A detailed comparison of Milvus, Pinecone, Vespa, Weaviate, Vald, GSI and Qdrant — While working on this blog post I had a privilege of interacting with all search engine key developers / leadership: Bob van Luijt and Etienne Dilocker (Weaviate), Greg Kogan (Pinecone), Pat Lasserre, George Williams (GSI Technologies Inc), Filip Haltmayer (Milvus), Jo Kristian Bergum (Vespa), Kiichiro Yukawa (Vald) and Andre Zayarni…

While working on this blog post I had a privilege of interacting with all neural search frameworks key developers / leadership: Malte Piestch (Haystack), Amin Ahmad (Vectara), Florian Hönicke (Jina AI), David Mezzetti (txtai), Daniel Vassilev (Relevance AI), George Sivulka and Swetha Revanur (Hebbia), Aarne Talman and myself (Muves). The…

Change of format: in this episode you will find a demo of SWIRL! Imagine you have an existing search engine and would like to extend it with a new data source. Something that most of us would do is to get this data – by downloading, scraping or some other…

One of the reasons why I host Vector Podcast is the unique opportunity to meet the makers in the Search space and learn from them. My conversation with Atita Arora, Search Relevance Consultant at OpenSource Connections, gave me both the chance to learn new things, and enjoy the drive, energy and dedication to the field of search engine development, that Atita is full of. It is not a typical episode, because we spoke about life, profession, moving around, open source, women of search, but also vector search for #ecommerce. As usual, you will find quite a bit of self-study material on the topic, including code, datasets and blogs. Be sure to check the show notes.

Connor is one of the top professionals in the Vector Search field I know for two years now. He has a background in Academia working on deep learning, which is a definite unfair advantage when it comes to the core of this field. He is not only able to recommend…

We often talk about neural networks, vector search, MLOps, search scalability and cost. But one topic that deserves more attention is where this journey begins: data. 🎙 In this episode (recorded right before Christmas) with Evgeniya Sukhodolskaya (Jenny), Data Advocate at Toloka, you’ll dive into the topic of data labeling…

Around two weeks ago I had a big honor to deliver the keynote at the Haystack EU conference held in Berlin, Germany. In it, I’ve shared some of my learnings from interviewing Vector Search makers in the Vector Podcast. Worth sharing them here: Malte Pietsch (CTO Deepset, Haystack): Metric blindness …

Vector Podcast episode with Doug Turnbull, Staff Relevance Engineer, Shopify New episode of Vector Podcast, Season 2! I’ve had an immense pleasure to talk to a mogul in Search world, original creator of Quepid (Search Quality Assurance and Toolbox I recommend to all my clients), Splainer, Learning to Rank plugin for Elasticsearch and an educational GitHub repo hello-ltr, author of…

Vector Podcast episode with Malte Pietsch, CTO at Deepset Big language models are a new trend that is about to launch and influence NLP and search engines. NLP with advances in Deep Learning is getting behind fascinating use cases, like question answering in healthcare and finance. Haystack platform enables you to create flexible search pipelines, starting with document conversions (say, pdf to text), extracting metadata useful for search & filter later, proceeding to semantic indexing and similarity matching. You can combine sparse retrieval with dense search, all this being agnostic to a particular vector DB or NLP model.