EE Times Current

IMChip’s founders say interface memristors are more reliable and scalable than filamentary ones. The Groningen spin-out grows the devices at high temperature, then transfers them onto silicon. In this month’s Brains and Machines, Sunny Bains talks with Tamalika Banerjee, chief scientific officer, and Ruben Hamming-Green, head of R&D, about their plan for an edge-AI prototype chip within two years. Giulia D’Angelo of the Czech Technical University in Prague and Ralph Etienne-Cummings of Johns Hopkins University join the discussion.

IMChip’s founders say interface memristors are more reliable and scalable than filamentary ones. The Groningen spin-out grows the devices at high temperature, then transfers them onto silicon. In this month’s Brains and Machines, Sunny Bains talks with Tamalika Banerjee, chief scientific officer, and Ruben Hamming-Green, head of R&D, about their plan for an edge-AI prototype chip within two years. Giulia D’Angelo of the Czech Technical University in Prague and Ralph Etienne-Cummings of Johns Hopkins University join the discussion.

As AI-driven SoCs move to advanced process nodes, design complexity, development cost, and execution risk are rising sharply. In this episode, Synopsys Executive Director of Product Management Ravi Todi explains why competitive power, performance, and area (PPA) are no longer sufficient on their own. Success in the AI era also depends on predictable execution and disciplined management of total cost of ownership (TCO) across the full SoC lifecycle.

The discussion highlights how a holistic, silicon-proven Foundation IP platform—delivered as an integrated solution from a single trusted partner—can help reduce risk early, minimize integration issues and re-s...

In this podcast, EE Times' Sally Ward-Foxton talks to Majestic Labs’ Sha Rabii about why AI's shift toward inference, long context, and agentic workloads could require a fundamentally different compute-memory architecture.

In this month's Brains and Machines, Dr. Ryad Benosman discusses event-based vision, retinal prosthetics, and neuromorphic startups with Dr. Sunny Bains of University College London. A co-founder of Prophesee, he explains why he believes AI's future must come from neuromorphic engineering. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University. 

As systems become more software-defined, the traditional development model of waiting for hardware before serious software validation begins is no longer sustainable. Software teams need platforms earlier. Hardware teams need realistic workloads sooner. Verification teams need better ways to expose system-level issues before tapeout. We will look at how digital twins are becoming the shared foundation for this new HW/SW co-development model. Using virtual platforms, hardware emulation, and FPGA prototyping, teams can start earlier, collaborate more closely, and design/optimize/validate with greater confidence. We will also discuss new system-level verification challenges in power, performance, and DFT, showing...

Artificial intelligence is accelerating semiconductor development, but more compute, more automation, and more engineering data do not automatically create better decisions. As design and manufacturing workflows become increasingly AI-enabled, a new constraint is emerging: trust. In this episode, Dr. Jim Shiely builds on themes from his Patterning the Singularity leadership work to explore the semiconductor industry’s “trust bottleneck” and why trustworthy engineering intelligence is becoming essential to future innovation.

On this month's episode of Brains and Machines, five engineers debate neuromorphic sensing and learning. Recorded at the Neuromorphic Hardware and Algorithms conference at the University of Sussex, the panel explores whether events and spikes are the right framework for integrating sensor modalities, motor control, and learning across systems. They also examine commercial directions and revisit the perennial question: what is neuromorphic engineering?

The panelists are:

For years, AI infrastructure was measured at the scale of the data center. That's changed. In this episode, Neeraj Paliwal explains why the rack has become the indivisible unit of a modern AI system — designed as one system rather than a collection of servers — and why performance is no longer defined by the compute in any single box, but by how efficiently data moves, is stored, and is secured across the entire rack.

 And getting there depends on co-designing the silicon, memory, interconnect, and packaging together, with the IP foundation turning concentrated power into usable compute.

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, t...

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. 

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 conversa...

Professor Gert Cauwenberghs has been working toward building brain-scale systems for decades. At the University of California San Diego, he’s now one of the leaders of the Neuromorphic Commons hub, also known as Thor, which will give the wider community access to neuromorphic hardware and simulators. In this episode of Brains and Machines, he talks to Dr. Sunny Bains of University College London about his approach to making systems that use minimal energy, are highly interconnected at all levels, and are surprisingly flexible. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Prof...

Professor Gordon Cheng builds humanoid robots that can feel their environment using artificial skin. In this episode of Brains and Machines, he talks to Dr. Sunny Bains of University College London about how the skin was designed, how it improves safety and why neuromorphic engineering will be important for machine autonomy. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

Professor Gordon Cheng builds humanoid robots that can feel their environment using artificial skin. In this episode of Brains and Machines, he talks to Dr. Sunny Bains of University College London about how the skin was designed, how it improves safety, and why neuromorphic engineering will be important for machine autonomy. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

Dr. Charlotte Frenkel from the Technical University of Delft set records with a low-power neuromorphic chip she designed as part of her Ph.D. In this episode of Brains and Machines, she talks to Dr. Sunny Bains of University College London about what she has learned about building simplicity into chips and integrity into benchmarks. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University.

The semiconductor industry is undergoing a shift with the rapid adoption of multi-die design, driven by the promise of improved power, performance, and area (PPA). But with innovation comes complexity, and one of the biggest challenges is ensuring silicon reliability and health through effective multi-die testing.

In this episode, we dive deep into the world of multi-die design for test: what it means, how it differs from traditional monolithic design testing, and why it’s critical for the future of semiconductor manufacturing. Learn how testing spans from individual dies to multiple dies to die-to-die links, and why si...

Dharmendra Modha’s TrueNorth chip added the word neuromorphic to the technorati lexicon back in 2014. In this episode of Brains and Machines, he talks to Sunny Bains of University College London about how that project led to his work on NorthPole and the axiomatic approach he took to design. 

In this episode of Brains and Machines, Dr. Terry Sejnowski talks to Dr. Sunny Bains of the University College London about how information flows both ways between neuroscience and engineered intelligence, proposes a new way of looking at memory and considers the Hopfield-Hinton Nobel Prize. 

Dr. Jennifer Hasler of Georgia Tech is best known for her work with field programmable analog arrays (FPAAs). In this episode of Brains and Machines, she talks about the importance of, and progress in, analog electronics for AI with Dr. Sunny Bains of the 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.

Dr. Tony Lewis, CTO of BrainChip, and four other key scientists talk to Dr. Sunny Bains of University College London. They discuss their business strategy, their temporal event-based neural network (TENN) and the next iteration of the Akida chip. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Prof. Ralph Etienne-Cummings of Johns Hopkins University.

In this episode of Brains and Machines, emeritus Prof. Rodney Brooks of Massachusetts Institute of Technology, currently CTO of Robust AI, talks about bottom-up and top-down approaches to robotics and AI with Dr. Sunny Bains of University College London. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Prof Ralph Etienne-Cummings of Johns Hopkins University.

Many IC design teams struggle with tight deadlines and limited resources. The industry is constantly searching for new ways to improve efficiency without compromising design quality. While they might find tools that run incrementally faster, the real gains come from adjustments to the design flow – including what we call ‘shift-left’ strategies that pull signoff-quality verification into the design implementation stage. Join our host, Eric Singer, for a compelling interview with David Abercrombie, Product Management Director of Artificial Intelligence & Licensing Applications at Siemens EDA.