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Jay Dawani is a visionary technologist and entrepreneur, currently serving as the Co-founder and CEO of Lemurian Labs. His work is centered on revolutionizing artificial intelligence by developing ultra-efficient, palm-sized AI supercomputers. Before co-founding Lemurian Labs, Jay made significant contributions as a Robotics Technologist at NASA's Jet Propulsion Laboratory (JPL), where he was involved in developing advanced robotics systems for space exploration. He holds a strong background in neuromorphic computing, AI, machine learning, and computer vision, often speaking about the future of AI hardware and its potential to solve complex global challenges. Jay is driven by the goal of making powerful AI accessible and sustainable.
Jay Dawani's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Co-founded and leads Lemurian Labs, a company pioneering the development of next-generation, energy-efficient AI hardware (LPU - Lemurian Processing Unit) designed to bring supercomputer-level AI capabilities to edge devices.
Spearheading the creation of compact, high-performance AI systems at Lemurian Labs, aiming to significantly reduce the power consumption and size of AI hardware.
Contributed to cutting-edge robotics projects and research at NASA's Jet Propulsion Laboratory, working on technologies for autonomous systems and space exploration.
A prominent voice and researcher in the field of neuromorphic computing and energy-efficient AI, pushing for new architectures that mimic the brain's efficiency.
Successfully led Lemurian Labs in securing significant seed funding (e.g., $9 million in 2023) to advance its innovative AI chip technology.
Western University - Year 2013
Karachi Grammar School - Year 2010
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Lemurian Labs is a fabless semiconductor company developing a novel, massively parallel, and ultra-low latency chip architecture specifically designed for Artificial Intelligence (AI) and Machine Learning (ML) workloads. Their goal is to accelerate AI computation significantly, enabling faster training and inference for complex models while improving energy efficiency. They focus on creating next-generation compute solutions to power the future of AI applications.
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