category: Top Stories

category: Auto, Security & Edge AI

Tool Matching Getting Tougher Across Test & Metrology
By Laura Peters - 10 Mar, 2026 - Comments: 0

Key Takeaways Engineers leverage both device-specific and tool-level data to identify a process "sweet spot." Tight, frequent tool-to-tool matching enables greater yield and fab flexibility. Machine learning helps capture the nuances of a tool's signature. Many people outside of the semiconductor industry wonder how humans can fabricate transistors with tens of nanometer sca... » read more

Digital Twins: The Cloud’s The Limit
By Ed Sperling - 10 Mar, 2026 - Comments: 1

Key Takeaways Digital twins are gaining traction as a way of testing different options at every step of the design-through-manufacturing flow. AI can be used to glue together disparate data types in multi-physics simulations. The promise of digital twins is huge, but multiple challenges need to be solved before it can live up to its potential. Digital twin technology is draw... » read more

Auto Security Accelerates With Standardization And Certified Silicon
By Ann Mutschler - 05 Mar, 2026 - Comments: 0

Key Takeaways The automotive sector is actively developing and delivering secure parts and features ranging from secure boot to encrypted data and in-network protections. The cost of a breach can involve everything from ransomware to liability and/or damage to a brand. New standards are being introduced to ensure security, and technology developers are integrating cybersecurity requi... » read more

Limiting AI/ML Tools To Ensure Physical AI Safety, Security
By Liz Allan - 05 Mar, 2026 - Comments: 0

Key Takeaways: AI-based tools can help monitor physical AI systems and LLMs, but human oversight is still needed to avoid false positives, bias, and other anomalies. For autonomous vehicles and robots, edge case scenarios and understanding human values are weak points, especially as moral and social values change over time. AI tools are growing and becoming increasingly helpful for c... » read more

New Automotive Architectures Are Shaking Up Processor And Memory Choices
By Ann Mutschler - 05 Mar, 2026 - Comments: 0

Key Takeaways Assisted and autonomous driving require more data from more sensors, and much faster processing of some of that data. The shift to software-defined vehicles and centralized intelligence makes it easier to identify where the most advanced processors and memories are required, and where older and less expensive technologies can be deployed. Technologies that were largely ... » read more

Tool And Methodology Changes Coming In Fab And Package Automation
By Gregory Haley - 04 Mar, 2026 - Comments: 0

Experts at the table: Semiconductor Engineering sat down to discuss what's changing in semiconductor fabs and packaging houses with Michael Lowman, senior product marketing manager for Data Analytics at Cohu; Aftkhar Aslam, CEO at yieldWerx, Woo Young Han, product marketing director at Onto Innovation; and Lihong Cao, senior director of engineering and technical marketing for ASE. What foll... » read more

Making Hybrid Bonding Better
By Laura Peters - 02 Mar, 2026 - Comments: 0

Key Takeaways Fab processes are optimizing for cleanliness, planarity, and high bond quality. Nanotwinned copper and SiCN PVD enable lower anneal and deposition temperatures for HBM. A thin, protective layer helps preserve the Cu/dielectric during aggressive processes. The future of semiconductor manufacturing is no longer dependent just on shrinking features. Instead, chipm... » read more

Using Data And AI More Effectively In EDA
By Brian Bailey - 26 Feb, 2026 - Comments: 0

Key Takeaways The data being produced by EDA tools tends to be for human consumption and has weak semantics. Agents are attempting to create actionable information from unstructured data. The Model Context Protocol may provide AI with access to better data. Semiconductor design generates a lot of data, but how much of that is useful or currently being used by AI tools? And h... » read more

AI Starting To Simplify Design Of Programmable Logic
By Liz Allan - 26 Feb, 2026 - Comments: 0

Key Takeaways AI/ML and agentic tools are getting better at helping design and compile FPGAs, but downstream programming is slower to benefit. FPGAs historically have been designed using Verilog or VHDL, but higher-level languages could push more intelligence into compilers. ML tools can also help with mixed-signal co-design by automatically tuning DSP algorithms based on analog simu... » read more

Verifying Scale-Up And Scale-Out In Data Centers
By Ed Sperling - 26 Feb, 2026 - Comments: 0

Semiconductor Engineering sat down to discuss challenges and solutions for data center build-out and build-up with Gordon Allan, Siemens EDA director of verification IP; Rishi Chugh, vice president of product marketing for network switching at Marvell; Saravanan Kalinagasamy, senior director of ASIC design and validation at Astera Labs; and Jalaj Gupta, product engineering lead at Siemens EDA. ... » read more

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