Noise Algorithms vs Random Number Generators

Developers should learn noise algorithms when working on projects involving procedural generation, such as game development for terrain or texture creation, or in simulations requiring natural variability, like weather modeling meets developers should learn about rngs when building secure systems (e. Here's our take.

Noise Algorithms

Nice Pick

Developers should learn noise algorithms when working on projects involving procedural generation, such as game development for terrain or texture creation, or in simulations requiring natural variability, like weather modeling

Pros

• They are also useful in data visualization to add subtle randomness for aesthetic purposes or in machine learning for data augmentation to improve model robustness
• Related to: procedural-generation, computer-graphics

Cons

• Specific tradeoffs depend on your use case

Random Number Generators

Developers should learn about RNGs when building secure systems (e

Pros

• g
• Related to: cryptography, statistical-analysis

Cons

• Specific tradeoffs depend on your use case

The Verdict

Use Noise Algorithms if: You want they are also useful in data visualization to add subtle randomness for aesthetic purposes or in machine learning for data augmentation to improve model robustness and can live with specific tradeoffs depend on your use case.

Use Random Number Generators if: You prioritize g over what Noise Algorithms offers.

The Bottom Line

Noise Algorithms wins

Developers should learn noise algorithms when working on projects involving procedural generation, such as game development for terrain or texture creation, or in simulations requiring natural variability, like weather modeling