Abhishek Rai: SLMs and the Shift Toward Lightweight, Everywhere AI
For years, the story of AI has been about going bigger — bigger models, bigger data, bigger GPUs. But a powerful counter-trend is emerging: going smaller and smarter. Small Language Models (SLMs) and Tiny LMs are reshaping how we think about deploying and using AI. In this talk, we’ll explore how this shift is enabling organizations and individuals to run advanced language capabilities on edge devices, low-cost GPUs, and even mobile hardware. We’ll look at what’s driving this movement — from efficiency breakthroughs like pruning and quantization to new training approaches that let smaller models punch far above their weight. More importantly, we’ll talk about why this matters: making AI more accessible, energy-efficient, privacy-friendly, and deployable in real-world environments where massive compute isn’t an option. We’ll also look ahead at what the next few years might hold for the SLM ecosystem — including personalized on-device models, hybrid AI architectures, and new business opportunities enabled by this “small is powerful” era. Whether you’re an AI practitioner, product leader, or just curious about where the field is heading, this session will give you a clear view of the trend, future, and impact of this major shift in AI.
