Vector Podcast

Dmitry Kan
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  • SCIENCE
  • MONTHLY
Vector Podcast Podcast

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.

  1. Berlin Buzzwords 2024 - Sonam Pankaj - EmbedAnything

    1 DAY AGO

    Berlin Buzzwords 2024 - Sonam Pankaj - EmbedAnything

    Video: https://youtu.be/dVIPBxHJ1kQ 00:00 Intro 00:15 Greets for Sonam 01:02 Importance of metric learning 3:37 Sonam's background: Rasa, Qdrant 4:31 What's EmbedAnything 5:52 What a user gets 8:48 Do I need to know Rust? 10:18 Call-out to the community 10:35 Multimodality 12:32 How to evaluate quality of LLM-based systems 16:38 QA for multimodal use cases 18:17 Place for a human in the LLM craze 19:00 Use cases for EmbedAnything 20:54 Closing theme (a longer one - enjoy!) Show notes: - GitHub: https://github.com/StarlightSearch/EmbedAnything - HuggingFace Candle: https://github.com/huggingface/candle - Sonam's talk on Berlin Buzzwords 2024: https://www.youtube.com/watch?v=YfR3kuSo-XQ - Removing GIL from Python: https://peps.python.org/pep-0703 - Blind pairs in CLIP: https://arxiv.org/abs/2401.06209 - Dark matter of intelligence: https://ai.meta.com/blog/self-supervised-learning-the-dark-matter-of-intelligence/ - Rasa chatbots: https://github.com/RasaHQ/rasa - Prometheus: https://github.com/prometheus-eval/prometheus-eval - Dino: https://github.com/facebookresearch/dino

    23 min
  2. Berlin Buzzwords 2024 - Doug Turnbull - Learning in Public

    18 JUL

    Berlin Buzzwords 2024 - Doug Turnbull - Learning in Public

    00:00 Intro 00:30 Greets for Doug 01:46 Apache Solr and stuff 03:08 Hello LTR project 04:42 Secret sauce of Doug's continuous blogging 08:50 SearchArray 13:22 Running complex ML experiments 17:29 Efficient search orgs 22:58 Writing a book on search and AI Show notes: - Doug's talk on Learning To Rank at Reddit delivered at the Berlin Buzzwords 2024 conference: https://www.youtube.com/watch?v=gUtF1gyHsSM - Hello LTR: https://github.com/o19s/hello-ltr - Lexical search for pandas with SearchArray: https://github.com/softwaredoug/searcharray - https://softwaredoug.com/ - What AI Engineers Should Know about Search: https://softwaredoug.com/blog/2024/06/25/what-ai-engineers-need-to-know-search - AI Powered Search: https://www.manning.com/books/ai-powered-search - Quepid: https://github.com/o19s/quepid - Branching out in your ML / search experiments: https://dvc.org/doc/use-cases - Doug on Twitter: https://x.com/softwaredoug - Doug on LinkedIn: https://www.linkedin.com/in/softwaredoug/

    27 min
  3. Eric Pugh - Measuring Search Quality with Quepid

    26 JUN

    Eric Pugh - Measuring Search Quality with Quepid

    00:00 Intro 00:21 Guest Introduction: Eric Pugh 03:00 Eric's story in search and the evolution of search technology 7:27 Quepid: Improving Search Relevancy 10:08 When to use Quepid 14:53 Flash back to Apache Solr 1.4 and the book (of which Eric is one author) 17:49 Quepid Demo and Future Enhancements 23:57 Real-Time Query Doc Pairs with WebSockets 24:16 Integrating Quepid with Search Engines 25:57 Introducing LLM-Based Judgments 28:05 Scaling Up Judgments with AI 28:48 Data Science Notebooks in Quepid 33:23 Custom Scoring in Quepid 39:23 API and Developer Tools 42:17 The Future of Search and Personal Reflections Show notes: - Hosted Quepid: https://app.quepid.com/ - Ragas: Evaluation framework for your Retrieval Augmented Generation (RAG) pipelines https://github.com/explodinggradients... - Why Quepid: https://quepid.com/why-quepid/ - Quepid on Github: https://github.com/o19s/quepid

    48 min
  4. Sid Probstein, part II - Bring AI to company data with SWIRL

    15 MAY

    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

    38 min
  5. Louis Brandy - SQL meets Vector Search at Rockset

    1 MAY

    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

    53 min
  6. Saurabh Rai - Growing Resume Matcher

    12 APR

    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

    26 min
  7. Sid Probstein - Creator of SWIRL - Search in siloed data with LLMs

    22/07/2023

    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/

    1h 32m
  8. Atita Arora - Search Relevance Consultant - Revolutionizing E-commerce with Vector Search

    17/05/2023

    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

    1h 32m
See All (26)

About

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.

Information

  • Creator
    Dmitry Kan
  • Years Active
    2021 - 2024
  • Episodes
    26
  • Rating
    Clean
  • Copyright
    © Vector Podcast 2021
  • Show Website
    Vector Podcast

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