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Powering “AI At The Edge” With Maxim’s PMICs

The demand for highly flexible and adaptive PMICs that power Application Processors (APs) is growing thanks to new Artificial Intelligence (AI) applications like AR/VR, embedded vision, speech processing, 3D image reconstruction, pedestrian detection, and gesture recognition, all of which require deep learning algorithms. APs must be highly flexible and configurable to implement the newest and most efficient algorithms. This mandates having a power solution that adapts and delivers to the dynamic system needs while maintaining low power consumption and maximizing run time. 

In this webinar, Gaurav Mital and Stan Bochenek discuss the challenges of powering APs in AI applications and provide a PMIC example which is best-in-class for size and efficiency. During the webinar a demo featuring NVidia's Jetson™ platform, shows how a computationally-intensive object recognition platform can be powered by Maxim’s high-performance PMIC solution. Learn how to drive your highest energy power needs efficiently for the next wave of AI applications.

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Speaker: Gaurav Mital
Gaurav is the power architect for high performance, computation-intensive PMICs for AI/machine learning platforms and low-power PMIC product line for wearables and hearables platforms at Maxim Integrated. He started his career as an analog power design engineer and has worked in the semiconductor industry for over 15 years on a wide range of mobile power products. He has an M.S. degree in EEE from California State University.
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