Weaviate Podcast

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Hey everyone! Thank you so much for watching the 38th episode of the Weaviate podcast! This episode features Leo Boystov, an expert in Information Retrieval technology! We discussed a very wide range of topics from an overview of IR methods such as BM25, Neural Bi-Encoder and Cross-Encoder rankers, and a super exciting new work Leo has co-authored on using Large Language Models to generate trainin...

Hey everyone! Thank you so much for watching the 37th episode of the Weaviate podcast! This episode discusses some of the ideas behind GPT Index. GPT Index presents really exciting ideas about how we use LLMs to index our data and then traverse these data structures. We began the podcast by discussing the origins of the tool and the ideas behind the Tree Index. We then discussed generalizing these...

Hey everyone! Thank you so much for watching the 36th episode of the Weaviate podcast! This episode continues on the marriage between LLMs and Semantic Search, welcoming back Weaviate CEO and Co-Founder Bob van Luijt! Enter LangChain and its creator, Harrison Chase, providing the glue between LLMs and tools, such as semantic search. LangChain provides a set of abstractions around chaining multiple...

This podcast debuts a huge new release from Weaviate... the generate module! The generate module is a new API in Weaviate that facilitates passing YOUR data from the Weaviate database to ChatGPT. This enables ChatGPT to become knowledgeable about your particular business or interests! Here is a great snippet from Bob around the 43 minute mark that describes how this kind of LLM technology is chang...

Chapters 1:00 Introduction 1:26 Why does the world need yet another database? 3:57 Memory Allocations 9:40 Delayed Decoding 16:05 SIMD 22:04 Demo Time! 24:38 Mad at Go? 26:00 Audience Questions

I am so excited to host Dmitry Kan on the Weaviate Podcast!! Dmitry is a world class expert on emerging trends in search technology! This podcast reflects on Dmitry's latest characterization of the field, the Neural Search Pyramid. This describes the different components involved with building a Deep Learning-powered Search experience from the Approximate Nearest Neighbor index algorithms, to Data...

Weaviate podcast #33. Thank you so much for watching the 33rd Weaviate Podcast! This episode features one of the heroes of Deep Learning for Search, Nils Reimers! Nils' work on SentenceBERT is one of the foundational works for applying Deep Representation Learning to text search. This is the idea that personally inspired me to work in this field. Having seen the successes of Contrastive Representa...

Weaviate Podcast #32. Thank you so much for watching the Weaviate podcast! We are super excited to host Sam Bean from You.com! As well as welcome Zain Hasan and John Trengrove to the Weaviate podcast for the first time! Sam begins by describing You.com, and then we dive into the Weaviate Spark Connector that Sam played a massive role in creating. I thought this was such a masterclass in the Spark...

Weaviate Podcast #31.  Weaviate 1.17!! This is a massive release for Weaviate, debuting Replication, Hybrid Search, BM25, Faster Startup and Import Times, as well as other fixes! Replication and Hybrid Search are two massive features for Weaviate, and we really hope you enjoy the description of them from the podcast. Please also check out the Weaviate 1.17 release blog post for more informati...

Weaviate Podcast #30.  Chapters 0:00 The future of search! 0:42 Welcome Marco and Chris! 4:28 Solving Hallucination with External Memory LLMs 8:16 Bob van Luijt on Weaviate and LLMs, Collaborations 14:48 What we have is not yet what the technology is capable of 16:45 Everything is Search! 18:55 The Magic of Machine Learning 20:30 Asking follow up questions 22:28 Meaning in LLMs and RLHF 27:10...

Weaviate Podcast #29. Hey everyone, thank you so much for watching another episode of the Weaviate podcast! This episode features Matthijs Douze, one of the most talented and accomplished scientists we've hosted on the Weaviate podcast! Matthijs has pioneered the use of Product Quantization to compress vector representations and enable even faster and more efficient approximate nearest neighbor ve...

Weaviate Podcast #28. Thank you so much for watching the 28th Weaviate Podcast! This episode features Maarten Grootendorst, developer of the BERTopic python library and an active evangelist of this exciting cluster analysis technology, (Maarten has written some incredible articles here - https://medium.com/@maartengrootendorst) ! In this podcast, Maarten did an incredible job explaining how BERTop...

