Nvidia's research highlighting small language models (SLMs) as the future of enterprise AI. SLMs, with fewer than a billion parameters, offer speed, customization, privacy, and cost-effectiveness that large models can't match.
The piece explains how SLMs work through techniques like pruning, quantization, knowledge distillation, and model compression. It discusses the benefits including faster responses, lower costs, better customization, enhanced privacy, and energy efficiency.
Real-world applications span healthcare, finance, retail, manufacturing, and autonomous agents. The blog emphasizes hybrid approaches combining SLMs with large models for optimal performance and cost-effectiveness in enterprise environments.
