Tag: Edge AI

Learn to optimize AI model deployment for mobile and laptop environments using Google's Gemma 4 Quantization-Aware Training (QAT) …

Explore and build three distinct on-device AI agents—a voice assistant, a data summarizer, and an anomaly detector—using tiny LLMs and …

Learn the fundamentals of model compression and Quantization-Aware Training (QAT) to optimize large language models like Gemma 4 for …

Dive into Quantization-Aware Training (QAT) for Gemma 4 models. Learn its principles, how it optimizes AI for mobile and laptop devices, and …

Explore Google's Gemma 4 family, including QAT variants, for optimizing AI model deployment on mobile and laptop devices. Learn about …

Learn how to access, understand, and select the right Gemma 4 Quantization-Aware Training (QAT) checkpoints for your mobile and laptop AI …

Learn how to effectively evaluate the performance of Gemma 4 Quantization-Aware Training (QAT) models, focusing on critical metrics like …

Learn how to deploy Google's Gemma 4 QAT models to mobile and laptop environments, focusing on efficiency, reduced memory, and faster …

Explore real-world applications, best practices for deployment, and future trends of Gemma 4 Quantization-Aware Training (QAT) models for …

Understand the landscape of on-device AI agents and tiny LLM systems, set up your development environment, and explore core tooling for edge …

Learn to implement robust, on-device speech-to-text functionality using Whisper.cpp, a high-performance C++ port of OpenAI's Whisper model, …

Master techniques for optimizing AI agent and tiny LLM performance and resource usage on constrained edge devices for real-world production …