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Build an AI Scheduler: Smart Meetings with Zoom, LlamaIndex & Qdrant @ AWSnPlease note that attendees require a photo ID to enter the venue. This event will also be streamed for those of you who cannot join us in San Fransisco.nThe Qdrant team, in partnership with AWS, LlamaIndex & Zoom invites you to the AWS AI Engineering Loft where we will show you hands on how to build a state of the art RAG application. Simon Suo, Co-Founder & CTO at LlamaIndex will give the closing talk.nDuring this one-day event, youll learn how to build a Retrieval-Augmented Generation (RAG) recommendation engine specifically designed to enhance meeting productivity.nBy leveraging Qdrant as a Vector Database, LlamaIndex as our LLM Framkework & the Zoom transcription SDK for data, you'll create a system that recommends future meetings to attend based on missed contentensuring you stay connected to topics of interest.nZoom's Developer Platform empowers teams to build collaborative applications by integrating with its highly scalable video & communication infrastructure. It enables the development of immersive, real-time collaboration tools & enhances virtual experiences across sectors.nLlamaIndexis a powerful tool for managing & querying large datasets, offering an intuitive interface for integrating machine learning models. It simplifies the process of building retrieval-augmented generation (RAG) systems, enabling developers to create more sophisticated & responsive agents.nnQdrant is an industry-leading vector database & a semantic search engine, powering large operations such as Twitter, Discord, Firefox, Tripadvisor, Johnson & Johnson, Deloitte, & more.nAgenda:n9:00 AM - Doors Openn9:00-10:00 AM - Networking + Breakfastn10:00-11:00 PM - Workshop: Building on Qdrant with Thierry Damiban10:00-11:00 PM - Qdrant + Cursor Walkthrough with Thierry Damiban12:00-1:00 PM - Lunch Breakn1:00-2:00 PM - Workshop: Zoom Developer Platform with Ojus Saven2:00-3:00 PM - Open Coding Sessionn3:00-4:00 PM - Closing Talk from Simon SuonnLearning Objectives:nUnderstand the fundamentals of RAG & its application in meeting recommendations.nGain practical experience using the transcription SDK to build a custom RAG recommendation engine.nLearn how to fine-tune models to improve the relevance & accuracy of recommendations.nKey Topics:nIntroduction to RAG:Overview of RAG & its benefits in recommendation systems.nTranscription SDK:Step-by-step guide on integrating & utilizing the transcription SDK.nBuilding the Engine:Best practices for developing a recommendation engine that analyzes missed meetings.nModel Fine-Tuning:Techniques for enhancing recommendation accuracy based on user preferences & meeting content.nTarget Audience:nThis workshop is designed for developers, data scientists, & AI practitioners interested in building practical AI applications for improving meeting effectiveness.nHosts:nZoom TeamnLlamaIndex TeamnQdrant Team
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