LLMs are powerful, but too large for most production environments. That’s where SLMs (Small Language Models) and distillation come in.
This video covers:
The role of small models in real-world systems
How knowledge distillation lets small models learn from larger ones
Trade-offs between speed, cost, and accuracy
Practical examples of deploying SLMs in apps and services
If you're working on ML infrastructure, backend deployment, or productizing AI, this is where theory meets engineering reality.