The Billion-Token Tender: Why RAG Isn't Fading, It's Gearing Up
10 hours ago
- #AI
- #Context Engineering
- #RAG
- Retrieval-Augmented Generation (RAG) remains essential despite advancements in language models with large context windows.
- Performance issues like 'context rot' and 'lost in the middle' degrade model accuracy with massive undifferentiated text blocks.
- Real-world industrial applications, such as construction tenders, involve data scales (e.g., 1.2 billion tokens) far beyond current model capacities.
- Cost analysis shows prohibitive expenses (e.g., $26,000 per query) for processing billion-token contexts with existing models.
- RAG and Context Engineering improve accuracy, control costs, and ensure speed by delivering only relevant data to models.