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As a member of a video game development team, you are tasked with creating characters whose features and expressions are derived from real human players using GAN (Generative Adversarial Network) models. The training process is resource-intensive, and your goal is to enhance training efficiency without significantly increasing costs. The team is also concerned about scalability and compliance with data privacy regulations. Which of the following strategies would best meet these requirements? (Choose three options)
A
Leverage preemptible Cloud TPU for cost-effective, fault-tolerant machine learning workloads, ensuring up to 70% cost reduction for fault-tolerant tasks.
B
Utilize AI Platform with TPUs to take advantage of TensorFlow APIs and custom templates for a managed environment that supports scalability and compliance with data privacy regulations.
C
Implement the Cloud TPU Profiler TensorBoard plugin to optimize your workload through visualization tools, enabling detailed analysis and optimization of training processes.
D
Set up a Compute Engine Cloud TPU VM and manually install TensorFlow for your project, which may increase setup time and potential for configuration errors.
E
None of the above options are suitable for enhancing training efficiency while managing costs and ensuring compliance.