Embedded Executive: Partnerships Can Simplify Complex AI Designs, with Renesas and EdgeCortix
Apr 3, 2024
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Vice President of Renesas Electronics and CEO of EdgeCortix discuss simplifying AI designs through partnerships. Topics include leveraging hardware architectures, optimizing AI models for fault detection, and streamlining AI designs for software engineers. They also explore the efficiency and applications of Gen.A.I at the edge.
Partnerships address complexities in AI design through integrating diverse hardware architectures.
Generative AI models promise efficient and robust applications, enhancing functionality in various industries.
Deep dives
The Evolution of Heterogeneous Architectures in AI
Heterogeneous computing architectures, particularly in AI, have seen significant growth to meet the demand for higher computing power and efficiency. Companies like Renaissance Electronics are integrating diverse nodes like CPUs, NPUs, and AI accelerators to handle complex workloads. This evolution poses challenges for developers who must navigate varied hardware architectures. Partnerships with companies like Edge Cortex aim to provide seamless solutions that address complexity and streamline AI development processes.
Understanding Generative AI and Its Applications
Generative AI represents a shift from traditional single-modality applications to more holistic and information-abstraction models. These models can generate language, vision, and multi-model applications efficiently. By requiring less training data and being robust in different environments, generative AI holds promise for diverse applications like people detection and industrial use cases. Companies like Edge Cortex and Renaissance Electronics focus on enabling developers to harness the power of generative AI for enhanced functionality.
Challenges and Solutions in AI Software Development
Developers face challenges in balancing performance, energy efficiency, and reliability when deploying AI solutions. The need for software portability and scalability across platforms further complicates AI development. Tools like quantization and unified programming models help manage the diversity of processing elements and precision levels. Collaborations between companies like Edge Cortex and Renaissance Electronics aim to simplify software complexities, especially in heterogeneous computing environments, for efficient AI development and deployment.
In a rare move, I had two guests join me for this week’s Embedded Executives podcast, but for a good reason. I was joined by Mohammed Dogar, Vice President and Head of Global Business Development and Ecosystem at Renesas Electronics, and Sakya Dasgupta, Founder and CEO of EdgeCortix.
I asked them to join me together because they have partnered on some interesting Edge AI technologies. We walked through the Renesas vision and strategy for AI and machine learning (ML) and how that led to the partnership with EdgeCortix. More importantly, we discussed what that means to the design engineer and the embedded community at large.
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