category: Round Tables

category: Auto, Security & Edge AI

AI In Chip Design: Lots Of Promise, Plenty Of Unanswered Questions
By Ed Sperling - 15 Jul, 2026 - Comments: 0

Key Takeaways: AI opens the door to exploring a much larger solution space, similar to what high-level synthesis did years ago, but questions persist about the impact of increasing reliance on what is essentially a black-box chip design. There is no consistent answer to how successful AI will be, where it will succeed or fail, or how it will apply to different markets and EDA customers.... » read more

Observability Is A Missing Layer In AI-Era Chiplet Design
By Ann Mutschler - 01 Jul, 2026 - Comments: 0

Key Takeaways: In chiplet-based architectures, observability must be designed as a fabric-aligned, cross-die telemetry plane so architects can correlate traffic, latency, congestion, and fault behavior across package boundaries without losing system context. AI can extract value from high-volume silicon telemetry only when the architecture provides consistent instrumentation, near-senso... » read more

Executive Outlook: Agentic AI’s Impact On Chip Design
By Ed Sperling - 25 Jun, 2026 - Comments: 1

Key Takeaways: Agentic AI has the potential to make engineers more productive, speed time to market, and automate some of the drudge work. The big challenge for design and verification engineers is where and whether they trust AI to get everything right, because there is no margin for error in semiconductors. Having humans in the loop will likely be the rule rather than the exception... » read more

Mask Economics Shape High-NA EUV Adoption
By Gregory Haley - 22 Jun, 2026 - Comments: 1

Key Takeaways: Mask costs are not stopping leading-edge scaling, but they increasingly influence design, node, and process choices. High-NA EUV will tighten requirements for CD, EPE, local CDU, mask 3D modeling, stitching, and materials. Reduced depth of focus in High-NA EUV will drive new resist, etch, film, and absorber approaches. Experts at the table: Semiconductor Engin... » read more

Designing Chips That Can Explain Themselves
By Ann Mutschler - 17 Jun, 2026 - Comments: 1

Key Takeaways: On-die telemetry gives architects a path to replace worst-case design margin with measured silicon behavior, improving PPA without compromising resilience. As monitor density and control-loop speed increase, observability must be architected hierarchically across local hardware response, on-die processing, and fleet-level learning. The real payoff is architectural: str... » read more

Observability Is Essential For Modern Silicon
By Ann Mutschler - 28 May, 2026 - Comments: 0

Experts At The Table: In-silicon observability — also known as on-die or on-chip visibility — is becoming increasingly important for managing the performance, reliability, and security of today’s high-performance systems. Semiconductor Engineering sat down to discuss this with Andy Nightingale, vice president of product management and marketing at Arteris; Nandan Nayampally, chief commerc... » read more

Curvilinear Masks Push The Limits Of Inspection And Metrology
By Gregory Haley - 27 May, 2026 - Comments: 0

Key Takeaways: Curvilinear masks require native data flows across design, mask data prep, writing, inspection, and metrology. Inspection is shifting from finding all defects to identifying which mask variations actually print on wafer. High-NA EUV will intensify inspection challenges, particularly for small printable defects and actinic contrast limits. Experts at the table... » read more

Mask Technology Faces A New Set Of Challenges
By Gregory Haley - 21 May, 2026 - Comments: 0

Key Takeaways: Mask inspection and repair remain the critical bottleneck, even as multi-beam writers have reduced mask-writing constraints. Curvilinear masks are becoming viable for critical layers, but qualification, metrology, and inspection standards still lag production needs. Scaling curvilinear requires curvilinear-native data flows, model-based checks, GPU/HPC compute, and les... » 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

Can Edge AI Keep Up?
By Ann Mutschler - 23 Apr, 2026 - Comments: 0

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

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