As ARM64 adoption grows across PCs and embedded devices, developers need robust tooling to build, optimize, and debug applications efficiently. This session explores the latest advancements in developer tools, compilers, debuggers, emulation strategies, and profiling techniques that simplify development on ARM64. We will discuss how modern toolchains support cross-compilation, how to optimize performance for ARM64-native applications, and best practices for ensuring seamless development workflows across multiple architectures. Attendees will gain insights into how development environments, open-source frameworks, and performance analysis tools are evolving to make ARM64 development as seamless as possible.

The evolution of on-device AI is transforming how developers build and deploy machine learning models, enabling real-time performance, enhanced privacy, and power-efficient execution. Windows on Snapdragon (WoS) provides a robust AI development ecosystem, allowing developers to run AI models directly on the device without relying on cloud inference. This session will explore best practices for optimizing AI workloads, leveraging hardware acceleration, and utilizing industry-standard frameworks to deploy AI models efficiently on WoS-powered devices. Attendees will gain insights into the AI developer workflow, from model conversion and quantization to execution and optimization, ensuring seamless performance for a wide range of AI applications.

Panel discussion on Windows on Arm with Microsoft, Arm, Qualcomm, Blender