tag: AI

Physical Access Control Raises New Security Concerns
By Ann Mutschler - 27 Aug, 2025 - Comments: 0

Experts At The Table: Semiconductor Engineering sat down to discuss hardware security challenges, including fundamental security of GenAI, with Nicole Fern, principal security analyst at Keysight; Serge Leef, AI-For-Silicon strategist at Microsoft; Scott Best, senior director for silicon security products at Rambus; Lee Harrison, director of Tessent Automotive IC Solutions at Siemens EDA; Mohit... » read more

Machine Learning In Semiconductor Manufacturing
By Ed Sperling - 22 Aug, 2025 - Comments: 0

Second in a seven-part series: Machine learning is a mathematical construct that is the foundation for nearly all the advancements in AI. ML came first, but it remains relevant even today. It can be applied to semiconductor fab for such things as predictive maintenance of manufacturing equipment, rather than just maintenance on a schedule, which decreases downtime. But getting this right is har... » read more

Best Options For Using AI In Chip Design
By Ed Sperling - 20 Aug, 2025 - Comments: 0

Experts at the Table: Semiconductor Engineering sat down to discuss how and where AI can be applied to chip design to maximize its value, and how that will impact the design process, with Chuck Alpert, Cadence Fellow; Sathish Balasubramanian, head of product marketing and senior director for custom IC at Siemens EDA; Anand Thiruvengadam, senior director and head of AI product management at S... » read more

AI, From A To Z
By Ed Sperling - 15 Aug, 2025 - Comments: 0

First in a seven-part series: What's the difference between AI, ML, DL, LLMs, and agentic AI? Is it truly revolutionary, or is it an evolutionary series of steps that have enabled machines to do much more than in the past? Jon Herlocker, vice president and general manager of software analytics at Cohu, talks about the evolution of AI over nearly 70 years, the chain of innovation that has enable... » read more

System-Level Design For 1.6 Tbps Interoperability In AI Data Centers
By Madhumita Sanyal - 14 Aug, 2025 - Comments: 0

By Madhumita Sanyal and Diwakar Kumaraswamy The rapid escalation of AI/ML workloads—driven by increasingly large language models—is reshaping high-performance computing and AI data center architectures. Real-time inference and large-scale training are pushing the limits of compute and interconnect performance. With model sizes and parameter counts doubling every 4–6 months, infrastruct... » read more

Re-Architecting AI For Power
By Brian Bailey - 14 Aug, 2025 - Comments: 0

The industry is becoming increasingly concerned about the amount of power being consumed by AI, but there is no simple solution to the problem. It requires a deep understanding of the application, the software and hardware architectures at both the semiconductor and system levels, and how all of this is designed and implemented. Each piece plays a role in the total power consumed and the utilit... » read more

Maximize Uptime And Improve TCO: RAS And Telemetry In HBM4 For Data Centers
By Raj Uppala - 14 Aug, 2025 - Comments: 0

As AI workloads scale and data center operations become increasingly complex, it is critical to keep the infrastructure up and running. Total Cost of Ownership (TCO) is a key metric that includes not only the upfront cost of hardware but also the ongoing expenses of power, cooling, maintenance, and—most importantly—downtime. A single memory failure in a hyperscale AI cluster can cascade int... » read more

UEC-CBFC: Credit-Based Flow Control For Next-Gen Ethernet In AI And HPC
By Harinee Rathod - 14 Aug, 2025 - Comments: 0

For ages, Ethernet has been the backbone of networking — starting from simple web browsing to cloud computing, data centers, automobiles, and more. Ethernet has enabled countless innovations, and now, it's expanding to meet the demands of AI and HPC. As the world shifts toward these new technologies, new challenges are emerging. These include increased scale, higher bandwidth density, mult... » read more

Reliable Training Data Paramount To AI Model Success
By Ann Mutschler - 14 Aug, 2025 - Comments: 0

AI systems are increasingly being integrated into safety- and mission-critical applications ranging from automotive to health care and industrial IoT, stepping up the need for training data that is reliable, secure, and which is generated from trusted sources. AI activity is growing exponentially, as everybody tries to figure out how to apply it to their domain, application, or workload. In ... » read more

Start Experimenting With Neural Super Sampling For Mobile Graphics
By Sergio Alapont Granero - 14 Aug, 2025 - Comments: 0

Mobile game developers around the world face increasing pressure to meet user expectations for sharper visuals, smoother gameplay, and longer battery life. Balancing these goals on constrained mobile devices often means making trade-offs. Traditional upscaling methods offer limited flexibility. Real-time AI rendering remains complex, power-hungry, or hardware dependent. Neural Super Sampling... » read more

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