Analysis
This article highlights a crucial aspect often overlooked in the excitement of Generative AI: inference cost. The author emphasizes that cost is an architectural design problem, not merely an accounting issue, offering practical strategies to optimize costs and ensure the long-term viability of Generative AI projects.
Key Takeaways
- •Inference costs can be broken down into a simple formula considering requests, tokens, and unit prices.
- •Optimizing for cost scalability involves strategies such as caching, model splitting, and asynchronous processing.
- •Prompt engineering and minimizing context length are crucial for reducing token usage and costs.
Reference / Citation
View Original"Cost is not a problem for accounting, but for architecture design."