tag: LLMs

AI Workloads at the Edge: Ensuring Performance, Privacy, and Security
By Ann Mutschler - 17 Dec, 2025 - Comments: 0

Experts At The Table: Semiconductor Engineering gathered a group of experts to discuss why some AI workloads are better suited for on-device processing to achieve consistent performance, avoid network connectivity issues, reduce cloud computing costs, and ensure privacy. The panel included Frank Ferro, group director in the Silicon Solutions Group at Cadence; Eduardo Montanez, vice president a... » read more

Generative AI In Chip Manufacturing
By Ed Sperling - 15 Dec, 2025 - Comments: 0

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

Ensuring Accuracy in LLM-Generated Hardware Logic Design Automation (IBM Research)
By Technical Paper Link - 08 Dec, 2025 - Comments: 0

A new technical paper "Mitigating hallucinations and omissions in LLMs for invertible problems: An application to hardware logic design automation" was published by researchers at IBM Research. Abstract "We show for invertible problems that transform data from a source domain (for example, Logic Condition Tables (LCTs)) to a destination domain (for example, Hardware Description Language (... » read more

Optimizing AI Workloads For Edge Computing
By Ann Mutschler - 03 Dec, 2025 - Comments: 0

Experts At The Table: Semiconductor Engineering gathered a group of experts to discuss how some AI workloads are better suited for on-device processing to achieve consistent performance, avoid network connectivity issues, reduce cloud computing costs, and ensure privacy. The panel included Frank Ferro, group director in the Silicon Solutions Group at Cadence; Eduardo Montanez, vice president an... » read more

DeepSeek’s New AI Models: V3.2 and V3.2-Speciale
By Technical Paper Link - 01 Dec, 2025 - Comments: 0

DeepSeek published two new AI models: V3.2: Pushing the Frontier Of Open LLMs. The company claims the model "performs comparably to GPT-5." and V3.2-Speciale. DeepSeek claims the model "surpasses GPT-5 and exhibits reasoning proficiency on par with Gemini-3.0-Pro." Find the technical paper here and here.  "DeepSeek-V3.2 is our first model to integrate thinking directly into tool-us... » read more

LLMs on Analog In-Memory Computing Based Hardware (IBM Research, ETH Zurich)
By Technical Paper Link - 01 Dec, 2025 - Comments: 0

A technical paper titled "Analog Foundation Models" was published by IBM Research– Zurich, ETH Zurich, IBM Research-Almaden, and IBM TJ Watson Research Center. Abstract: "Analog in-memory computing (AIMC) is a promising compute paradigm to improve speed and power efficiency of neural network inference beyond the limits of conventional von Neumann-based architectures. However, AIMC intro... » read more

AI Plays Multiple Roles Within EDA
By Brian Bailey - 25 Nov, 2025 - Comments: 0

AI's infusion into our world may seem sudden and unexpected, but EDA has been quietly adopting it for more than a decade. What's changed is that it's now becoming more visible, thanks to increasingly powerful large language models (LLMs) and the need to apply them to increasingly challenging multi-physics problems. Two fundamental shifts underlie AI's increasing prominence. First, heat is be... » read more

Machine Learning Tools Accelerate Materials Discovery
By Katherine Derbyshire - 20 Nov, 2025 - Comments: 0

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven software tools that promise to accelerate all three. Many of the challenges facing the semiconductor manufacturing industry are fundamentally materials science problems. What metal has the lowest resi... » read more

Intelligence Per Watt: Measuring Local Inference Viability, Studying 20+ Models, 8 HW Accelerators (Stanford Univ.)
By Technical Paper Link - 18 Nov, 2025 - Comments: 0

A new technical paper titled "Intelligence per Watt: Measuring Intelligence Efficiency of Local AI" was published by researchers at Stanford University and Together AI. Abstract: "Large language model (LLM) queries are predominantly processed by frontier models in centralized cloud infrastructure. Rapidly growing demand strains this paradigm, and cloud providers struggle to scale infrastruc... » read more

Edge AI Is Starting To Transform Industrial IoT
By Liz Allan - 17 Nov, 2025 - Comments: 0

A slew of wireless and increasingly multi-modal sensors is being targeted at the Industrial Internet of Things (IIoT), setting the stage for significant improvements in efficiency, higher yield, and reduced downtime. Wired IIoT devices, such as smart energy meters and breakers, industrial network gateways, and environmental sensors already are well established in factory settings. They have ... » read more

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