Send us a text

Discover the cutting-edge world of TinyML and Edge AI with our special guest, Eldar Sido from Renesas. As a key figure in the AI Center of Excellence, Eldar unveils the fascinating challenges and breakthroughs in embedding AI into compact devices like microcontrollers and sensors that are rapidly spreading across the globe. This episode promises an exploration into the dynamic realm of TinyML, focusing on its three foundational pillars: real-time analytics, voice, and vision. Eldar discusses the anticipated double-digit growth of this sector over the next decade, making it a pivotal listen for tech enthusiasts and those curious about the future trajectory of AI technology.

Eldar also shares how Renesas, through its acquisition of Reality AI, is enhancing its prowess in real-time analytics and tackling high-frequency sampling rates. With a focus on consultancy, data selection, and sensor placement, Eldar illustrates how only a sliver of the TinyML process is devoted to model development. By integrating Reality AI with the E-Square Studio IDE, Renesas is streamlining workflows to maximize the potential of TinyML. Tune in to understand how TinyML is reshaping industries and what lies ahead for Edge AI applications. This episode is packed with insights and strategies for anyone looking to leverage the power of TinyML in their projects.

Support the show

Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org

Send us a text

Discover how the fusion of cutting-edge technology and human interaction is revolutionizing education and healthcare with Professor Stella Kuei-An Nguyen from National Yangming Chow Tung University. Join us as we explore her innovative work in Human-AI Interaction using Inertial Measurement Units (IMU), and witness the transition of Raboni IMU devices into the transformative Bony AI. Collaborating with giants like TSMC, MIT, and leading hospitals, Professor Nguyen showcases how these advancements are not only elevating coding education but also offering groundbreaking solutions for medical conditions such as Parkinson’s and dementia. These innovations are powered by tiny machine learning algorithms, seamlessly blending sensors and AI processors into user-friendly interfaces that redefine efficiency in educational and healthcare diagnostics.

Delve into the world of advanced motion monitoring technology as we delve into the integration of Rabonit, IMU, and the YSI2 AI processor, designed to intelligently track movements. This sophisticated system promises to revolutionize the way we assess physical activity, especially for children in intermediate playing stages. With a specially designed app that extracts and analyzes movement curves, this technology offers invaluable insights that could enhance both educational environments and healthcare sectors. Join us for an insightful journey into how these tools are set to make a broader impact, aiming to enrich lives by providing effective and efficient information.

Support the show

Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org

Send us a text

What do rising pedestrian fatalities and the challenges of implementing intelligent transportation systems have in common? In this episode, we’re joined by Davis Sawyer from NXP and Mike "Witt" Whitaker from the City of Lakewood, Colorado, to unpack the complexities of applying edge AI to enhance urban safety. As Witt recounts his pioneering work with autonomous vehicles since the 1990s, we explore the fast-paced evolution of AI technology and its critical role in addressing real-world problems, such as the increasing need for pedestrian safety and efficient traffic management.

We take a hard look at the perplexing trend of fatal crashes involving impaired drivers despite a drop in overall traffic incidents. The conversation intensifies as we discuss the doubling of pedestrian fatalities, particularly at night, and the significant challenges posed by underreported impairment and the rise of fentanyl use. Our guests share insights into how collaborations with the police department and meticulous data analysis can reveal hidden patterns, driving the development of more effective municipal safety strategies.

Our exploration doesn’t stop there. We also discuss the advancements in detection technologies and the iterative process of refining systems like LiDAR and video to predict pedestrian movements more accurately. This episode offers a deep dive into the complexities and costs of deploying AI models in urban environments, including the importance of ML Ops, the challenge of model retraining, and the role of existing infrastructure in supporting intelligent systems. Join us as we navigate the intricate world of smart city solutions, focusing on the shared goal of safer streets for everyone.

Support the show

Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org