Milvus
Open-source vector database
Episodes
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#3673: Knowledge Graphs vs SQL: How Custom Relationships Change RetrievalWhy naming relationships (not just connecting data) transforms how you retrieve information. -
#2673: The Embedding Coupling Problem: Editing Vector StoresCan you edit or delete individual chunks in Pinecone? And can you actually back up a vector index? Yes—but with critical caveats. -
#2466: The Hidden Trap of Embedding Model Lock-InWhat happens when your vector database works great — until your embedding model gets deprecated and your vectors become useless. -
#2271: Vector Search in a Single FileWhat if you could do vector search with just SQLite? We explore sqlite-vec, the extension that adds embeddings to the world's simplest database, an... -
#2179: Building Cost-Resilient AI AgentsFailed API calls in agent loops aren't just technical problems—they're direct budget drains. Here's how checkpointing, retry strategies, and cachin... -
#2139: AI Wargame Memory: Beyond the Context WindowWhy simply extending context windows fails in multi-agent simulations, and how layered memory architectures preserve strategic fidelity. -
#1794: RAG Is Cheaper Than You Think (Until It’s Not)From a $1 embedding bill to a $10k/month vector database bill, here’s the real math behind RAG in 2026. -
#1792: Google's Native Multimodal Embedding Kills the Fusion LayerGoogle’s new embedding model maps text, images, audio, and video into a single vector space—cutting latency by 70%. -
#1592: The Vector Debt Trap: Choosing Embeddings That LastStop treating embedding models like plumbing. Learn how to navigate vector debt, multimodal retrieval, and database configuration for RAG. -
#1483: The Recall-Per-Dollar Era: Mastering Vector Database TuningStop burning money on unoptimized vector searches. We dive into HNSW tuning, distance metrics, and the vital "recall-per-dollar" metric. -
#1475: The Folder Illusion: Why Cloud Storage Breaks Your Mental ModelFolders are a lie in the cloud. Explore why Amazon S3 uses flat namespaces and "keys" instead of traditional file hierarchies. -
#1235: Beyond "No Training": Securing the New Agentic AI StackThink your data is safe because of a "no training" clause? We deconstruct the hidden security risks within the modern agentic AI stack. -
#1215: The Vector DB Hangover: Scaling Without Going BrokeStop overpaying for your AI's memory. We break down the math of self-hosting vectors and the rise of serverless search. -
#816: From Scrolls to SQL: The Evolution of Human OrderExplore the history of how we organize the world, from ancient library catalogs to the future of AI-driven vector databases. -
#662: The Geopolitical Graph: Mapping Global Power with AIMove beyond flat maps. Discover how graph databases and AI reveal the hidden connections and second-order effects shaping our global landscape. -
#200: Why Graph RAG Beats Flat Vectors for AI MemoryExplore how the AI stack is evolving from simple vector search to complex Graph RAG and why the "boring" Postgres database is winning the race. -
#64: How AI Learns to See, Hear, and Think TogetherAI is evolving beyond text, learning to see, hear, and understand our world. Discover the future of human-AI interaction! -
#30: Which AI Tools Will You Still Use Next Year?RAG vs. Memory: Are you building resilient AI? Discover the crucial difference between these two foundational pillars.