LF Yadda

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  • Entropic Foundations of Life: Shannon and Boltzmann Entropies as Universal Drivers Beyond Biological Confines

    With GROK3 This paper explores how Shannon entropy (information uncertainty) and Boltzmann entropy (thermodynamic disorder) collaboratively underpin the mechanisms driving life. Technically, it examines self-organization as an emergent property of energy dissipation and information processing, supported by mathematical frameworks and examples from biology and artificial systems. Philosophically, it challenges anthropocentric definitions of life, proposing that…

  • The Paradox of Determinism and Randomness in Large Language Models: Engineering Creativity Through Controlled Chaos

    With Deepseek and a random comment I copied from X expand this thinking to a 2000 word essay Our computing platforms are massive deterministic systems. Incredible energy goes into the silicon supply chain to ensure that our hardware is linear, predictable, and deterministic… But with LLMs, we intentionally break this deterministic model. Stochastic gradient descent,…

  • deepseek summary of amazon’s quantum computing chip ocelot

    The article titled “Hardware-efficient quantum error correction via concatenated bosonic qubits” presents a significant advancement in quantum computing by demonstrating a scalable and hardware-efficient approach to quantum error correction (QEC). The research focuses on reducing the physical-qubit overhead associated with error correction, which is a major challenge in realizing practical quantum computers. The authors achieve this by…

  • Modes of Artificial Neural Networks Construction

    My discussion with Deepseek what are the current modes of artificial NEURAL NETWORKS in terms of construction like software. hardware Thought for 48 seconds Okay, so I need to figure out the current modes of artificial neural networks in terms of construction, both software and hardware. Hmm, where do I start? Let me break this…

  • Retrieval-Augmented Generation (RAG) Across Database Types

    Diagram: A RAG system retrieving from structured and unstructured internal sources. The LLM (“Generation Model”) receives a prompt augmented with context fetched by specialized retrievers – a structured data retriever (via SQL queries to databases) and an unstructured data retriever (via document search). In a complete RAG implementation, the retrieval component pulls both structured data…

  • Decoding the Black Box: Analogies Between Neural Network Embeddings, Modulation, and Spectral Decomposition in Large Language Models

    Abstract This paper explores the interpretability of artificial neural networks (ANNs), particularly large language models (LLMs), through the lens of signal processing and spectral analysis. Drawing parallels to transmission carrier modulation and Fourier transform-like decomposition, we analyze how high-dimensional vector embeddings encode linguistic patterns and relationships. While acknowledging the non-linear, adaptive nature of ANNs, we propose frameworks inspired…