Small Language Models (SLMs) are becoming popular as practical and flexible AI solutions, offering a simpler, more cost-effective alternative to larger models. Compared to Large Language Models (LLMs), SLMs have a simplified design, lower processing demands, and better affordability, making them suitable for a wider range of applications.
Advantages of Small Language Models
SMALL Language Models (SLMs) are appealing to businesses and individuals with tighter budgets due to their simplified design and lower processing demands. They enable quicker development cycles, experimentation, and precise customization for specific activities or sectors. Additionally, SLMs offer better privacy and security, making them suitable for handling sensitive data applications.
Some Popular Examples of SLMs
SLMs include Llama 2, Alpaca 7B, Mistral and Mixtral, Microsoft’s Phi, DistilBERT, and Orca 2. These models offer competitive performance and flexibility in capturing a wide range of language patterns and behaviors.
Conclusion
SLMs represent a significant advancement in AI research and development, offering a more effective, flexible, and affordable way to address language challenges in AI. The emergence of SLMs promises to drive innovation, democratize access to AI, and transform sectors worldwide as the AI ecosystem develops.
Practical AI Solutions for Your Company
Discover how AI can transform your work processes, identify automation opportunities, define KPIs, select AI solutions, and implement them gradually. For AI KPI management advice and continuous insights into leveraging AI, connect with us at hello@itinai.com. Explore the AI Sales Bot from itinai.com/aisalesbot designed to automate customer engagement 24/7 and manage interactions across all customer journey stages.
List of Useful Links:
AI Lab in Telegram @aiscrumbot – free consultation
Twitter – @itinaicom
