EE Times Current provides a deep dive into the most compelling stories in the electronics industry. Tune in to keep yourself current on what matters to design engineers and other tech industry professionals
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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…
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…
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…
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…
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…
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…
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…
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…
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.
