In this four-part series, you’ll learn how to create an Intelligent App with Azure. This first tutorial walks you through what Azure AI and Azure Container Apps are, how to set up an Azure environment, and building your basic application.

In this article, we build a Retrieval-Augmented Generation (RAG) pipeline using KitOps, integrating tools like ChromaDB for embeddings, Llama 3 for language models, and SentenceTransformer for embedding models.

In the last article, we created an Intelligent App that leverages Azure AI Vision to analyze images and extract data. We developed an API to perform optical character recognition (OCR) on uploaded images and tested this API locally.

This article discusses the application of Stable Diffusion models in generative AI, focusing on image generation from text prompts.

Democratizing Access to Large Language Models

How to control game elements based on predefined conditions

This article provides a comprehensive guide to TensorFlow 2.x, covering its execution modes, model building APIs, and insights for choosing the right approach for machine learning projects.

An overview on how to interrogate Dall-E in VB.NET

Use CodeProject.AI Server to simplify your MLOps by providing a self-hosted, open source solution with easy installation, support for any language or framework, and built-in management of AI modules

In the part of our series on intelligent apps, we’ll explore how AI is transforming application development, from design and architecture to building.