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In this episode of the Eye on AI podcast, Craig Smith sits down with Krishna Rangasayee, CEO of SiMa.ai, to explore the innovations in AI at the edge and how embedded systems are transforming industries like robotics, automotive, and industrial automation.
Krishna brings over 30 years of experience in software and silicon design, leading us through SiMa.ai's vision of disrupting edge computing with their Machine Learning System on Chip (MLSoC).
We dive deep into how SiMa.ai’s chips are designed to accelerate AI workloads at the edge, providing unmatched performance and efficiency compared to cloud-based solutions.
We also discuss the future of AI hardware, including the role of open-source platforms, the challenges of scaling AI in embedded systems, and why the edge market is poised to outgrow the cloud in the coming years.
Krishna shares his insights on the importance of AI software architecture, how SiMa.ai’s platform simplifies integration for developers, and the emerging potential of neuromorphic and quantum computing.
Join us as we delve into the next big AI gold rush, the edge market, and learn why AI-powered edge devices will reshape the way industries operate.
Don’t forget to like, subscribe, and hit the notification bell for more exclusive insights into the future of AI and edge computing!
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(00:00) Preview and Introduction
(02:13) SiMa.ai's Focus on Chip Design for the Edge
(05:38) How is SiMa.ai Different from NVIDIA’s CUDA?
(08:29) The Evolution of Chip Architecture
(11:50) AI’s Move to the Edge Market?
(19:19) Industries Driving Demand for SiMa.ai's Technology
(21:25) How Do Edge Applications Work?
(25:09) Chips Design for Edge Devices
(33:01) SiMa.ai Scaling Plans
(36:12) What is SiMa.ai Focusing On in the Future?
(40:30) SiMa.ai’s Fundraising Journey
(42:57) Hiring and Retaining Top Talent in the Industry
(46:01) The Future of Chip Technology
