Running More Efficient AI/ML Code With Neuromorphic Engines


Neuromorphic engineering is finally getting closer to market reality, propelled by the AI/ML-driven need for low-power, high-performance solutions. Whether current initiatives result in true neuromorphic devices, or whether devices will be inspired by neuromorphic concepts, remains to be seen. But academic and industry researchers continue to experiment in the hopes of achieving significant ... » read more

Fundamental Issues In Computer Vision Still Unresolved


Given computer vision’s place as the cornerstone of an increasing number of applications from ADAS to medical diagnosis and robotics, it is critical that its weak points be mitigated, such as the ability to identify corner cases or if algorithms are trained on shallow datasets. While well-known bloopers are often the result of human decisions, there are also fundamental technical issues that ... » read more

Dealing With AI/ML Uncertainty


Despite their widespread popularity, large language models (LLMs) have several well-known design issues, the most notorious being hallucinations, in which an LLM tries to pass off its statistics-based concoctions as real-world facts. Hallucinations are examples of a fundamental, underlying issue with LLMs. The inner workings of LLMs, as well as other deep neural nets (DNNs), are only partly kno... » read more

Linear Drive Optics May Reduce Data Latency


Optical and electrical are starting to cross paths at a much deeper level, particularly with the growing focus on 3D-ICs and AI/ML training in data centers, driving changes both in how chips are designed and how these very different technologies are integrated together. At the root of this shift are the power and performance demands of AI/ML. It can now take several buildings of a data cente... » read more

The Data Crisis Is Unfolding — Are We Ready?


The rapid advancement of technology has led to an unprecedented amount of data being generated, captured, and consumed globally. However, this reliance on data comes at a considerable cost. The widespread sharing and processing of data is necessary to navigate our everyday lives. Still, any disruption to this process can have severe consequences, threatening our ability to function as a society... » read more

3D-IC Intensifies Demand For Multi-Physics Simulation


The introduction of full 3D-ICs will require a simultaneous analysis of various physical effects under different workloads, a step-function change that will add complexity at every step of the design flow, expand and alter job responsibilities, and bring together the analog and digital design worlds in unprecedented ways. 3D-ICs will be the highest-performance advanced packaging option, in s... » read more

Chip Industry Week In Review


By Susan Rambo, Karen Heyman, and Liz Allan. Renesas plans to acquire Altium, maker of PCB design software, for $5.9 billion. In a conference call, Renesas CEO Hidetoshi Shibata cited Altium's PCB design software and digital twin virtual modeling as key components of its future strategy. "I believe it will generate transformational value for our combined customers and our stakeholders," Shib... » read more

SRAM Scaling Issues, And What Comes Next


The inability of SRAM to scale has challenged power and performance goals forcing the design ecosystem to come up with strategies that range from hardware innovations to re-thinking design layouts. At the same time, despite the age of its initial design and its current scaling limitations, SRAM has become the workhorse memory for AI. SRAM, and its slightly younger cousin DRAM, have always co... » read more

Chip Industry Week In Review


By Jesse Allen, Gregory Haley, and Liz Allan. Cadence introduced an AI-based thermal stress and analysis platform aimed at 2.5D and 3D-ICs, and cooling for PCBs and electronic assemblies. The company also debuted a HW/SW accelerated digital twin solution for multi-physics system design and analysis, combining GPU-resident computational fluid dynamics (CFD) solvers with dedicated GPU hardwar... » read more

Dealing With Noise In Image Sensors


The expanding use and importance of image sensors in safety-critical applications such as automotive and medical devices has transformed noise from an annoyance into a life-threatening problem that requires a real-time solution. In consumer cameras, noise typically results in grainy images, often associated with poor lighting, the speed at which an image is captured, or a faulty sensor. Typi... » read more

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