Evolution and Challenges of RAG Systems in Data Processing

I'm excited to share this conversation with Max Rumpf the founder of Sid.AI. I wanted to speak to Max because Retrieval Augmented generation has become core to building AI applications and he knows more about RAG than anyone I know.

We get deep into the challenges of building RAG systems and the episode is full of technical detail and practical insights. 

We cover:
00:00 - Introduction to Max Rumpf and SID.ai
03:39 - How SID.ai's RAG approach differs from basic tutorials
07:30 - Challenges of document processing and chunking strategies
13:07 - Retrieval techniques and hybrid search approaches
15:06 - Discussion on knowledge graphs and their limitations
20:58 - Reranking in RAG systems and performance improvements
32:14 - Impact of longer context windows on RAG systems
35:10 - The future of RAG and information retrieval
39:47 - Recent research papers on AI and hallucination detection
42:04 - Value-augmented sampling for language model alignment
43:11 - Future trends and investment opportunities in AI
43:50 - SEO optimization for LLMs and its potential as a business
45:20 - Closing thoughts and wrap-up

I hope you enjoy the conversation and if you do, please subscribe!