Developers recognize the critical need for efficient AI solutions across diverse computing environments. As enterprises race to deploy AI projects, developers can gain a competitive edge by leveraging the AI and machine learning (ML) tools in software development kits (SDKs) to optimize large language models (LLMs) that power chatbots, virtual assistants, and other AI systems. Hardware-specific SDKs are designed to enable seamless integration with on-device hardware, enhancing model execution and accelerating neural network inference to improve the model’s ability to apply patterns to new input.
With the transition to AI PCs, developers face important hardware-optimization choices for performance and efficiency. For example, they can build AI applications on devices powered by Intel® Core™ Ultra processors with hybrid architectures—using both Performance-cores (P-cores) and Efficient-cores (E-cores)—or on devices powered by Qualcomm® Snapdragon® Arm64 systems on a chip (SoCs), which are often used for mobile devices. Prowess Consulting tested the Intel® OpenVINO™ toolkit and the Qualcomm® AI Engine Direct SDK on Dell™ XPS™ 13 AI PCs to determine the better choice for developers. The Intel OpenVINO toolkit earned higher scores in target hardware support, platform compatibility, features, ease of use, and other factors.