About open source

The first time that I heard the phrase “Open Source” was back in highschool. At that time, I was learning 3D modeling back then, and Blender, an open source software was my tool.

So, my first impression of open source was that it meant free. Later on, as I progressed with Blender, I gradually realized another advantage of open source, which is customization. Since Blender is open source, it allows users to modify it and extend its functionality. Many people can contribute to its development, creating plugins and add-ons. For example, one of my visualization project was base on a plugin that converted music file into numerical values, which I could apply to 3D models. In the contrast, with closed source softwares, users must rely on the company to introduce new features. This process can take a long time and eventually the updates might not actually meet the needs of the user.

Despite its many advantages, open source also comes with challenges. One major drawback is frequent maintenance and lack of stability. Although Blender is relatively stable, unofficial add-ons often suddenly become unusable after a few version updates, unlike those in closed-source software, which usually receive consistent support.

Four Projects that chosen by me

1. Blender
   Blender is a open source 3D modeling software used for modeling, animation, and rendering. I’ve been using Blender for 4 years and witnessed its progress. It is now gradually replacing some of the traditional animation production workflows.
2. Godot Engine
   Godot is an open-source game engine that primarily focuses on 2D games. Typically, if you want to publish a game using a commercial engine, you need to pay a licensing fee. However, Godot is completely free and open-source, making it an attractive choice for indie developers.
3. DeepSeek
   DeepSeek is an open-source AI chat robot, which is similar to ChatGPT. It provides open-access models for researchers and developers.
4. Python
   Python is an open-source programming language widely used in fields such as finance, data science, web development, and machine learning. Its simplicity make it an ideal choice for beginners. I’ve taken the NYU CS-SHU Data Structure course, which was based on Python.