Max Irwin - Founder, MAX.IO - On economics of scale in embedding computation with Mighty

Vector Podcast by Dmitry Kan

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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