Microprocessors are vital for the performance of AI systems, enabling efficient data processing and decision-making in real-time applications. However, with the increasing complexity of AI models, challenges like high power consumption, limited scalability, and integration with AI-specific algorithms have become more prominent.
Current research is addressing these challenges by focusing on the development of energy-efficient microprocessors that balance computational power with minimal energy usage. Efforts are also being directed towards enhancing parallel processing, reducing latency, and improving hardware integration to better support AI workloads. The goal is to create microprocessors that can handle the demands of modern AI applications while remaining scalable, cost-effective, and environmentally friendly.