a review of Chip Huyen's bookFellow
Review of AI Engineering
Alexander Polomodov and Evgeny Sergeev review AI Engineering chapter by chapter, from foundation models to evaluating AI applications.
About the series
The series connects the book's ideas with practical questions in building generative-AI products: model choice, quality, cost, and validation.
Three episodes cover the introduction and the first four chapters.
Hosts
catalog
All episodes
S1E11:25:12
Preface and Introduction
The first episode maps Chip Huyen's AI Engineering and examines the transition from traditional ML to applications built on foundation models.
Foundation modelsTokensMultimodalityMCP and platforms
S1E21:55:37
Understanding Foundation Models
The second episode explores foundation models: their data, domain knowledge, multimodality, and the evolution from RNNs to transformers.
TransformersModel trainingSFT and RLHFHallucinations
S1E31:54:48
Evaluation Methodology and Evaluating AI Systems
The third episode combines the chapters on evaluation methodology and the practical evaluation of AI systems.
EvaluationModel metricsAI as a judgeValidation