category: Top Stories

category: Auto, Security & Edge AI

Smart Test Collides With The Data Chain
By Gregory Haley - 12 May, 2026 - Comments: 0

Key Takeaways: The promise of smart test is a data-chain problem before it is an algorithm problem. A device can pass every checkpoint and still carry a latent defect the test record never captured. As test grows more adaptive, the validity of the measurement environment matters as much as the measurement itself. For years, the test roadmap has pointed toward more adaptive f... » read more

HBM Shifts Testing Left To Preserve AI Chip Yield
By Anne Meixner - 12 May, 2026 - Comments: 1

Key Takeaways: A high-yield, known-good stack requires multiple test insertions. Known good stack testing poses challenges for power delivery and thermal management. The shift to HBM4 and HBM5 will increase the pressure for shift-left test flows. Taller high-bandwidth memory (HBM) stacks and tighter TSV pitch are impacting AI module yields. The solution is to push test furth... » read more

Building AI Without Guardrails
By Ann Mutschler - 07 May, 2026 - Comments: 0

Key Takeaways: AI governance is broadly recognized as essential, but today it remains fragmented, largely aspirational, and lacking enforceable mechanisms for accountability, runtime assurance, and global interoperability. Because AI innovation is advancing too quickly for governments or standards bodies to keep pace, practical AI governance is most likely to emerge first from high‑ri... » read more

Humanoid Touch And Voice Are Improving Rapidly
By Liz Allan - 07 May, 2026 - Comments: 0

Key Takeaways Humanoid robots are rapidly expanding beyond factories and logistics toward broader, general-purpose roles (including in-home assistance), driven by advances in AI and sensing. Compared with vision and language, touch (haptics) and hearing/voice in real environments remain the hardest — and most commercially important — sensing challenges, requiring fast sensor fusio... » read more

Next-Gen Batteries Require Impedance Data And Active Balancing
By Liz Allan - 07 May, 2026 - Comments: 0

Key Takeaways Electric vehicles and energy storage systems using LFP batteries require more sophisticated diagnostic methods because they exhibit very flat cell voltages across various charge levels, making it harder to estimate usable energy. Battery management systems are leveraging new components, AI/ML, digital twins, and other techniques to get more accurate, real-time data, includ... » read more

Using AI To Monitor Dashboards In Chips And Systems
By Ed Sperling - 06 May, 2026 - Comments: 0

Key Takeaways: New types of dashboards are being used in conjunction with AI to make sense of large quantities of data. These dashboards can be used to quickly identify and fix power and heat-related problems, such as hotspots or voltage droop. Future dashboards will likely be much more customizable for different users or applications. Chipmakers are starting to use AI to ma... » read more

Designing Chips In The Context Of Rapidly Evolving AI
By Ann Mutschler - 04 May, 2026 - Comments: 0

Key Takeaways: Agentic edge AI drives long-lived, tool-mediated loops with variable demands for compute, tokens, and memory. Edge PPA is dominated by memory hierarchy and data movement, forcing tight feature triage and robust RAS. Rapid model churn (multimodal, MoE, new formats) requires programmable, headroom-rich compute, interconnect, and runtime. Experts At The Table: Ch... » read more

Creating Agentic EDA Methodologies
By Brian Bailey - 30 Apr, 2026 - Comments: 1

Key takeaways Agentic methodologies need to be able to reason across multiple data formats and abstractions. It is not clear how much data from previous designs is useful in new designs. Standards may help, but the lack of them may only impact cost. The relationship between tools and methodologies is bidirectional. Tools enable methodologies, and methodologies are dependent ... » read more

Foundry Capacity Is Limiting Who Competes At Leading Edge Nodes
By Ann Mutschler - 30 Apr, 2026 - Comments: 0

Key Takeaways: Leading-edge node access is increasingly reserved for hyperscalers, squeezing smaller chip developers. Chiplets and advanced packaging offer a path forward, but raise cost, complexity, and risk — especially for smaller teams. Chip architecture is now driven as much by capacity, yield, and economics as by technical goals. The benefits of device scaling are sl... » read more

NoC Coherency Challenges Balloon With AI SoCs And Chiplets
By Liz Allan - 30 Apr, 2026 - Comments: 0

Key Takeaways Data movement, congestion, and energy efficiency are key determiners of whether compute is usable. Different processors bring various coherency challenges. For example, a cache-coherent NoC for CPUs is expensive and harder to verify than an I/O-coherent NoC for an accelerator. Designers need to balance top-down performance with bottom-up physical engineering to effect... » read more

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