Mobilint has begun mass production of next-generation edge AI chips that incorporate video codec technology from Chips&Media, the companies announced on November 4. The South Korean partners are targeting robotics applications, including humanoids, where several cameras can generate more video than a system can easily… Read More
Artificial Intelligence
Three-Dimensional Chess Anyone? The Challenges of Power Integrity for Multi-Die Designs
Power integrity has been a substantial design challenge for a long time. In the multi-die era, the problems associated with EMIR analysis must now move beyond the chip to consider interactions across the entire stack. The effects to be analyzed span a multi-dimensional, multi-material space. The graphic at the top of this post… Read More
The $725 Million Chip Development: Why Execution Risk, Not IP Cost, Now Dictates Advanced-Node Survival
The philosophy of relying on a single, unified IP stack to lower your total cost of ownership is not a new concept invented just for the AI era. Semiconductor engineering teams have been weighing the trade-offs of piecemeal versus integrated intellectual property sourcing for decades. In previous process generations, veering… Read More
CTO Interview with Taylor Barton of Certus Semiconductor
Taylor Barton is a Lead Analog/Mixed-Signal and I/O IC Design Engineer at Certus Semiconductor, where he has worked since December 2022. He has designed more than 20 silicon-proven I/O and ESD libraries and has led analog and I/O IP projects, including ADC and SerDes designs. Taylor holds B.S. and M.S. degrees in Electrical Engineering… Read More
Ceva’s next NeuPro generation opens new possibilities across AI
Ceva is broadening the possibilities for AI silicon with a new generation of its NeuPro neural processing unit portfolio, bringing a common architecture and unified software environment to applications spanning sensors, intelligent devices and cloud infrastructure.
Announced on October 28, the portfolio reflects an opportunity:… Read More
ML-Based Power Models for CPUs. Innovation in Verification
An effective learned power model for a CPU could be a significant advantage in early estimation of power performance against realistic workloads in complex architectures. Paul Cunningham (GM, Verification at Cadence), Raúl Camposano (Silicon Catalyst, entrepreneur, former Synopsys CTO and lecturer at Stanford, EE292A)… Read More
CEO Interview with Lisa Spelman of Cornelis
Lisa Spelman is CEO of Cornelis, where she leads the company’s efforts to advance high-performance networking for AI and HPC infrastructure. She brings more than 20 years of experience across AI, cloud, enterprise infrastructure, data center operations, product strategy, and go-to-market leadership.
Before joining Cornelis,… Read More
From Sequential R&D to Trusted Co-Innovation: The EPIC Model for Semiconductor Innovation
The semiconductor industry has long depended on collaboration between technology developers, equipment suppliers and manufacturers. But as artificial intelligence reshapes computing, established ways of working together may no longer be sufficient. The next wave of innovation will depend not just on what companies develop,… Read More
SEMICON West’s Autonomous Fab Vision Needs a Decision-Escalation Design
By Gleb Tsipursky
SEMICON West 2026’s smart-manufacturing agenda connected digital twins, agentic AI, physical AI, and increasingly autonomous factory operations. The final day included a session on automation and equipment for autonomous facilities. At its October CONNECT conference, PDF Solutions planned demonstrations… Read More
Arteris FlexGen Opens Up Multi-Die Traffic Management for Non-Coherent Networks
Last year I wrote about Arteris’ introduction of multi-die support for coherent NoCs. This is a very big deal because hyperscalers and OEMs are now building large systems that depend on multi-chiplet architectures and require efficient traffic management between chiplets, in one case as many as 12 compute, fabric/cache and … Read More


The $725 Million Chip Development: Why Execution Risk, Not IP Cost, Now Dictates Advanced-Node Survival