What are your favorite tips for reducing AI training costs?

Google Cloud AI Infrastructure
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Beginner Question: GPU vs TPU for AI Projects

I’m new to AI infrastructure and cloud computing. For small-to-medium AI projects, would you recommend GPUs or TPUs? What frameworks and optimization tips have worked best for you?

Looking forward to learning from the community!

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My favorite ways to reduce AI training costs are:

  • Using the smallest model that meets the requirements instead of training very large models.
  • Cleaning and filtering data before training to avoid wasting compute on low-quality data.
  • Starting with pre-trained models and fine-tuning them rather than training from scratch.
  • Monitoring experiments carefully and using early stopping when model performance stops improving.
  • Optimizing batch sizes, learning rates, and resource allocation to maximize GPU/TPU utilization.
  • Using distributed training and cloud resources efficiently, including spot/preemptible instances when appropriate.
  • Tracking metrics and experiment results to avoid repeating unsuccessful training runs.