Cost optimization in Prompt Engineering / GenAI - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is cost optimization in machine learning?

Cost optimization means finding ways to reduce the money spent on training and running machine learning models without losing quality.

beginner

Why is cost optimization important in AI projects?

Because training and using AI models can be expensive, cost optimization helps save money and makes projects more efficient and sustainable.

intermediate

Name one common method to reduce training costs in machine learning.

Using smaller or simpler models, like fewer layers or parameters, can reduce training time and cost.

intermediate

How does using cloud spot instances help with cost optimization?

Spot instances are cheaper cloud computers that can be used when available, lowering costs but with some risk of interruption.

advanced

What role does model pruning play in cost optimization?

Model pruning removes unnecessary parts of a model to make it smaller and faster, which reduces computing costs.

What is a simple way to reduce machine learning training costs?

A Increase training data size

B Train on slower hardware

C Add more layers to the model

D Use a smaller model

Using a smaller model reduces computation and training time, lowering costs.

Which cloud resource is usually cheaper but less reliable for training?

A Spot instances

B Dedicated instances

C On-premise servers

D Reserved instances

Spot instances cost less but can be interrupted, so they save money with some risk.

What does model pruning do?

A Removes unnecessary parts

B Increases training time

C Adds more neurons

D Adds more training data

Pruning removes parts of the model that are not needed, making it smaller and cheaper to run.

Why is cost optimization important in AI?

A To make models more complex

B To save money and resources

C To increase training time

D To use more data

Cost optimization helps save money and makes AI projects more efficient.

Which of these is NOT a cost optimization strategy?

A Using simpler models

B Reducing model size

C Training longer on expensive hardware

D Using cheaper cloud options

Training longer on expensive hardware increases costs, so it is not a cost optimization strategy.

Explain in your own words what cost optimization means in machine learning and why it matters.

Think about how saving money helps AI projects run better.

List and describe two methods to reduce costs when training machine learning models.

Consider model size and cloud computing options.