Senior Vice President, GM of Intelligent Sensing Division & Chief Strategy Officer, Synaptics
Search every verified Satish Ganesan interview, podcast appearance, and on-the-record quote — each transcript cross-checked by AI and human review to confirm speaker identity. At CES 2025, Satish Ganesan discussed Synaptics’ focus on integrating artificial intelligence into its sensing, processing, and connectivity technologies. He stated that the company is “pushing AI to the edge of sensing technologies” and embedding AI-native solutions to enhance user experience with low memory and processing requirements. Ganesan noted that Synaptics’ history in fingerprint and biometric technology originated from AI neural networks, and the company is now innovating to run AI and machine learning on embedded processors for use cases such as palm-versus-finger detection on touchpads. In automotive, he said the company is adding intelligence to touch sensors using small machine learning algorithms for driver detection, glove detection, and moisture detection. Ganesan also highlighted that Synaptics is providing AI technologies to help customers in PCs and automotive differentiate their products, as processors come from various suppliers. He mentioned that user presence detection and security solutions are already shipping in some laptops, using a small processor near the camera sensor to detect user gaze and turn off the monitor to save battery. Looking ahead, Ganesan said Synaptics will focus on infusing AI into all its ecosystems over the next 12 months, aiming to become the primary processor and improve user experience across PCs, automotive, and other markets.
“We are focusing on pushing AI to the edge of sensing technologies, embedding AI native solutions and connectivity solutions to enhance user experience with very low memory and processing power requirements.”
“Our history of fingerprint and biometric technology started from an AI neural network, and now we are innovating to run AI and machine learning on embedded processors with very limited memory and processing power to enhance simple use cases.”
“In automotive, we are adding intelligence to touch sensor capabilities using small machine learning algorithms for driver detection, glove detection, and moisture detection to improve safety and security.”
“We are innovating to run AI algorithms on low memory and low compute environments, such as touchpads, to detect palm versus finger and improve user experience by resolving common issues with AI.”
On the first day of CES 2025, EE Times had the chance to catch up with Satish Ganesan, senior VP and general manager of the ...
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