Weaviate Podcast #27. Thank you so much for watching the 27th episode of the Weaviate Podcast! This is truly one of my favorite podcasts we have published so far, I think the way Weaviate and Neural Magic fit together is really exciting! Michael did an amazing job explaining the concepts behind how Neural Magic delivers and tests inference acceleration, as well as the vision for the future of Deep...

Weaviate Podcast #26. Thank you so much for watching the 26th episode of the Weaviate Podcast! This is another really special episode! Jonathan Frankle is one of the world's experts in Deep Learning and is making incredible advances at MosaicML in efficient Deep Learning training. The headline event is the release of MosaicML Cloud and a set of new cost estimates for GPT language models at differe...

Weaviate Podcast #25. Thank you so much for watching the 25th episode of the Weaviate Podcast! This is a really special episode with Erik Bernhardsson! Erik is one of the early thought leaders on Approximate Nearest Neighbor (ANN) Search, creating the ANNOY library at Spotify. Erik shared incredible insights about vector search at Spotify such as the role of Offline and Online Machine Learning inf...

Weaviate Podcast #24. Weaviate v1.15 Release! Thank you so much for checking out the Weaviate podcast -- here is a summary of what is new in Weaviate 1.15:  1. Cloud-native backups – allows you to configure your environment to create backups – of selected classes or the whole database – straight into AWS S3, GCS or local filesystem 2. Reduced memory usage - we found new ways to optimize memor...

Weaviate Podcast #23. Thank you so much for watching the 23rd episode of the Weaviate Podcast! This episode dives into a new technique for Self-Supervised retrieval in NLP with some incredible results!

Weaviate Podcast #22. Thank you so much for watching the 22nd Weaviate Podcast with Yaoshiang Ho! Yaoshiang is a Co-Founder of Masterful AI, a company doing incredible work in the Computer Vision model training and deployment space ( https://www.masterfulai.com/) . I really hope you enjoy this podcast, Yaoshiang and I went deep into some of the cutting edge Computer Vision algorithms such as Noisy...

Weaviate Podcast #21. Thank you for watching the 21st Weaviate Podcast with Laura Ham! Laura Ham has worked on Weaviate at SeMI Technologies for a little over 5 years. She has had a heavy influence on all things from the GraphQL User Experience design to the Graph data model, and the creation of educational content! I really enjoyed this podcast, please see the list of topics under “chapters”! Her...

Weaviate Podcast #20. Tuana Celik, a Developer Advocate at Deepset, presented many exciting ideas around Question Answering! We began with her Game of Thrones Question Answering Demo on HuggingFace Spaces and continued to discuss all topics QA from Extractive to Abstractive, benefits of Retrieve-then-Read, and Zero-Shot Generalization, to give a quick preview. For our Weaviate users, please check...

Weaviate Podcast #19. SeMI Technologies Co-Founder and CTO Etienne Dilocker returns to the Weaviate podcast to describe what's new with Weaviate v1.14! Please see the chapter outlines if you would like to skip ahead to the update most relevant to you! Please also see this blog post lead by Sebastian Witalec describing the new changes to Weaviate!  Weaviate v1.14 Blog Post: https://weaviate.io...

Weaviate Podcast #18. Thank you for watching the 18th Weaviate Podcast with Vincent D. Warmerdam! Vincent is an engineer at Spacy working on exciting tools such as Prodigy! Vincent describes how nearest neighbor search can aid in tasks such as Data De-Duplication and Data Labeling! Vincent shared many interesting ideas from representations of text, challenges with annotator disagreement, lessons f...

Weaviate Podcast #17. Thank you for watching the 17th Weaviate Podcast with Kyle Lo! Vector Search enables us to find semantically similar items in large collections. Scientific Literature Mining is an extremely interesting case of this where we search through enormous collections of scientific papers to find evidence and ideas. Kyle has an extremely impressive resume in this application domain, t...

Weaviate Podcast #16. ANN Benchmarks are a tool for evaluating the performance of in-memory approximate nearest neighbor algorithms. Etienne Dilocker, the CTO of SeMI Technologies, the company behind Weaviate shares some insight knowledge about this interesting topic.