Chip Huyen

Chip Huyen, a computer scientist and author with experience at Netflix and NVIDIA, joins the conversation to explore AI Engineering. They discuss how AI Engineering differs from Machine Learning Engineering and express caution over fine-tuning tactics. The episode highlights practical steps to build AI applications and emphasizes the value of structured learning paired with project-based methods. Chip also shares insights into deploying AI for customer service and the importance of human oversight in integrating AI into business processes.

In this insightful discussion, Chip Huyen, an independent AI researcher and the author of "AI Engineering," dives into the intricacies of AI engineering versus traditional machine learning. She highlights common pitfalls in AI systems and the critical nature of effective planning. The conversation also touches on AI agents, their limitations, and the significance of rigorous evaluation processes. Additionally, Chip explores the growing trend of open-source models and the exciting potential of synthetic data, along with her predictions for AI advancements by 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.

Chip Huyen, an AI engineering expert and author of 'AI Engineering,' discusses the future of AI application development. He shares insights on using advanced AI models like ChatGPT in innovative ways. Huyen emphasizes the importance of understanding foundational concepts to avoid common pitfalls in AI projects. The conversation dives into the phenomenon of AI hallucinations and the evolving roles of engineers in this space. Finally, he predicts a transformative rise of AI agents by 2025, highlighting their potential to revolutionize workplace efficiency.

Chip Huyen explores the shifting sand of large data models, Herman Õunapuu reviews the Zimaboard, Bryan Braun shares recent VSCode configuration discoveries, and Swizec Teller summarizes the inaugural AI Engineer Summit.