Today, we’re diving into the fascinating world of edge AI, exploring its rapid evolution and its transformative impact on industries like automotive. With advancements in model efficiency and hardware capabilities, edge AI is reshaping design requirements for devices, particularly in balancing the critical factors of power, performance, and cost. Let’s set the stage and delve into how these trends are driving innovation at the edge.

Neuronova is an analog neuromorphic startup based in Milan, Italy. In this episode of Brains and Machines, the CEO and CTO talk to Dr. Sunny Bains of University College London about their inference processor that idles at less than 10 nanowatts and what they hope to do with it. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

Professor Chris Eliasmith is a computer scientist and philosopher who’s been modelling cognitive systems for almost three decades. In this episode of Brains and Machines, he talks to Dr. Sunny Bains of University College London about his neural engineering framework and the semantic pointer architecture his team have developed to implement it. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

Dive into the evolving world of asset tracking and locationing with Renesas!

Explore what ‘locationing’ really means in the evolving space of asset management, how to leverage the various cutting-edge Renesas locationing technologies to gain visibility and control over your assets, and how Renesas as a field-proven leader within this technology space can empower you and your customers to move from simple tracking to intelligent, real-time locationing. 

In this episode, we look at the changing landscape of multi-die design, highlighting how the industry is addressing current challenges and opportunities. We share customer perspectives on essential requirements, including design considerations, scalability, performance and integration, while outlining the current state of multi-die design and the elements shaping future developments. Discover how companies are responding to these demands and gain insights into the future of multi-die design.

Dr. Claudia Lenk’s group creates brain-inspired hearing systems with micromechanical hair cells. In this episode of Brains and Machines, she talks to Dr. Sunny Bains of University College London about the advantages of the approach and how it could be applied to speech processing in AI. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

In this episode, we’ll explore Siemens EDA’s innovative approach to AI and dive into Calibre-specific topics. We’ll discuss when to use Calibre, when it might not be the best fit, and how to leverage it to maximize productivity and designer effectiveness—all without compromising on quality.

AI is everywhere these days, from space exploration to dating apps, and Siemens has been a pioneer in this space, investing in AI long before it became a trend. So, let’s dive in and explore how Siemens EDA is shaping the future of design with AI.

Brad Aimone from Sandia National Labs works with the world’s biggest neuromorphic platforms. In this episode of Brains and Machines, he talks to Sunny Bains of University College London about how this allows him to think deeply about what they’re good for. Discussion follows with Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

Professor Barbara Webb from the University of Edinburgh in Scotland​ uses physical robots to validate neural mechanisms in crickets, ants, and bees. In this episode of Brains and Machines, she talks to Dr. Sunny Bains of University College London about her work. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

Today we’re talking about something that’s top-of-mind for a lot of you: closing the reliability gaps in increasingly complex analog and mixed-signal IC designs—and doing it earlier, faster, and more systematically.

As designs become more heterogeneous and integration of IP blocks more intricate, traditional simulation and ERC tools often aren’t enough. They’re reactive by nature, catching issues too late in the flow—when rework is costly, and design intent is harder to trace.

That’s why “shift-left” verification has become more than just a buzzword. It’s a strategic necessity. And today’s conversation is all about one of the tools helping to make that shift actionable: Siemens’ Insight Analyzer.