, facilitating ongoing learning from user interactions. It gathers and manages conversational facts, classifies dialogue intentions, and arranges chat histories. By utilizing Zep, developers and businesses can enhance AI applications, leading to improved personalization, accuracy, and efficiency. This tool minimizes hallucinations, enhances recall, and provides scalable, secure data management, making it essential for developing more intelligent and context-aware AI experiences.