SLMs vs LLMs: Building Faster, Cheaper, and More Private AI Systems
Failed to add items
Sorry, we are unable to add the item because your shopping cart is already at capacity.
Add to Cart failed.
Please try again later
Add to Wish List failed.
Please try again later
Remove from wishlist failed.
Please try again later
Adding to library failed
Please try again
Follow podcast failed
Please try again
Unfollow podcast failed
Please try again
-
Narrated by:
-
By:
Do you really need a trillion-parameter model to solve enterprise problems?
In this episode, we unpack why Small Language Models (SLMs) are gaining momentum across enterprise AI. We explore how techniques like knowledge distillation and quantization allow smaller models to deliver competitive performance - while significantly reducing cost, latency, and energy consumption.
We also discuss why SLMs are a natural fit for agentic AI, enabling multi-step reasoning, on-device and on-prem deployments, and stronger data privacy in regulated environments. The takeaway: the future of AI isn’t just about bigger models, but smarter architectures built for real-world production.
No reviews yet