What are small language models and how do they differ from large ones?
9 days ago
- #Technology
- #AI
- #Language Models
- Microsoft released a new small language model (SLM) that operates on users' computers.
- Small language models (SLMs) are specialized tools with millions to tens of millions of parameters, designed for specific tasks.
- Large language models (LLMs) like ChatGPT and Gemini are versatile, with billions or trillions of parameters, capable of handling diverse tasks.
- LLMs excel in nuanced understanding, complex reasoning, and generalizing knowledge to new scenarios.
- LLMs require significant computational power, usually run in the cloud, and have high operational costs.
- SLMs are fast, efficient, and affordable, making them ideal for specific applications like book recommendations or grammar checking.
- SLMs are easier to fine-tune for specific needs, such as medical appointment scheduling or language learning.
- SLMs are suitable for constrained environments like self-driving cars or satellites with limited processing power.
- Hybrid approaches use SLMs for routine tasks and LLMs for complex queries, optimizing cost and performance.
- The choice between SLMs and LLMs depends on specific needs, resources, and the complexity of tasks.