As AI agents grow more capable, the question of trust becomes increasingly critical, especially in complex engineering environments like semiconductor and PCB design. Siemens EDA and NVIDIA are tackling that challenge head-on, combining deep EDA domain expertise with cutting-edge AI infrastructure to deliver a new generation of agentic AI capabilities for engineering teams.

In this episode, we sit down with Amit Gupta, Chief AI Strategy Officer at Siemens EDA, and Tim Costa, VP and GM of Industrial and Computational Engineering at NVIDIA, to explore how their collaboration is shaping the future of EDA workflows. Together, they discuss domain-scoped AI agents that don't just execute tasks but verify their own outputs using physics-based EDA software validation, purpose-built to support the demands of long-running engineering workflows.

We dig into what self-verifying agentic AI actually means in practice, what the Siemens and NVIDIA collaboration looks like under the hood, and what it delivers in terms of tool-calling reliability, token efficiency, result quality, and time-to-results for engineering teams working across the full EDA lifecycle.

In this month’s Brains and Machines podcast, Dr. Jeff Shainline talks  about superconducting neural hardware with Dr. Sunny Bains of University College London. Currently in development at Great Sky in Boulder, Colorado, the new systems will incorporate photonic interconnects and a neuromorphic approach to intelligence. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

Some of the most critical semiconductor innovation today sits beneath intelligent systems, where data moves, connects, and scales. As architectures become more distributed, sensor-rich, and AI-driven, challenges in bandwidth, latency, power, and interoperability intensify. In this episode, we unpack the interface technologies driving this evolution: from automotive SerDes to advanced imaging and next-gen connectivity.

In this latest episode of Brains and Machines, Dr. Patty Stabile of the Eindhoven University of Technology chats with us about  her optical neural networks with ultra-low-latency processing, and the semiconductor optical amplifiers that make them possible. 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 of EE Times Current, we’ll dive into Physical AI — from humanoids and embodied agents to the chips, sensors, and systems that let machines see, move, and interact with us. Guiding us through this future of silicon is our host, Hezi Saar, Executive Director of Product Marketing at Synopsys. Hezi brings a front-row view of the semiconductor and AI landscape — and the people building it.

With advanced safety features, sophisticated sensors, and personalized temperature controls, software-defined vehicles require more power than ever before. Traditional automotive power systems simply can’t keep up with the demand. As the industry moves toward the adoption of 48-volt technology, a zonal architecture will play a critical role in this transition. This podcast covers why auto industry is undergoing a big E/E transition and the zonal architecture fundamentals, covering 48V power architectures, zonal E/E architecture, software-defined vehicles (SDV), and how integrated solutions such as 48V e‑fuses enable this transition.

This latest episode of Brains and Machines features a panel discussion on neuromorphic engineering and physical computing held at the Atoms to Bits: The AlphaBet of Intelligence v2.0 conference at the University of Manchester, held in February 2026. The panelists were Dr. Damien Querlioz, Dr. Julian Büchel, Professor Tamalika Banerjee, Dr. Maxence Ernoult, and Professor Steve Furber, and the session was chaired by Dr. Sunny Bains of University College London. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

In the latest episode of Brains and Machines, Sally Ward-Foxton of EE Times talks to Dr. Sunny Bains of the University College London. They discuss the importance of power in all AI systems, the benefit of having dedicated inference chips, and where neuromorphic fits into the market. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

Challenges: power generates heat. Heat distorts wires and changes transistor behavior. A change in wires and transistors implies that initial power estimates were wrong.

More and more designers are moving to heterogeneous architectures. This comes with new challenges as compared to the 2D domain. Come learn how the Calibre team can help achieve successful 3D IC design goals.

In this latest episode of Brains and Machines, Professor Rodolphe Sepulchre, a control theorist from the University of Cambridge, talks to Dr. Sunny Bains of University College London. They discuss the inspiration he took from studying biological neurons, why both discrete and continuous behaviors are inherent to how they work, and why building neurons is often easier than simulating them.