Episode notes
00:00 Introduction
01:10 Max's deep experience in search and how he transitioned from structured data
08:28 Query-term dependence problem and Max's perception of the Vector Search field
12:46 Is vector search a solution looking for a problem?
20:16 How to move embeddings computation from GPU to CPU and retain GPU latency?
27:51 Plug-in neural model into Java? Example with a Hugging Face model
33:02 Web-server Mighty and its philosophy
35:33 How Mighty compares to in-DB embedding layer, like Weavite or Vespa
39:40 The importance of fault-tolerance in search backends
43:31 Unit economics of Mighty
50:18 Mighty distribution and supported operating systems
54:57 The secret sauce behind Mighty's insane fast-ness
59:48 What a customer is paying for when buying Mighty
1:01:45 ...
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