Workflow-Level Design For Trustworthy GenAI Integration in Vehicles (UOL, Denso)


A new technical paper, "Workflow-Level Design Principles for Trustworthy GenAI in Automotive System Engineering," was published by researchers at University of Oldenburg and Denso Automotive. Abstract "The adoption of large language models in safety-critical system engineering is constrained by trustworthiness, traceability, and alignment with established verification practices. We propos... » read more

HW-Based Image Generation Using FTJs (SNU, Sungkyunkwan U., SK hynix et al.)


A new technical paper, "CMOS-compatible ferroelectric tunnel junctions integrate stochastic sampling and deterministic computing for image generation," was published by researchers at Seoul National University, Sungkyunkwan University, Hanyang University, Sogang University, and SK Hynix. Abstract "Recent progress in generative modeling has intensified the need for compact, energy-efficien... » read more

How SW and HW Vulnerabilities Can Complement LLM-Specific Algorithmic Attacks (UT Austin, Intel et al.)


A new technical paper, "Cascade: Composing Software-Hardware Attack Gadgets for Adversarial Threat Amplification in Compound AI Systems," was published by the University of Texas, Austin, Intel Labs, Symmetry Systems, Microsoft and Georgia Tech. Abstract "Rapid progress in generative AI has given rise to Compound AI systems - pipelines comprised of multiple large language models (LLM), so... » read more

Generative AI In Chip Manufacturing


Generative AI is a natural-language or text-based query, predicting patterns based on a massive set of data. While most of the attention has been focused on chatbots and copilots, it also can be used to identify small, transient aberrations in semiconductor manufacturing that are otherwise difficult to find. Jon Herlocker, vice president and general manager of software analytics at Cohu, talks ... » read more

Rethinking The Role Of CPUs In AI: A Practical RAG Implementation


In many enterprise environments, engineers and technical staff need to find information quickly. They search internal documents such as hardware specifications, project manuals, and technical notes. These materials are often scattered, making traditional search inefficient. These documents are often confidential or proprietary. This constraint prevents these documents from being processed by... » read more

Resilient And Optimized GenAI Systems


AI and data center systems are being pushed to their limits, with soaring complexity, nonstop inference workloads, and rising energy demands. Addressing these pressures requires more than incremental improvements, it calls for collaboration across the ecosystem. That’s why proteanTecs has joined forces with Arm, bringing our real-time monitoring technology into Arm’s Neoverse Compute Subsys... » read more

Chip Innovation Will Bridge The Gap For USA Data Center Power


Heading to meetings in Silicon Valley, I often drive through Santa Clara, passing boxy buildings with few windows. They are data centers for local customers willing to pay for low latency. Data centers cluster in Santa Clara because that city's power has been the cheapest in Silicon Valley. The San Jose Mercury News recently reported that two data centers in Santa Clara are empty, waiting for a... » read more

Formal Verification’s Value Grows


Experts at the table: Semiconductor Engineering sat down to discuss why formal verification is becoming more important, with Ashish Darbari, CEO for Axiomise; Jin Zhang, product management group director for the Verification Group at Cadence; Sean Safarpour, executive director for R&D at Synopsys; and Jeremy Levitt, principal engineer for Digital Verification Technology at Siemens EDA. Wha... » read more

Multiple Challenges Emerge With Physical AI System Design


Physical AI holds the promise of making everything from robots to a slew of mobile edge devices much more interactive and useful, but it will significantly alter how systems are designed, verified, and monitored. Physical AI systems need to work both independently and together. They need the ability to make decisions quickly and locally, typically using much less power than other types of AI... » read more

Critical Optimization Factors For GenAI Chipmakers


Today’s GenAI arms race is fought with novel chip architectures and packaging. Specialized hardware designs are proliferating in the form of GPUs, TPUs, NPUs, and more, all tuned for parallelism and matrix-heavy AI math. In this hyper-competitive landscape, chip vendors scramble to differentiate their products on multiple fronts. They promise some mix of better performance, efficiency, or ... » read more

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