Autonomous Driving: Assessment Of YOLO Algorithms (RMIT et al.)


A new technical paper titled "Advances in You Only Look Once (YOLO) algorithms for lane and object detection in autonomous vehicles" was published by RMIT University, Kyungpook National University, Deakin University and the RCA Robotics Laboratory, Royal College of Art. Abstract "Ensuring the safety and efficiency of Autonomous Vehicles (AVs) necessitates highly accurate perception, especia... » read more

5 Strategic Decisions for Building a Scalable Compute Platform for Now and the Future


Artificial intelligence (AI) is no longer a “nice-to-have” technology—it’s a central driver of competitive advantage and business innovation. Across industries, enterprises are moving beyond experimentation and embedding AI into all their products, workflows, and customer experiences. But as organizations scale, many are discovering a stark reality: their compute infrastructure was not ... » read more

Revolutionizing Semiconductor Collaboration: The Emergence of AI-Driven Industry Platforms


Demand for advanced computing is robust, driven by AI, cloud technologies, and widespread electrification of the economy. As Moore’s Law slows, the industry is pivoting toward innovative approaches—exploring 3D architectures, chiplets, and sophisticated hybrid packages. Concurrently, the semiconductor landscape is becoming increasingly global, with advanced devices now relying on integratin... » read more

Efficient Synchronous Dataflow Execution For GPUs (NVIDIA, UW-Madison)


A new technical paper titled "Kitsune: Enabling Dataflow Execution on GPUs with Spatial Pipelines" was published by researchers at NVIDIA and the University of Wisconsin-Madison. Abstract "State-of-the-art DL models are growing in size and complexity, with many modern models also increasing in heterogeneity of behavior. GPUs are still the dominant platform for DL applications, relying on ... » read more

The Growing Need For Collaboration Across The Semiconductor Industry


Abstract: AI-driven collaboration is becoming essential for the semiconductor industry to manage its increasingly complex global supply chain. This new model facilitates real-time data sharing and multi-party orchestration, moving beyond conventional, crisis-driven interactions. By leveraging a secure data infrastructure, automated orchestration, and AI agents, companies can automate busines... » read more

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

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