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.
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[ 3.1 ms ] story [ 8.0 ms ] thread- 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.