http://localhost:1313/chapter1/s3/index.html Work in progress This section is under construction. This information hasn’t been reviewed or edited yet! Introduction The AI landscape can be confusing when it comes to deployment choices, particularly because similar names often mask very different security and operational implications. For instance, when someone mentions “using GPT,” they might be referring to ChatGPT’s web interface, OpenAI’s API service, or Azure’s enterprise deployment—each with vastly different security profiles and use cases. In some cases, people even confuse the term “ChatGPT” with the underlying GPT model itself, further complicating conversations. Hugo en http://localhost:1313/chapter1/s3/s3_activity/index.html Mon, 01 Jan 0001 00:00:00 +0000 http://localhost:1313/chapter1/s3/s3_activity/index.html Work in progress This section is under construction. This information hasn’t been reviewed or edited yet! Practical Activity Overview This application demonstrates how to run a local inference using Ollama. We’ll be building and running this application locally on your machine. Prerequisites Python 3.8 or higher installed on your system Basic familiarity with command line/terminal A text editor or IDE of your choice At least 8GB RAM (16GB recommended for better performance) At least 10GB free disk space Activities Step 1: Set Up Your Development Environment 1.1 Make sure you are using the virtual environment we created in the previous activity: