beluis3d

Completely agree. There are three primary forms of bias: Human Bias, Data Bias, and Algorithmic Bias. A better solution is to improve existing machine learning models with existing solutions (e.g., domain adaptation, domain generalization, discovering latent domains). This will improve the overall performance.

Just heard.

This seems more like Computer Vision than augmented reality.

Easy to read. This article explains the difference between CS Topics such as Artificial Intelligence, Machine Learning, and Deep Learning:

https://medium.com/machinevision/overview-of-artificial-inte...

Very interesting. I like the connections to Gradient Descent and Gauss-Newton Algorithm.

Thanks for the feedback. Can you speak more to "null space optimization", "self intersection", and "hybrid position/force control"? High level descriptions of the situations would be helpful, thanks. Or links to resources.

CCD is good. FABRIK is even easier to implement, as is super stable: https://medium.com/unity3danimation/create-your-own-ik-in-un...

The FABRIK system is more stable and easier to implement. Check here for my review on FABRIK, plus pseudo-code: https://medium.com/unity3danimation/create-your-own-ik-in-un...

Udemy does this as well for all of their products.

FABRIK: https://medium.com/unity3danimation/create-your-own-ik-in-un...

Inverse Jacobian Methods can be computationally expensive. I suggest using FABRIK methods (suggested for JavaScript). Algorithm and pseudo-code here: https://medium.com/unity3danimation/create-your-own-ik-in-un...

Hey, thanks for reading. There are a TON of ways to implement Inverse Kinematics, and I'm going to cover the most popular ones in coming articles. Do you have any preferred animation techniques you'd like me to cover? All of my articles will be available here: https://medium.com/unity3danimation