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RAG-Anything: Making AI Understand Every Part of a Document A recent X (Twitter) thread introduced a new AI framework called RAG-Anything, which fixes some big weaknesses in today’s Retrieval-Augmented Generation (RAG) systems—the kind used by large language models to pull in external information when answering questions. The Problem with Old RAG Systems Most current RAG…

(An Essay on the Information-Theoretic Structure of Comedy) I. Introduction: The Information Content of a Laugh Humor is one of the few human behaviors that defies both reduction and repetition. You can describe a joke, quantify its rhythm, and even trace its neuronal timing — but the moment you explain it, it dies. Yet this…

Unveiled in September 2025 by researchers at the Chinese Academy of Sciences’ Institute of Automation in Beijing, SpikingBrain marks a major milestone in neuromorphic artificial intelligence. It is described as the world’s first large-scale brain-like AI system—an attempt to move beyond conventional Transformer-based architectures toward networks that behave more like the human brain itself. Traditional…

“Where there is a gradient, something will awaken to feed on it.” ⚡ I. The Living Sky They rise from the sea like thoughts from heat—columns of vapor learning to breathe.No skeleton, no seed, only temperature and spin shaping themselves into intention.A hurricane is not chaos; it is order born from imbalance, a transient geometry…

Tokenization, in the context of Large Language Models (LLMs), breaks down text into smaller, machine-readable units called tokens. Similarly, in molecular modeling, tokenization involves converting complex molecular structures or chemical data into discrete, machine-readable units that can be processed by machine learning models. These models, often referred to as molecular language models or graph-based models,…

Tokenization is a foundational process in natural language processing (NLP) that transforms raw human language into machine-readable units called tokens. These tokens serve as the essential building blocks for LLMs, enabling them to understand and generate text. This document explores the importance of tokenization, defines what tokens are, and details the various tokenization strategies used…