Streamlining Failure Analysis Of Chips


Experts at the Table: Semiconductor Engineering sat down to discuss how increasing complexity in semiconductor and packaging technology is driving shifts in failure analysis methods, with Frank Chen, director of applications and product management at Bruker Nano Surfaces & Metrology; Mike McIntyre, director of product management in the Enterprise Business Unit at Onto Innovation; Kamran Hak... » read more

How Much AI Is Really Needed?


Tensor Core GPUs have created a generative AI model gold rush. Whether it’s helping students with math homework, planning a vacation, or learning to prepare a six-course meal, generative AI is ready with answers. But that's only one aspect of AI, and not every application requires it. AI — now an all-inclusive term, referring to the process of using algorithms to learn, predict, and make... » read more

Data Collection For Edge AI / Tiny ML With Sensors


Reality AI software from Renesas provides solution suites and tools for R&D engineers who build products and internal solutions using sensors. Working with accelerometers, vibration, sound, electrical (current/voltage/ capacitance), radar, RF, proprietary sensors, and other types of sensor data, Reality AI software identifies signatures of events and conditions, correlates changes in signat... » read more

Neuromorphic Hardware Accelerator For Heterogeneous Many-Accelerator SoCs


A technical paper titled “SpikeHard: Efficiency-Driven Neuromorphic Hardware for Heterogeneous Systems-on-Chip” was published by researchers at Columbia University. Abstract: "Neuromorphic computing is an emerging field with the potential to offer performance and energy-efficiency gains over traditional machine learning approaches. Most neuromorphic hardware, however, has been designed wi... » read more

Network-on-Chips Enabling Artificial Intelligence/Machine Learning Everywhere


Recently, I attended the AI HW Summit in Santa Clara and Autosens in Brussels. Artificial intelligence and machine learning (AI/ML) were critical themes for both events, albeit from different angles. While AI/ML as a buzzword is very popular these days in all its good and bad ways, in discussions with customers and prospects, it became clear that we need to be precise in defining what type of A... » read more

Thoughts On AI Consciousness


By Anda Ioana Enescu Buyruk and Catalin Tudor The rapid advancement of artificial intelligence (AI) has sparked profound discussions regarding the possibility of AI systems achieving consciousness. Such a development carries immense implications, forcing us to redirect our focus from studying the behavior of other organisms to scrutinizing ourselves. This article will delve into the concept ... » read more

When And Where To Implement AI/ML In Fabs


Deciphering complex interactions between variables is where machine learning and deep learning shine, but figuring out exactly how ML-based systems will be most useful is the job of engineers. The challenge is in pairing their domain expertise with available ML tools to maximize the value of both. This depends on sufficient quantities of good data, highly optimized algorithms, and proper tra... » read more

Photonic-Electronic SmartNIC With Fast and Energy-Efficient Photonic Computing Cores (MIT)


A technical paper titled “Lightning: A Reconfigurable Photonic-Electronic SmartNIC for Fast and Energy-Efficient Inference” was published by researchers at Massachusetts Institute of Technology (MIT). Abstract: "The massive growth of machine learning-based applications and the end of Moore's law have created a pressing need to redesign computing platforms. We propose Lightning, the first ... » read more

Automotive Intrusion Detection Methodologies (TU Denmark)


A new technical paper titled "Intrusion Detection in the Automotive Domain: A Comprehensive Review" was published by researchers at DTU Compute Technical University of Denmark Abstract "The automotive domain has realized amazing advancements in communication, connectivity, and automation— and at a breakneck pace. Such advancements come with ample benefits, such as the reduction of traffic... » read more

Tradeoffs In DSP Design


More intelligence is now required in the front-, mid-, and back-haul for 5G/6G communication, requiring a mix of high performance, low power, and enough flexibility to accommodate constantly changing protocols and algorithms. One solution to these conflicting goals involves reconfigurable DSPs, in which the processing element is hardwired like an ASIC but still configurable for a variety of app... » read more

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