AI Techniques To Solve HW-SW Challenges For Useful Quantum Computing (Nvidia, U. of Oxford et al.)


A new technical paper "Artificial intelligence for quantum computing" was published by researchers at NVIDIA, University of Oxford, University of Toronto, Quantum Motion, University of Waterloo et al. Abstract "Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extend... » read more

AI With Open And Scaled Data Sharing in IC Manufacturing (NIST)


A new workshop report titled "Artificial Intelligence with Open and Scaled Data Sharing in Semiconductor Manufacturing" was published by NIST. Abstract "The Workshop sponsored by the National Science Foundation (NSF) (NSF award 2334590, "Artificial Intelligence with Open and Scaled Data Sharing in the Semiconductor Industry") and supported by the National Institute of Standards and Techno... » read more

AI-Empowered Analog IC Sizing Methods (Univ. of Glasgow Et Al.)


A new technical paper titled "From Systematic to Intelligent: Assessing AI-Empowered Optimization Techniques for Analog Building Block Sizing" was published by researchers at University of Glasgow, Mediatek, The University of Edinburgh, Magics Technologies NV, University of Sevilla and Georgia Institute of Technology. Abstract "This paper presents a comprehensive, design-insight-based compa... » read more

The Limits Of AI’s Role In EDA Tools


The world has been inspired by generative AI models like ChatGPT. These are very applicable to things like copilots and agentic AI, but the adoption of these models into EDA tools is less obvious. What may be appropriate, and can AI make EDA tools faster or better? EDA has been enabling Moore's Law for the past 40 years, and that has required pushing the limits of many of the algorithms and ... » read more

Beyond the Bottleneck: AI Cluster Networking Report 2025


Artificial intelligence (AI) is the engine of next-generation innovation. However, increasing complexity means increased demand on data center networks. As AI grows into a central component of enterprise strategies, organizations must carefully consider how they design, test, and scale their infrastructure. This report, based on a global survey conducted by Heavy Reading in collaboration with K... » read more

Report: The Road to Artificial General Intelligence: Achieving the Next Era of Intelligence


Explore how industry leaders are defining artificial general intelligence (AGI) and what it may take to reach it. Developed by MIT Technology Review and Arm, this deep dive examines accelerating timelines, the compute innovations shaping progress, and why today’s models still fall short of true intelligence. Designed for engineers, researchers, and technology leaders navigating the future of ... » read more

AI: Driving the Way to Safer and Smarter Cars


As autonomous vehicles have only begun to appear on limited public roads, it has become clear that achieving widespread adoption will take longer than early predictions suggested. With Level 3 systems in place, the road ahead leads to full autonomy and Level 5 self-driving. However, it’s going to be a long climb. Much of the technology that got the industry to Level 3 will not scale in all th... » read more

Operational Cybersecurity and Supply Chain Risks Across the AI Lifecycle (Sandia National Labs)


A new technical paper titled "Surveying the Operational Cybersecurity and Supply Chain Threat Landscape when Developing and Deploying AI Systems" was published by researchers at Sandia National Labs. Abstract "The rise of AI has transformed the software and hardware landscape, enabling powerful capabilities through specialized infrastructures, large-scale data storage, and advanced hardware... » read more

For Chip Developers, HW/SW Co-Design Key To Data Center Efficiency


Data centers and high-performance computing (HPC) are the primary enablers of today’s power-hungry AI-driven technology, but chip designers, EDA vendors, and the data centers themselves have a long list of options available to them to help curb AI's power consumption. Chip designers play a critical role in ensuring energy efficient processing from the bottom up, whether that is hardware-so... » read more

Report: The AI Efficiency Boom


Artificial Intelligence (AI) is undergoing a fundamental transformation. While early AI models were large, compute-heavy, and dependent on cloud processing, a new wave of efficiency-driven innovations is moving AI inference—the generation of model results—to the edge. Smaller models, improved memory and compute performance, and the need for privacy, low latency, and energy efficiency are dr... » read more

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