Uploaded January 2026 | Updated September 2026, 2 weeks ago
In this interview with EE Times' senior India correspondent Yashasvini Razdan, Esam Elashmawi, chief strategy and marketing officer at Lattice Semiconductor, talks about how Lattice field programmable gate arrays (FPGAs) fit into the artificial intelligence (AI) landscape, from data centers to edge and far edge applications.
He shares practical examples around sensor fusion, low power artificial intelligence, security at the silicon level, and how programmability helps customers adapt to changing requirements. Esam also discusses post-quantum security, emerging applications such as robotics and humanoids, and Lattice’s growing work in India.
Watch the video here.
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In this interview with EE Times' senior India correspondent Yashasvini Razdan, Esam Elashmawi, chief strategy and marketing officer at Lattice Semiconductor, talks about how Lattice field programmable gate arrays (FPGAs) fit into the artificial intelligence (AI) landscape, from data centers to edge and far edge applications.
He shares practical examples around sensor fusion, low power artificial intelligence, security at the silicon level, and how programmability helps customers adapt to changing requirements. Esam also discusses post-quantum security, emerging applications such as robotics and humanoids, and Lattice’s growing work in India.
Watch the video here.
------
Also:
🎙 Listen to EE Times On Air podcasts on power, embedded, AI, and more: eetimes.com/podcasts/?utm_source=eetimes_youtube&utm_medium=social&utm_campaign=description
🎥 Don't miss an episode and subscribe to our YouTube channel: youtube.com/@eetimes747
Stay up to date with the latest news in the electronics industry
➡️ EE Times: eetimes.com/?utm_source=eetimes_youtube&utm_medium=social&utm_campaign=description
➡️ Power Electronics News: powerelectronicsnews.com/?utm_source=eetimes_youtube&utm_medium=social&utm_campaign=description
➡️ Embedded: embedded.com/?utm_source=eetimes_youtube&utm_medium=social&utm_campaign=description
➡️ EDN: edn.com/?utm_source=eetimes_youtube&utm_medium=social&utm_campaign=description
📰 Subscribe to our newsletters: aspencore.dragonforms.com/loading.do?omedasite=EventSubscription&pk=youtube
🖥️ Attend free tech webinars: eetimes.com/webinars/?utm_source=eetimes_youtube&utm_medium=social&utm_campaign=description
📈 Download free industry white papers: eetimes.com/techpapers/?utm_source=eetimes_youtube&utm_medium=social&utm_campaign=description
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![Distributed Intelligence Is Key to Scaling Physical AI
In this video interview, Rafael Sotomayor, President and CEO of NXP Semiconductors, explains why scaling physical AI is not just about building bigger brains, but about putting the right intelligence in the right place. He tells EE Times Executive Editor, Nitin Dahad, “If we are to scale physical AI for humanoids, we need to ask ourselves: how do we mimic the human body?”
In order to do this Sotomayor explains NXP’s view of the architecture required for this: the neural axis architecture. This is a distributed approach to placing the right level of intelligence of each layer needed for physical AI: the reasoning layer, the coordination layer, and the reflex layer.
Based on this, he said, “There’s a spectrum [of intelligence] that makes a humanoid useful.”
Watch the video interview with Rafael Sotomayor here to learn more about this concept and how it addresses the challenge of scaling physical AI.
#physicalAI #neuralaxisarchitecture #reasoninglayer #coordinationlayer
#reflexlayer Distributed Intelligence Is Key to Scaling Physical AI](https://i.ytimg.com/vi/_kvXsfMrgHo/mqdefault.jpg)

