However, as AI expands from cloud data centers to industrial automation, robotics, autonomous machines, and edge systems, the physical realities of power delivery, sensing, and system efficiency are becoming critical factors in performance, scalability, and reliability.
The new e-book brings together the perspectives of experts from across the AI ecosystem, including specialists from onsemi, Amazon, Google, Meta, and Tesla, to analyze how advances in power semiconductors, sensing technologies, and hardware architectures are contributing to AI applications, from hyperscale data centers to robots to real-world autonomous systems.
As AI workloads continue to grow, the industry faces increasing challenges in providing the power needed to support ever-dense computing environments. The ebook examines how the shift to higher-voltage architectures and the adoption of wide-bandgap semiconductor technologies, such as silicon carbide (SiC) and gallium nitride (GaN), are helping data center operators improve efficiency, reduce thermal management needs, and decrease overall energy consumption.
The ebook also highlights the growing importance of sensing in physical AI applications. While vision remains a key element of autonomous systems, intelligent machines are increasingly relying on a combination of image, force, torque, position, and proximity sensing to interact safely and effectively with the physical world. The ebook explains how improvements in the quality of sensing systems can reduce processing overhead, decrease energy consumption, improve response times, and enable more reliable AI decision-making at the edge.
The topics covered in the e-book are as follows:
How growing AI workloads are transforming energy requirements in data centers, edge infrastructure, and industrial systems.
The role of silicon carbide (SiC) and gallium nitride (GaN) technologies in improving energy efficiency, reducing thermal issues, and resilience to higher power densities.
Why sensing quality directly impacts AI accuracy, latency, power consumption, and overall system performance.
Benefits of intelligent edge sensing, local data processing, and sensor fusion in autonomous and AI systems.
Strategies for reducing latency and improving safety in robotics, industrial automation, and collaborative machines.
System-level approaches to integrating sensing, power delivery, and AI processing to enable physical autonomy.
The e-book also features onsemi technologies that support AI applications, such as EliteSiC ™ silicon carbide solutions, Hyperlux ™ image sensors , the Treo™ analog and mixed-signal platform, industrial connectivity solutions, and advanced energy management.
