It was great to discuss with Jo Kristian on these topics and more:

- History of Vespa - Tensor data structure and its use cases - Multi-stage ranking pipeline - Game-changing vector search in Vespa - Approximate vs exact nearest neighbor search tradeoffs - Misconceptions in neural search - Multimodal search is where vector search shines - Power of building fully-fledged demos - How to combine vector search with sparse search: Reciprocal Rank Fusion - The question of WHY (my favourite)

I wonder what topics are interesting to HN community -- it would help me focus on these topics / embed into my questions in new episodes.