In this article we will explore how self-hosted AI, specifically CodeProject.AI Server, empowers businesses to leverage the power of AI while maintaining control over their data.

A layman's description of how Kalman Filters work, and sample code that shows how to use it to forecast stock market volatilities

Democratizing Access to Large Language Models

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.

Effortlessly integrate and leverage OpenAI's text embeddings for enhanced text analysis in your .NET projects.

This article will show you how to create a module for CodeProject.AI Server that wraps some code that takes a long time to complete

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

Leveraging Open-Source AI Technologies with Red Hat OpenShift Data Science and Intel® Architecture

This article explores the various self-hosted AI frameworks available and understand their strengths, weaknesses, and compatibility with your project requirements. Make an informed decision that aligns with your organization's goals

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.