tag: AI

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

Follow The AI Leader
By Brian Bailey - 03 Mar, 2026 - Comments: 0

In the 1980s, a common expression was "nobody ever got fired for buying IBM." It was considered the safe option, long after new technologies had emerged. While it may not have been the most advanced option available, it remained the safe bet. It had an established ecosystem, and it was a known quantity. But who or what is the safe bet when it comes to AI? Who has the necessary data? Who has ... » read more

AI Energy Gap And Chiplets: Why Data Movement Matters
By Ashley Stevens - 26 Feb, 2026 - Comments: 0

At the recent Chiplet Summit 2026 preconference tutorial, the panel session, “Best Way to Make Chiplets Work,” brought together leaders from across the semiconductor ecosystem to tackle one of the most pressing challenges in advanced system design: how do we make heterogeneous, multi-die systems operate as a cohesive, energy-efficient whole for AI? While much discussion focused on st... » 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

The On-Device LLM Revolution
By Steve Roddy - 20 Feb, 2026 - Comments: 0

The AI world is experiencing a fundamental shift. After years of cloud-centric inference dominated by massive data center GPUs, we're witnessing an accelerating migration of language models to edge devices. These are not the trillion-parameter behemoths that require server farms, but the "Goldilocks zone" models: 3B to 30B parameters — large enough to deliver genuinely useful AI capabilities,... » read more

Force Fields Will Accelerate Atomistic Simulations By 10,000× In 2026, Unlocking New Era Of Discovery
By Anders Blom - 19 Feb, 2026 - Comments: 0

By Anders Blom and Igor Markov “Force fields” have long captured our imagination — the invisible shields of science-fiction lore that protect starships and superheroes from harm. But in the world of scientific discovery, force fields play a much different role: They are mathematical models that let us peer into the atomic heart of matter itself. Now, thanks to breakthroughs in artif... » read more

Research Bits: Feb. 17
By Jesse Allen - 17 Feb, 2026 - Comments: 0

Analog layout foundation model Researchers from Pohang University of Science and Technology (POSTECH) built a foundation model for automated analog circuit layout. The team used a self-supervised learning approach, in which the model learns without human-provided labels. To counter a lack of available training data, the team divided analog layouts into small patches, masked part of each lay... » read more

One-on-One With proteanTecs CEO Shai Cohen
By Ed Sperling - 17 Feb, 2026 - Comments: 0

The acceleration of technology is unprecedented: AI data centers, edge build-out, robotics, photonics, quantum, multi-die assemblies. Semiconductor Engineering Editor in Chief Ed Sperling talks with proteanTecs CEO Shai Cohen about what's changing and what impact it will have. Click here to listen. » read more

How Siemens Symphony Pro Enabled AnalogPort To Verify Complex Chip Interfaces
By Siemens EDA - 13 Feb, 2026 - Comments: 0

The semiconductor industry's shift toward chiplet-based architectures has created significant mixed-signal verification challenges for high-speed die-to-die interconnects. Traditional verification approaches force difficult trade-offs: Digital mixed-signal (DMS) flows sacrifice analog fidelity, while Analog mixed-signal (AMS) flows struggle with scalability and manual overhead. This paper detai... » read more

Formal Verification First: How AI Supports But Cannot Replace It
By Fabiana Muto - 13 Feb, 2026 - Comments: 0

At a recent VLSI-D panel, industry leaders explored one of the most pressing topics in silicon design today — the intersection of AI-powered EDA, which is revolutionizing chip design for tomorrow. Ashish Darbari, CEO of Axiomise, questioned the panelists on the role of AI in chip design, optimizing PPA, validation and verification. While the panel explored the role of AI in design implemen... » read more

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