Blog Review: Apr. 29


Synopsys' Madhumita Sanyal shows why interface IP has emerged as the keystone for building scalable, reliable 3D multi-die designs in which interconnects often have a greater influence on overall system capability than the peak performance of individual dies. Cadence's Frank Ferro checks out why SOCAMM2 built on LPDDR is being deployed in AI data centers, increasing memory bandwidth and capa... » read more

Can Edge AI Keep Up?


Key Takeaways: Model development is outpacing silicon design cycles, so edge AI architectures must prioritize adaptability. The required cadence for model updates is highly application-dependent and is closely tied to product lifetime and operational risk. Adaptability can conflict with power, performance, and area targets, so effective heterogeneous architectures and robust softwa... » read more

Blog Review: Apr. 22


In a podcast, Siemens EDA's Harry Foster and Vladislav Palfy chat about why coverage closure has become one of the biggest bottlenecks in modern verification and how a unified approach that combines planning, automation, and analytics helps teams break through coverage plateaus. Synopsys' Emily Gerken and Marc Swinnen consider the challenges of designing analog and mixed-signal circuits at a... » read more

Chip Industry Week In Review


Acquisitions and business pivots Teradyne acquired Israel-based TestInsight, a semiconductor test provider with pattern conversion, validation, and virtual test capabilities. Credo plans to acquire DustPhotonics, a developer of silicon photonics PICs for optical transceivers. Molex plans to acquire Teramount, a provider of detachable, passive-alignment fiber-to-chip connectivity solu... » read more

Why More CPUs Are Needed For Agentic AI


The shift from generative AI to agentic AI will significantly increase the amount of compute power needed in data centers. Queries to search for and analyze data from multiple sources will be performed simultaneously by agents and without human intervention, rather than a single request from a live person. Jeff Defilippi, senior director of product management at Arm, talks about the impact of r... » read more

Blog Review: Apr. 15


Cadence's Wilson Kobalkar shares why eUSB2‑V2 represents a major evolutionary step for the USB 2.0 ecosystem, including how it achieves multi‑gigabit HSx operation and why symmetric/asymmetric modes unlock new design possibilities. Synopsys' Akanksha Soni explains the difference between metal-oxide-metal, metal-insulator-metal, and metal-oxide-semiconductor capacitors, identifying the ad... » read more

Startup Funding: Q1 2026


The new year started off with a bang for private semiconductor companies, with 18 garnering mega funding rounds exceeding $100 million, and two, Rapidus and Cerebras, reaching the $1 billion mark. Predictably, the vast majority of those are either designing chips primarily for AI inference workloads or attempting to overcome bandwidth limitations by improving interconnects from the chip level t... » read more

A New Era For Co-Processing


Key Takeaways: There is no single processor capable of executing everything efficiently, meaning that multiple processors are required. Maximum efficiency is gained by minimizing the movement of data. Architects must maximize efficiency for today's workloads, while also adding enough flexibility to handle tomorrow's. New processor architectures are rapidly evolving thanks to... » read more

Rethinking Robotics Reinforcement Learning: A Practical Humanoid Training Workflow


Reinforcement learning (RL) for robotics is often associated with large GPU clusters, distributed infrastructure, and x86-based development environments. Training a humanoid robot with high-fidelity simulation is a resource-intensive workflow that runs in the data center. What if that workflow could run on a single workstation? In this blog post, we explore a complete robotics pipeline bu... » read more

Fast Isn’t Fast Enough: Redefining Metrics for Edge AI


Key Takeaways: Edge AI performance is about low latency and power efficiency, not peak TOPS. Memory bandwidth and data movement now limit edge AI more than compute. Successful edge AI requires balanced hardware, software, and fast model updates. Experts At The Table: Today’s chip architect must contend with multiple factors when architecting AI processors for fast and effi... » read more

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