What component of Google Cloud is specifically designed to provide acceleration for ML tasks?

Tensor Processing Units (TPUs) are specialized hardware accelerators designed by Google specifically for accelerating machine learning tasks. They are optimized for TensorFlow, Google's machine learning framework, which allows for faster processing and training of deep learning models compared to traditional CPUs or even GPUs. TPUs handle large matrix computations efficiently, which is crucial for the high volume of calculations involved in training and running machine learning models.

In contrast, the other components mentioned don't have the same level of specialization for ML tasks. Google Cloud Functions is primarily meant for running event-driven serverless applications, while Google Kubernetes Engine facilitates the orchestration of containerized applications. BigQuery ML enables users to create and execute machine learning models using SQL queries on large datasets but does not inherently provide hardware acceleration for ML tasks like TPUs do. Thus, TPUs stand out as the correct choice for providing acceleration specifically tailored to machine learning workloads.