Artificial intelligence is rapidly expanding its presence in our daily and professional workflows. More and more tasks rely on AI-powered solutions, and a growing number of models are being integrated into both everyday consumer applications and complex business processes. As a result, the demand for AI models delivered as services continues to grow.
At the same time, concerns about data protection are becoming increasingly important. Many users and organizations prefer to keep their information private rather than send sensitive data to large cloud-based AI providers. This naturally raises an important question: How can we use AI models directly on our personal computers or laptops, without depending on external cloud services?
Fortunately, the ecosystem around local AI is evolving…
Artificial intelligence is rapidly expanding its presence in our daily and professional workflows. More and more tasks rely on AI-powered solutions, and a growing number of models are being integrated into both everyday consumer applications and complex business processes. As a result, the demand for AI models delivered as services continues to grow.
At the same time, concerns about data protection are becoming increasingly important. Many users and organizations prefer to keep their information private rather than send sensitive data to large cloud-based AI providers. This naturally raises an important question: How can we use AI models directly on our personal computers or laptops, without depending on external cloud services?
Fortunately, the ecosystem around local AI is evolving rapidly. A number of solutions already exist that make running models locally not only possible, but in many cases surprisingly simple. These tools allow users to maintain full control over their data while still benefiting from powerful AI capabilities. As demand increases, the market continues to offer more accessible, efficient, and user-friendly options.
In this series of articles, I will explore the most available approaches for running AI models locally and discuss what opportunities and advantages localized AI systems provide. We’ll look at the different tools, compare their capabilities, and walk through the process of implementing such a system on your personal machine. We will also explore how to integrate local AI tools into broader workflows and automation pipelines.
Additionally, we will dive into key practical topics:
- How to choose the right AI model for your needs
- How to install and run models on your local computer
- How various tools and runtimes differ in performance and speed
- How to embed AI capabilities into your daily work processes
The goal of this series is to give a clear, beginner-friendly overview of the current local AI landscape and help you understand how to bring powerful AI tools directly to your own device.