As AI technology continues to evolve, selecting the right foundational layer becomes crucial in determining the effectiveness and flexibility of the AI systems we develop. In the realm of AI development, options such as Model-Driven (MD) approaches, Agentic Retrieval-Augmented Generation (AGENTIC RAG), and entirely new frameworks present unique advantages and challenges.
Given this landscape, we're eager to hear your thoughts:
What do you consider the most important factors when selecting a base layer for AI?
Have you had any experiences or insights from using MD, AGENTIC RAG, or other frameworks in your AI projects?
Do you foresee any emerging technologies or paradigms that could redefine the "base layer" in the future?
How do you balance innovation and practicality when deciding on a foundational layer?
Join the conversation and share your experiences, insights, and questions with fellow community members!