Gaurav Ghai is the Co-founder and CEO of Quadric, a company at the forefront of developing a new type of general-purpose neural processing unit (GPNPU) architecture designed for on-device AI and high-performance computing at the edge. With a robust background in the semiconductor industry, Gaurav has extensive experience in processor architecture, GPU design, and system-level solutions. Before co-founding Quadric, he held significant engineering and leadership roles at major semiconductor companies like NVIDIA and AMD, where he contributed to the development of cutting-edge graphics and processor technologies. He is passionate about making high-performance AI computation more accessible, efficient, and versatile for a wide range of applications, from autonomous systems to industrial IoT.
Gaurav Ghai's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Successfully co-founded Quadric and leads the company in its mission to revolutionize edge computing with its innovative GPNPU technology, attracting significant venture capital funding and guiding product development.
Instrumental in the conceptualization and development of Quadric's unique General-Purpose Neural Processing Unit (GPNPU), a novel processor architecture capable of handling both machine learning workloads and classical C++ algorithms on a single chip with high efficiency.
Spearheaded multiple successful funding rounds for Quadric, including a significant Series B, enabling the company to scale its operations, expand its team, and advance its technology in the competitive AI hardware market.
Held key technical and management positions at NVIDIA and AMD, contributing significantly to the architecture and design of industry-leading GPUs and processor technologies prior to founding Quadric.
Championing the development of powerful and flexible AI processing solutions specifically designed for edge devices, aiming to unlock new capabilities in real-time AI applications where low latency and power efficiency are critical.
Maharshi Dayanand University - Year 2016
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