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Context-Aware AI Conversational Agents with RAG Architecture (SD-ETTI, AIDA 2024)


  • Project type Online course, Live coding session
  • Organizer AI Doctoral Academy (AIDA)
  • Host Institutions Doctoral School of Electronics, Telecommunications & Information Technology (National University of Science and Technology POLITEHNICA Bucharest) & AI Multimedia Lab
  • Period 13-14 May 2024
  • Duration 4 hours
  • Level Postgraduate
  • My Role Lecturer
  • Topics RAG, GenAI, LLM, Knowledge Representation, Neural Networks, Vector Databases
  • Keywords AI, Knowledge, Similarity, Semantic, Natural Language Processing, Reasoning, Python, Java, LLM
  • Skills developed Public speaking, Tech presentation
  • Curricula URL
  • Register Registration Form


LLMs have a limited capacity for context. Just as humans cannot digest unlimited context, these models have a specific size limit for the context they can process.

Building AI agents capable of lifelong learning represents an ultimate complexity task, closely tied to the breadth of context they can process.

This course aims to explore cutting-edge techniques for constructing a full-stack, context-aware system from the ground up. It’s designed to be scalable, suitable for small applications as well as state and enterprise levels.

We’ll discuss challenges related to scalability and the implications for data protection and privacy across various contexts, including personal data, financial nuances or military-grade sensitivity.

Key concepts covered include:

  • Conversational Agents Architecture
  • Retrieval-Augmented Generation (RAG) Architecture
  • Streamlining unstructured data
  • Large Language Models
  • Knowledge Representation Techniques
  • Data Embedding
  • Retrieval
  • Semantic Search
  • Reasoning





This event is part of Artificial Intelligence Doctoral Academy - a consortium of 59 universities and 19 research centers and industry members from across Europe.


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