Vector Podcast Dmitry Kan
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- Science
Vector Podcast is here to bring you the depth and breadth of Search Engine Technology, Product, Marketing, Business. In the podcast we talk with engineers, entrepreneurs, thinkers and tinkerers, who put their soul into search.
Depending on your interest, you should find a matching topic for you -- whether it is deep algorithmic aspect of search engines and information retrieval field, or examples of products offering deep tech to its users.
"Vector" -- because it aims to cover an emerging field of vector similarity search, giving you the ability to search content beyond text: audio, video, images and more.
"Vector" also because it is all about vector in your profession, product, marketing and business.
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Sid Probstein, part II - Bring AI to company data with SWIRL
00:00 Intro
01:54 Reflection on the past year in AI
08:08 Reader LLM (and RAG)
12:36 Does it need fine-tuning to a domain?
14:20 How LLMs can lie
17:32 What if data isn't perfect
21:21 SWIRL's secret sauce with Reader LLM
23:55 Feedback loop
26:14 Some surprising client perspective
31:17 How Gen AI can change communication interfaces
34:11 Call-out to the Community -
Louis Brandy - SQL meets Vector Search at Rockset
00:00 Intro
00:42 Louis's background
05:39 From Facebook to Rockset
07:41 Embeddings prior to deep learning / LLM era
12:35 What's Rockset as a product
15:27 Use cases
18:04 RocksDB as part of Rockset
20:33 AI capabilities: ANN index, hybrid search
25:11 Types of hybrid search
28:05 Can one learn the alpha?
30:03 Louis's prediction of the future of vector search
33:55 RAG and other AI capabilities
41:46 Call out to the Vector Search community
46:16 Vector Databases vs Databases
49:16 Question of WHY -
Saurabh Rai - Growing Resume Matcher
Topics:
00:00 Intro - how do you like our new design?
00:52 Greets
01:55 Saurabh's background
03:04 Resume Matcher: 4.5K stars, 800 community members, 1.5K forks
04:11 How did you grow the project?
05:42 Target audience and how to use Resume Matcher
09:00 How did you attract so many contributors?
12:47 Architecture aspects
15:10 Cloud or not
16:12 Challenges in maintaining OS projects
17:56 Developer marketing with Swirl AI Connect
21:13 What you (listener) can help with
22:52 What drives you?
Show notes:
- Resume Matcher: https://github.com/srbhr/Resume-Matcher
website: https://resumematcher.fyi/
- Ultimate CV by Martin John Yate: https://www.amazon.com/Ultimate-CV-Cr...
- fastembed: https://github.com/qdrant/fastembed
- Swirl: https://github.com/swirlai/swirl-search -
Sid Probstein - Creator of SWIRL - Search in siloed data with LLMs
Topics:
00:00 Intro
00:22 Quick demo of SWIRL on the summary transcript of this episode
01:29 Sid’s background
08:50 Enterprise vs Federated search
17:48 How vector search covers for missing folksonomy in enterprise data
26:07 Relevancy from vector search standpoint
31:58 How ChatGPT improves programmer’s productivity
32:57 Demo!
45:23 Google PSE
53:10 Ideal user of SWIRL
57:22 Where SWIRL sits architecturally
1:01:46 How to evolve SWIRL with domain expertise
1:04:59 Reasons to go open source
1:10:54 How SWIRL and Sid interact with ChatGPT
1:23:22 The magical question of WHY
1:27:58 Sid’s announcements to the community
YouTube version: https://www.youtube.com/watch?v=vhQ5LM5pK_Y
Design by Saurabh Rai: https://twitter.com/_srbhr_ Check out his Resume Matcher project: https://www.resumematcher.fyi/ -
Atita Arora - Search Relevance Consultant - Revolutionizing E-commerce with Vector Search
Topics:
00:00 Intro
02:20 Atita’s path into search engineering
09:00 When it’s time to contribute to open source
12:08 Taking management role vs software development
14:36 Knowing what you like (and coming up with a Solr course)
19:16 Read the source code (and cook)
23:32 Open Bistro Innovations Lab and moving to Germany
26:04 Affinity to Search world and working as a Search Relevance Consultant
28:39 Bringing vector search to Chorus and Querqy
34:09 What Atita learnt from Eric Pugh’s approach to improving Quepid
36:53 Making vector search with Solr & Elasticsearch accessible through tooling and documentation
41:09 Demystifying data embedding for clients (and for Java based search engines)
43:10 Shifting away from generic to domain-specific in search+vector saga
46:06 Hybrid search: where it will be useful to combine keyword with semantic search
50:53 Choosing between new vector DBs and “old” keyword engines
58:35 Women of Search
1:14:03 Important (and friendly) People of Open Source
1:22:38 Reinforcement learning applied to our careers
1:26:57 The magical question of WHY
1:29:26 Announcements
See show notes on YouTube: https://www.youtube.com/watch?v=BVM6TUSfn3E -
Connor Shorten - Research Scientist, Weaviate - ChatGPT, LLMs, Form vs Meaning
Topics:
00:00 Intro
01:54 Things Connor learnt in the past year that changed his perception of Vector Search
02:42 Is search becoming conversational?
05:46 Connor asks Dmitry: How Large Language Models will change Search?
08:39 Vector Search Pyramid
09:53 Large models, data, Form vs Meaning and octopus underneath the ocean
13:25 Examples of getting help from ChatGPT and how it compares to web search today
18:32 Classical search engines with URLs for verification vs ChatGPT-style answers
20:15 Hybrid search: keywords + semantic retrieval
23:12 Connor asks Dmitry about his experience with sparse retrieval
28:08 SPLADE vectors
34:10 OOD-DiskANN: handling the out-of-distribution queries, and nuances of sparse vs dense indexing and search
39:54 Ways to debug a query case in dense retrieval (spoiler: it is a challenge!)
44:47 Intricacies of teaching ML models to understand your data and re-vectorization
49:23 Local IDF vs global IDF and how dense search can approach this issue
54:00 Realtime index
59:01 Natural language to SQL
1:04:47 Turning text into a causal DAG
1:10:41 Engineering and Research as two highly intelligent disciplines
1:18:34 Podcast search
1:25:24 Ref2Vec for recommender systems
1:29:48 Announcements
For Show Notes, please check out the YouTube episode below.
This episode on YouTube: https://www.youtube.com/watch?v=2Q-7taLZ374
Podcast design: Saurabh Rai: https://twitter.com/srvbhr