arXiv:2601.02509v1 Announce Type: new Abstract: Following the initial publication of hdlib, a Python library for designing Vector-Symbolic Architectures (VSA), we introduce a major extension that significantly enhances its machine learning capabilities. VSA, also known as Hyperdimensional Computing, is a computing paradigm that represents and processes information using high-dimensional vectors. While the first version of hdlib established a robust foundation for creating and manipulating these vectors, this update addresses the growing need for more advanced, data-driven modeling within the […]

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By Michael Nielsen, December 2018 In natural science, Nature has given us a world and we’re just to discover its laws. In computers, we can stuff laws into it and create a world. – Alan Kay Quantum computing originated in the 1980s with several papers that received little fanfare at the time. Even by the mid-1990s, mentioning quantum computing to a physicist usually resulted in the question: “What’s a quantum computer?” Answers would often then be greeted with: […]

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arXiv:2602.05970v1 Announce Type: cross Abstract: Neural scaling laws relate loss to model size in large language models (LLMs), yet depth and width may contribute to performance differently, requiring more detailed studies. Here, we quantify how depth affects loss via analysis of LLMs and toy residual networks. We find loss scales inversely proportional to depth in LLMs, probably due to functionally similar layers reducing error through ensemble averaging rather than compositional learning or discretizing smooth dynamics. This regime is […]

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arXiv:2601.08927v1 Announce Type: new Abstract: For any positive integer $g ge 2$, we derive general conditions for the existence of a $2g$-cycle in the Tanner graph of two-dimensional ($2$-D) classical quasi-cyclic (QC) low-density parity-check (LDPC) codes. Based on these conditions, we construct a family of $2$-D classical QC-LDPC codes with girth greater than $4$ by stacking $p times p times p$ tensors, where $p$ is an odd prime. Furthermore, for composite values of $p$, we propose two additional […]

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Introduction Writing with AI assistance is not the same as writing by AI. When you write directly with AI, you’re prompting it to generate content from scratch. When you write with AI assistance, you remain the author—AI simply helps refine your work rather than doing most of it for you. The Problem with Full AI Generation Yes, you can create a story from scratch using AI prompts, but the result will likely be short and won’t capture exactly […]

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