Episode description

00:00 Introduction

01:11 Yaniv’s background and intro to Searchium & GSI

04:12 Ways to consume the APU acceleration for vector search

05:39 Power consumption dimension in vector search

7:40 Place of the platform in terms of applications, use cases and developer experience

12:06 Advantages of APU Vector Search Plugins for Elasticsearch and OpenSearch compared to their own implementations

17:54 Everyone needs to save: the economic profile of the APU solution

20:51 Features and ANN algorithms in the solution

24:23 Consumers most interested in dedicated hardware for vector search vs SaaS

27:08 Vector Database or a relevance oriented application?

33:51 Where to go with vector search?

42:38 How Vector Search fits into Search

48:58 Role of the human in the AI loop

58:05 The missing bit in the AI/ML/Search space

1:06:37 Magical WHY question

1:09:54 Announcements

- Searchium vector search: https://searchium.ai/

- Dr. Avidan Akerib, founder behind the APU technology: https://www.linkedin.com/in/avidan-akerib-phd-bbb35b12/

- OpenSearch benchmark for performance tuning: https://betterprogramming.pub/tired-of-troubleshooting-idle-search-resources-use-opensearch-benchmark-for-performance-tuning-d4277c9f724

- APU KNN plugin for OpenSearch: https://towardsdatascience.com/bolster-opensearch-performance-with-5-simple-steps-ca7d21234f6b

- Multilingual and Multimodal Search with Hardware Acceleration: https://blog.muves.io/multilingual-and-multimodal-vector-search-with-hardware-acceleration-2091a825de78

- Muves talk at Berlin Buzzwords, where we have utilized GSI APU: https://blog.muves.io/muves-at-berlin-buzzwords-2022-3150eef01c4

- Not All Vector Databases are made equal: https://towardsdatascience.com/milvus-pinecone-vespa-weaviate-vald-gsi-what-unites-these-buzz-words-and-what-makes-each-9c65a3bd0696

Episode on YouTube: https://youtu.be/EerdWRPuqd4

Podcast design: Saurabh Rai: https://twitter.com/srvbhr