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Rahul Agarwal

Founder | Agentic AI... • 18h

Small Language Models are set to transform AI agents-but only if implemented the right way. By 2027, Gartner predicts task-specific SLMs will be used three times more than general-purpose LLMs. NVIDIA agrees, calling them “the future of AI agents.” What are SLMs? Lightweight transformer models with millions to low billions of parameters. They prioritize speed, efficiency, and lower memory use over broad generalization. Why companies adopt SLMs: * Privacy-focused on-prem solutions * Cost-effective for high-volume tasks * Easily fine-tuned for specialized applications Optimizing SLMs in AI agents: * Intelligent Routing: Simple tasks to SLMs, complex ones to LLMs * Pipeline Collaboration: SLMs preprocess, LLMs refine * Parallel Verification: SLMs draft while LLMs verify * Conditional Activation: Escalate only when confidence is low Who’s using them: Uber, OpenAI, Microsoft leverage SLMs for faster, specialized AI pipelines. Follow me for more such content on AI!

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