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AWS Certified AI Practitioner · AWS
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B. Decrease the number of tokens in the prompt: In a few-shot learning scenario, the number of tokens used in the prompt contributes directly to the cost, as you're billed based on the number of tokens processed during each invocation. By decreasing the number of tokens in the prompt, the company can reduce the cost per invocation while still maintaining the model's performance. This can be done by reducing the number of examples or making the examples more concise.
D. Use Provisioned Throughput To lower the monthly cost, the company can use Provisioned Throughput (PT) to scale their model's resource utilization. This allows them to pay only for the actual compute time used by the model, rather than paying a fixed monthly fee.
you are right to point this out but B is a more correct answer. There is a limit as to how much you can save with Provisioned Throughput (given that you were using On Demand before and that the company is okay with a longer term commitment). However, Decrease the number of tokens in the prompt is going to be more effective and doesn't require a longer term commitment.