AI Signals From Tomorrow
Signals from Tomorrow is a podcast channel designed for curious minds eager to explore the frontiers of artificial intelligence. The format is a conversation between Voyager and Zaura discussing a specific scientific paper or a set of them, sometime in a short format and sometime as a deep dive.
Each episode delivers clear, thought-provoking insights into how AI is shaping our world—without the jargon. From everyday impacts to philosophical dilemmas and future possibilities, AI Signals from Tomorrow bridges the gap between cutting-edge research and real-world understanding.
Whether you're a tech enthusiast, a concerned citizen, or simply fascinated by the future, this podcast offers accessible deep dives into topics like machine learning, ethics, automation, creativity, and the evolving role of humans in an AI-driven age.
Join Voyager and Zaura as they decode the AI signals pointing toward tomorrow—and what they mean for us today.
AI Signals From Tomorrow
Large Language Models On The Edge
We discuss the paper "A Review on Edge Large Language Models: Design, Execution, and Applications" (https://arxiv.org/pdf/2410.11845) which is a survey on the design, execution, and applications of large language models (LLMs) on edge devices. It highlights the challenges of deploying large models with billions of parameters on resource-constrained hardware, including memory constraints and computational demands. The paper explores offline pre-deployment techniques such as quantization, pruning, knowledge distillation, and low-rank approximation to make models more efficient, and online runtime optimizations, covering software-level optimizations, hardware-software co-design, and hardware-level considerations. Finally, it showcases various on-device LLM applications across personal, enterprise, and industrial domains and discusses future research directions and open challenges in this field.