Techtroniks

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

 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: Mul