The MAD Podcast with Matt Turck
What You MUST Know About AI Engineering in 2025 | Chip Huyen, Author of “AI Engineering”
Jan 16, 2025
Chip Huyen, an esteemed AI engineer and author, shares his insights on AI engineering. He distinguishes AI engineering from traditional machine learning, explaining how foundational models democratize app development. Huyen dives into the crucial role of prompt engineering and the complexities of AI model evaluation. With a closer look at the generative AI stack, he dispels myths around Retrieval-Augmented Generation (RAG) and discusses the evolving nature of AI agents. This conversation is a treasure trove for anyone interested in the future of AI technology.
01:12:35
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Quick takeaways
- AI engineering is transformed by foundational models, enabling broader access to AI application development compared to traditional machine learning approaches.
- Evaluating AI systems accurately is critical yet challenging, requiring sophisticated metrics to detect silent failures amid increasing complexity.
Deep dives
The New Landscape of AI Engineering
AI engineering represents a significant evolution in the way applications are developed, leveraging pre-existing foundation models rather than relying solely on the creation of new models. Chip Houyan highlights that the availability of powerful, large language models has democratized the ability to build AI applications, making it accessible for many organizations. Historically, the field required extensive resources to develop models from scratch, which limited participation to a few organizations. In contrast, today, even those without deep expertise in machine learning can utilize these models to create applications, leading to a surge of new ideas and innovations in the space.
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