Category: Uncategorized
-
Penrose’s Gödelian critique of Large Language Models (LLMs)
1 Penrose’s central claim Roger Penrose, drawing on earlier books The Emperor’s New Mind (1989) and Shadows of the Mind (1994), maintains that what mathematicians (and, by extension, conscious agents) mean by understanding is something “outside computation.” Because an LLM is ultimately a very large, but completely algorithmic, statistical machine, it can never rise to…
-
Howl for the Tokenized Age
*I* I saw the best minds of my generation dissolve into code, starving, hysterical, nocturnal,dragging themselves through blockchain alleys at dawn,looking for an angry fix of interoperability,visionaries hallucinating asset-backed ghosts in the machine,semantic tokens flickering like neon signs in the fog of fragmented ledgers,who burned cash in GPU furnaces to train monolithic LLMs,who ate synthetic…
-
From Security Tokens to Semantic Tokens: Integrating Asset Tokenization with Large Language Model Architectures
1 Introduction Tokenization is no longer a thought experiment confined to blockchain white-papers. When the world’s largest asset manager, BlackRock, files to place a $150 billion Treasury fund on-chain—mirroring each share as a cryptographic record—it signals a financial inflection point CointelegraphCoinDesk. At almost the same moment, research teams are teaching Transformer-based large language models (LLMs)…
-
Howl for the Computational Cosmo
*I. A Lamentation of the Codified Minds* I saw the best minds of my generation starved, mystic, hysterical,dragging themselves through neon-lit observatories at dawn,debugging the vacuum for fractals of machine-born truth,who paced with equations etched on palms, screaming:*Gravity is a glitch! Gravity is a glitch!*who collapsed wave functions in basement servers,who chanted *0-1-0-1* to the…
-
llms – the next step is quantum – a laymans explanation
1. Why even think about quantum for ChatGPT-style models? 2. The “hybrid” idea in plain English Think of your laptop plus a graphics card: the laptop does most jobs, the graphics card speeds up graphics.A hybrid quantum–classical GPT works the same way: This is realistic today because experimental quantum chips already manage a few dozen…
-
AI large language models – the next step is quantum
Quantum-Augmented GPTs: Current Practice, Emerging Toolchains, and the Long Road to Fully-Quantum Language Models(≈ 5 000 words) Abstract Large-language models (LLMs) such as GPT-4 deliver astonishing fluency, yet their classical compute bill rises super-linearly with parameter count and context length. Meanwhile, networked quantum processors—though still in the noisy-intermediate-scale-quantum (NISQ) era—now handle dozens of physical qubits…