Lesson 1495 of 1570
AI and Training vs Inference: The Two Halves of Every AI
AI gets built in two phases — knowing the difference explains why it's both expensive and instant.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The big idea
- 2training
- 3inference
- 4cost
Concept cluster
Terms to connect while reading
Section 1
The big idea
Training = the months-long, $100M+ process where AI learns from massive data. Inference = the tiny, fast process every time you ask a question. Training happens once; inference happens billions of times a day. That's why companies obsess over inference cost and why your queries take seconds, not months.
Some examples
- GPT-4 training reportedly cost $100M+.
- Inference per query costs cents to fractions of cents.
- Companies make money on inference; training is a sunk cost.
- NVIDIA H100 GPUs power most training; cheaper chips run inference.
Try it!
Search 'GPT-4 training cost' and 'GPT-4 inference cost'. The 1000x difference is the whole AI economy explained.
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