Yongsheng Wu, VP Engineering at Granica.ai

Building Reliable Data Pipelines for Effective AI: Insights from Yongsheng Wu

In this episode, we dive into the vital importance of structuring reliable data pipelines before tackling AI and machine learning projects. Featuring Yongsheng Wu, VP of Engineering at Granica.Ai, the discussion covers Wu's extensive experience in the field, including his roles at Pinterest, Twitter, and Salesforce.

We explore essential steps for training an AI software engineer, emphasizing the significance of clean and well-labeled data, effective model evaluation, and the continuous improvement cycle of AI models. Wu also shares thoughts on the future of software engineering roles and remote work dynamics in engineering teams. Tune in to gain valuable insights on building robust data foundations for AI success.

00:00 Introduction to Data and AI
00:31 Guest Introduction: Yongsheng Wu
01:19 Foundations of AI Training
03:30 Importance of Clean Data
08:34 Data Labeling and Curation
12:12 Challenges in AI Implementation
15:58 Future of Software Engineering
21:53 Building Effective Engineering Teams
25:58 Conclusion and Contact Information