Hello JSLovers,
Join us for an interactive session exploring the evolving landscape of machine intelligence. We’ll compare Generative AI with Predictive Machine Learning, highlighting where each excels—and where they fall short.
Generative AI is powerful in its ability to generalize, but it often struggles to incorporate new or domain-specific knowledge. Together, we’ll unpack these limitations and explore practical techniques to make models smarter and more useful in real-world scenarios:
- Prompt Engineering
- Context-Aware Generation (CAG)
- Retrieval-Augmented Generation (RAG)
- Model Context Protocol (MCP)
This won’t just be theory—we’ll get hands-on with methods that transform generic models into intelligent assistants tailored to specific domains.
We’ll also set the stage for our next meetup on Agents and Agentic AI, where we’ll move beyond response generation to building systems that can plan, act, and collaborate autonomously.
Thanks,
Keyur