Concept
Vector search finds data by similarity of embeddings rather than exact matches and is a foundation for retrieval-augmented AI applications; Azure SQL Database and SQL Server 2025 support it natively.
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2026-06-08 · Video on YouTube
The explosion of AI-powered applications has created a new challenge: how do you efficiently search through billions of vector embeddings without exploding infrastructure costs? In this episode, we explore the “billion-vector problem” and compare two leading…
2026-07-16 · Video on YouTube
Vector databases are one of the key technologies powering modern AI applications, yet most people never interact with them directly. Unlike traditional databases that search for exact words or values, vector databases search by meaning, enabling AI to…
2026-07-17 · Video on YouTube
Azure AI Search is Microsoft's intelligent search and information retrieval service for building modern search experiences and AI-powered applications. It combines traditional keyword search with vector search, semantic ranking, and AI enrichment, making it a…
2026-06-07 · Video on YouTube
In this episode, Mirko Peters explores one of the most ambitious experiments in enterprise AI: engineering Microsoft Copilot to analyze and reason across more than 35 million pages of highly complex and interconnected information, inspired by the scale and…
2025-12-17 · Video on YouTube
Your AI isn’t broken — your digital city is lying to it. In this noir-style podcast episode, we pull back the curtain on why Copilot, search, and enterprise AI tools hallucinate, misfire, and surface the wrong answers even when the data “exists.” The culprit…
2026-05-01 · Video on YouTube
This episode explains that vector search on its own is not a complete or reliable strategy for building accurate AI systems like Copilot. While many organizations rely on embeddings and vector databases to retrieve information, this approach often leads to…
2026-08-17 · Video on YouTube
Most teams still treat Azure SQL as passive storage behind the application. In this interview, Dirceu Resende shows data engineers and architects how Azure SQL Database can call REST APIs, automate workflows and support AI with vector search. You learn where…
2025-11-03 · Video on YouTube
AI is becoming a first-class citizen in the .NET ecosystem, and in this episode we explore how the new integrated AI Engine in .NET 10 transforms the way developers build intelligent applications. You’ll learn how .NET now provides a unified platform for…
2026-07-16 · Video on YouTube
Retrieval-Augmented Generation (RAG) is one of the most important techniques behind modern AI applications, enabling large language models to answer questions using your own business data instead of relying only on their training knowledge. In this episode of…
Vector search returns content that is mathematically similar, not necessarily correct or relevant. Results can look right but be wrong, which leads to hallucinations and reduced trust. The real issue is how information is retrieved, not the language model. · From the episode: Improve Microsoft Copilot Accuracy Beyond…
Hybrid retrieval combines vector search with keyword search so the system matches both meaning and exact terms. This improves precision and recall, and it is presented in the episode as the new standard for Copilot-style retrieval. · From the episode: Improve Microsoft Copilot Accuracy Beyond…
Embedding models focus on semantic similarity, so they can ignore critical metadata such as audience or recency. A query with specific criteria may then return loosely related results, which is how important details get lost. · From the episode: Improve Microsoft Copilot Accuracy Beyond…
The episode covers AI, vector search and RAG in connection with Azure SQL. It also touches Microsoft Fabric, Power BI and observability as part of the discussion about the changing role of databases in modern applications. · From the episode: When Azure SQL Becomes an Application…
They work together with Microsoft.Extensions.AI and Visual Studio 2026 to simplify tasks such as vector search and workload orchestration, so AI features fit into familiar application architecture. · From the episode: Build AI Applications with .NET 10
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Maintained by Mirko Peters (Microsoft MVP) · Last updated:
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