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Showing posts from May, 2024

Microchip to Boost Edge AI with NVIDIA Holoscan

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 The NVIDIA Holoscan AI sensor processing platform, SDK and development ecosystem has helped to streamline the design and deployment of AI and high-performance computing ( HPC ) applications at the edge for real-time insights. Now, FPGAs are unlocking new edge-to-cloud applications for this advanced AI platform while enabling AI/ML inferencing and facilitating the adoption of AI in the medical, industrial and automotive markets.  Microchip's new PolarFire FPGA Ethernet Sensor Bridge is empowering developers to create innovative, real-time solutions with NVIDIA’s edge AI and robotics platforms that will revolutionize sensor interfaces across a wide range of powerful applications. To enable developers building artificial intelligence (AI)-driven sensor processing systems, Microchip Technology has released its PolarFire FPGA Ethernet Sensor Bridge that works with the NVIDIA Holoscan sensor processing platform.  Accelerating Real-time Edge AI with NVIDIA Holoscan The Pola...

Apple M4 becomes the new underdog of arm processors

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Apple's M4 chip is officially here, debuting in the new iPad Pro at Apple's "Let Loose" event on May 7, 2024. Built using second-generation 3-nanometer technology, M4 is a system on a chip (SoC) that advances the industry-leading power efficiency of Apple silicon and enables the incredibly thin design of iPad Pro. It also features an entirely new display engine to drive the stunning precision, colour, and brightness of the breakthrough Ultra Retina XDR display on iPad Pro.   A new CPU has up to 10 cores , while the new 10-core GPU builds on the next-generation GPU architecture introduced in M3, and brings Dynamic Caching, hardware-accelerated ray tracing, and hardware-accelerated mesh shading to iPad for the first time. M4 has Apple’s fastest Neural Engine ever, capable of up to 38 trillion operations per second, which is faster than the neural processing unit of any AI PC today.  Combined with faster memory bandwidth, along with next-generation machine learning (M...

Kolmogorov-Arnold Networks Explained

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 A groundbreaking research paper released just few days ago introduces a novel neural network architecture called Kolmogorov-Arnold Networks (KANs). This new approach, inspired by the Kolmogorov-Arnold representation theorem, promises significant improvements in accuracy and interpretability compared to traditional Multi-Layer Perceptrons (MLPs). Let’s dive into what KANs are, how they work, and the potential implications of this exciting development. Kolmogorov-Arnold Networks (KANs) are promising alternatives of Multi-Layer Perceptrons (MLPs). KANs have strong mathematical foundations just like MLPs: MLPs are based on the universal approximation theorem, while KANs are based on Kolmogorov-Arnold representation theorem. KANs and MLPs are dual: KANs have activation functions on edges, while MLPs have activation functions on nodes. This simple change makes KANs better (sometimes much better!) than MLPs in terms of both model accuracy and interpretability. The Traditional Foundation:...