Alan Tseng

I'm no expert, but this reminds me of traditional control theory like PID controllers and Kalman filters. Seems like the real benefit of modern AI is learning and adapting the complex, high-level policies you mentioned in the blog post. For autonomous robots and drones, combining classical control with reinforcement learning seems to be the key.

This is a really detailed guide to PyTorch profiling—definitely a tool that many AI engineers overlook. That said, the data can still be quite overwhelming. A quick cheatsheet decoding what the core metrics mean (especially for custom kernels, Tensor Cores, or multi-GPU setups) would be a great addition.*

For anyone wanting to go even lower-level on NVIDIA hardware, Nsight Compute is also worth a look for some serious profiling: https://developer.nvidia.com/nsight-compute

Edit: OK I saw the summary at the end of the post. But a concise, self-contained cheatsheet with little graphics would help a lot.