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
Artificial Intelligence
The Industry Challenge: AI Is Forcing Semiconductor Innovation Beyond the Chip
Applied Materials President and CEO Gary Dickerson with the EPIC Center founding partners on October 12, 2026, in Sunnyvale, CA. (Tomas Ovalle/AP Content Services for Applied Materials, Inc.)The bottlenecks are becoming interconnected
Artificial intelligence is changing what the semiconductor industry must deliver. … Read More
Who Gets to Move the Recipe? How Autonomous Agents Earn Decision Authority in the Fab
by Ajay Kumar Govindaram
There’s a question I’ve started asking at every agentic AI demo I sit through, and it has a clean answer in every fab on earth: who is allowed to change the recipe? In a semiconductor factory, that was settled decades ago. A person doesn’t touch a production recipe because they feel confident.… Read More
Moving Beyond AI-Assisted Design – Agentrys Shows the Way with Agentic Loop Engineering
At Hot Chips 2026, OpenAI presented Jalapeño, an inference ASIC built with AI in the design loop. As reported from the session by ServeTheHome and Tom’s Hardware, OpenAI showed measured block-level wins over a human baseline — 56% on a BF16 multiply, alongside a 10% smaller matrix-unit area — within a roughly nine-month path from… Read More
Why Semiconductor AI Starts with Data, Not Algorithms
The next gains from AI in semiconductors will come less from models and more from making fab and test data reliable, connected and tied to engineering decisions.
By Sriram Nithin Gopal Lanka
Every few months there is a new AI model that can do more and semiconductor manufacturers are under pressure to put them to work. But ask the engineers… Read More
Why AI Security Starts at the Chip Level
Artificial intelligence is becoming part of the infrastructure that powers healthcare, transportation, finance, manufacturing, and everyday digital services. As these systems grow more capable, they also process more sensitive information and depend on increasingly complex hardware. The Synopsys white paper, “Securing… Read More
Delivering Silicon Systems Through AI Disruption, Part 1: Writing the Score
Score: the written music for an orchestra, with every section’s part laid out on the same page so they play together. In this article, it’s your designed workflows.
Is AI helping you hit your tape-out date, or putting it at risk? How would you know?
Every Director I talk to is being asked to use AI to deliver faster, or better,… Read More
Intel’s Open Software Blueprint: Why Production AI Needs More Than GPUs
Intel’s strategic argument about enterprise AI is that the value of a model depends on the system that surrounds it. In an article by executives Bill Pearson and Anil Nanduri, the company positions open software as the connective tissue linking CPUs, GPUs, data, and business applications. The message is straightforward: accelerator… Read More
Overcoming the Edge AI Power Wall with Low-Voltage Foundation IP
As artificial intelligence (AI) workloads migrate to endpoint hardware, edge AI devices face immense pressure to deliver real-time inference within highly restrictive power and thermal envelopes. Traditional silicon scaling no longer yields the power-density returns it once did. To compensate, engineering teams are turning… Read More
ChipAgents and NVIDIA Put Autonomous Chip Design to the Test
ChipAgents has introduced Build-A-Chip-Bench, a benchmark developed with NVIDIA to evaluate whether AI agents can complete digital chip design tasks from specification through physical implementation. The initiative measures progress beyond generating hardware code, asking whether autonomous systems can deliver verified… Read More


Smoothing the Quantum Path: ASML and Xanadu Target Photon Loss