Notas del episodio
Topics:
00:00 Introduction
01:21 Jo Kristian’s background in Search / Recommendations since 2001 in Fast Search & Transfer (FAST)
03:16 Nice words about Trondheim
04:37 Role of NTNU in supplying search talent and having roots in FAST
05:33 History of Vespa from keyword search
09:00 Architecture of Vespa and programming language choice: C++ (content layer), Java (HTTP requests and search plugins) and Python (pyvespa)
13:45 How Python API enables evaluation of the latest ML models with Vespa and ONNX support
17:04 Tensor data structure in Vespa and its use cases
22:23 Multi-stage ranking pipeline use cases with Vespa
24:37 Optimizing your ranker for top 1. Bonus: cool search course mentioned!
30:18 Fascination of Query Understanding, ways to implement and its role in search UX