Author: Marcin Borecki

Architecting Enterprise-Grade AI Solutions with .NET 9

Summary: This article explores best practices for architecting enterprise-grade AI solutions using .NET 9. Learn how to design scalable, maintainable, and secure AI systems that meet the demands of enterprise environments while leveraging the latest features in .NET 9. Introduction As artificial intelligence continues to transform businesses across industries, the need for robust, enterprise-grade AI […]

Building Real-Time AI Applications with SignalR and .NET

Summary: This post explores how to build real-time AI applications using SignalR and .NET. Learn how to create interactive applications that leverage AI capabilities while providing immediate feedback and updates to users through real-time communication. Introduction Real-time communication has become an essential component of modern web applications, enabling immediate updates, interactive experiences, and collaborative features. […]

Implementing AI-Powered Code Generation and Assistance in .NET Applications

Summary: This post explores how to integrate AI-powered code generation and assistance capabilities into .NET applications. Learn how to leverage large language models to create tools that can generate code, provide intelligent code completion, and assist developers throughout the development lifecycle. Introduction Artificial Intelligence has revolutionized many aspects of software development, and one of the […]

Fine-Tuning LLMs for Domain-Specific Applications in .NET

Summary: This post explores how to fine-tune large language models for domain-specific applications using .NET. Learn how to prepare training data, fine-tune models, and deploy them in .NET applications to achieve better performance on specialized tasks. Introduction Large Language Models (LLMs) have revolutionized natural language processing with their ability to understand and generate human-like text. […]

Implementing Multi-Modal AI Applications with .NET and Azure AI Vision

Summary: This post explores how to build multi-modal AI applications that can process both text and images using .NET and Azure AI Vision. Learn how to create applications that can understand and generate content across different modalities, enabling more natural and comprehensive AI experiences. Introduction Multi-modal AI represents a significant advancement in artificial intelligence, enabling […]

Building AI-Powered Microservices with .NET 8 and Azure Container App

Summary: This post explores how to design, develop, and deploy AI-powered microservices using .NET 8 and Azure Container Apps. Learn how to create scalable, resilient AI services that leverage the latest features of .NET 8 and the managed container environment of Azure Container Apps. Introduction Microservices architecture has become a popular approach for building complex […]

Optimizing Vector Search in .NET Applications with Azure AI Search

Summary: This post explores how to implement and optimize vector search in .NET applications using Azure AI Search. Learn about vector embeddings, similarity search algorithms, and best practices for building high-performance semantic search experiences. Introduction Vector search has revolutionized how we implement search functionality in modern applications. By representing content as numerical vectors (embeddings) and […]

Developing Cross-Platform AI Applications with .NET MAUI and Azure AI

Summary: This post explores how to build cross-platform AI-powered applications using .NET MAUI and Azure AI services. Learn how to create intelligent mobile and desktop apps that leverage AI capabilities while maintaining a single codebase. Introduction The demand for intelligent applications that work seamlessly across multiple platforms continues to grow. For .NET developers, the combination […]

Implementing Responsible AI Practices in .NET Applications

Summary: This post explores how to implement responsible AI practices in .NET applications. Learn about Microsoft’s Responsible AI principles, tools for fairness assessment, transparency techniques, and how to build AI systems that are ethical, transparent, and accountable. Introduction As artificial intelligence becomes increasingly integrated into our applications and services, the importance of implementing responsible AI […]

Leveraging Azure AI Studio for .NET Developers: Building End-to-End AI Solutions

Summary: This post explores how .NET developers can leverage Azure AI Studio to build comprehensive AI solutions. Learn how to use this unified platform to develop, test, and deploy AI applications with seamless integration to your .NET projects. Introduction Azure AI Studio represents a significant evolution in Microsoft’s AI development ecosystem, providing a unified platform […]