Context-Aware RAG Chatbots (Ciklum GenAI Upskill Program, 2024)
Info
- Project type Public Speaking, Tech Presentation
- Date 19th of March 2024
- My Role Speaker, Mentor, Community Lead
- Registered 130 developers (from Ciklum)
- Topics RAG, RAT, GenAI, Data Protection, Machine Forgetting
- Keywords RAG, Architecture, Embeddings. Data Chunking. Semantic Search, Retrieval, Multilinguality, RAT, Context Understanding, Machine Forgetting
- Skills developed Presentation, Speaking
- Presentation slides PDF
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Video recording (password protected)
Description
The Ciklum GenAI Upskill Program, which I am spearheading alongside my colleague Denys Osipenko, our Data Science Lead from Ukraine, represents one of my major internal initiatives and the first corporate program I've developed on a large scale. This certification program is designed to guide our developers through specialized learning paths and mentoring sessions.
My mentoring session focused on RAG, Context Understanding, and Enterprise Chatbots, exploring the architecture and the unique challenges encountered at this scale.
Session Description and Agenda.
Why is Context more important than ever?
The ability to create conversational agents that excel in large business environments is becoming crucial for smarter, more effective digital assistance.
AI chatbots, with their wide spectrum of use cases, are transforming user experiences (UX) and privacy approaches.
They serve not only as customer support and personal assistants but also as alternatives to traditional graphical user interfaces.
As businesses increasingly rely on these technologies, understanding how to build and implement sophisticated chatbot systems, particularly in enterprise settings, is more relevant than ever.
We will talk about
We will explore the meaning of RAG, its essential role in AI agents, and its broad potential. RAG's versatility extends to various applications, including Agents, Copilots, Chatbots, and multimodal apps. This session will specifically focus on chatbots – examining the emerging opportunities, their development, the challenges encountered, current capabilities, and technical limitations. We'll provide an in-depth analysis of RAG's transformative impact in the AI field, especially in advancing chatbot functionalities.
Agenda
- RAG Architecture & Plugins.
- Embeddings. Data Chunking. Semantic Search.
- Retrieval.
- Unstructured Data.
- Multilinguality.
- RAT & Context Understanding.
- Enterprise Data Protection and Privacy.
- Machine Forgetting.
- Best Practices
This workshop is focused on providing developers with the essential knowledge and tools required to develop advanced, privacy-aware, and efficient AI chatbots, that can manage complex conversations and discern context, shaping the future of digital interactions in business contexts.
References
