ML Engineer by profession. In today’s rapidly evolving AI era, understanding hardware is no longer optional it’s foundational. As AI models grow in complexity, the performance bottleneck increasingly lies in how well software leverages underlying compute architectures. From CPU cores handling sequential workloads to GPU threads enabling massive parallelism, and further to specialized AI accelerators designed for efficiency and speed, the hardware ecosystem is redefining how we train, deploy, and scale intelligent systems.