- LLMs and SLMs: LLMs have hundreds of billions of parameters, while SLMs have fewer, ranging from a hundred million to tens of billions.
- Performance: SLMs consume fewer resources than LLMs, are customizable, and provide good performance, particularly for specific tasks like retrieval-augmented generation (RAG).
- Industry Trends: Companies like Google, Mistral AI, and Microsoft are rolling out compact SLMs for mobile devices.
Impact
- Smaller language models revolutionize AI accessibility and efficiency.
- Increased adoption of compact models across industries.
- Shift towards mobile-centric AI applications.
Eksentricity 