Software Engineering Daily AI Pipelines with Maxime Armstrong and Yuhan Luo
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Sep 24, 2024 
In this discussion, Yuhan Luo and Maxime Armstrong, Software Engineers at Dagster, dive into the evolving landscape of AI pipelines. They address the financial challenges associated with maintaining AI models and the importance of cost-effective strategies. The duo highlights the nuances of AI versus traditional data engineering, emphasizing the crucial role of observability and automation for optimizing QA processes. They also explore the future of AI integration, discussing open-source versus managed solutions and the significance of human oversight in AI development.
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AI Costs
- Training AI models is a significant cost.
- Running and maintaining them, especially LLMs, also contributes to expense.
Observability for Cost Control
- Closely monitor costs in AI pipelines, especially runtime costs beyond training.
- Observability is key for managing these expenses effectively.
Early Stage Complexity
- AI pipeline complexity causes cost issues early in development, not just at scale.
- Even small-scale projects can become costly due to numerous interconnected components.
