AI Systems Thinking – Algorithms, Data, Compute, and Knowledge
Lesson 3: Compute, Scale, and Practical Limits
Lesson Objectives
By the end of this lesson, students should be able to:
- Explain compute in non-technical language.
- Recognize tradeoffs among speed, cost, quality, and complexity.
- Avoid treating scale as wisdom.
Lesson Content
Compute is processing capacity. More compute can allow larger models, more data processing, faster responses, or more complex workflows. But compute does not automatically create good judgment. A system can be large and still misunderstand the task, rely on weak data, or produce output that needs review.
Practical teams care about tradeoffs. Faster output may cost more. More complex workflows may need monitoring. Larger systems may produce impressive answers that still require verification.
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