This document outlines the technical architecture for processing a livestream multi-host & multi-guest podcast transcript into various marketing outputs for both social media and technical marketing purposes.
obelisk on main [?] is 📦 v0.1.0 via 🐍 v3.9.6
❯ docker model run ai/qwen3
Interactive chat mode started. Type '/bye' to exit.
> tell me about your training corpus, knowledge scope, and strongest logic and skill qualities.
<think>
Okay, the user is asking about my training corpus, knowledge scope, and the strongest logic and skill qualities. Let me start by recalling the information I have.
First, the training corpus. details due to privacy. So I should mention that it's a diverse set of texts, including books, articles, etc., up to 2024, but not the exact sources.de exact| { | |
| "mcpServers": { | |
| "puppeteer": { | |
| "command": "npx", | |
| "args": ["-y", "@modelcontextprotocol/server-puppeteer"], | |
| "env": { | |
| "PUPPETEER_LAUNCH_OPTIONS": "{\"headless\": \"new\", \"args\": [\"--no-sandbox\", \"--disable-setuid-sandbox\", \"--disable-dev-shm-usage\", \"--window-size=1280,720\"]}", | |
| "ALLOW_DANGEROUS": "true" | |
| } | |
| }, |
Introduction:
This primer presents a comprehensive, textbook-style exploration of the mathematical foundations underlying the Universal Object Reference (UOR) and Prime Framework as described in the attached paper. Our goal is to equip the reader with deep technical mastery of all prerequisite disciplines, from fundamental definitions to advanced concepts, in a self-contained manner. We cover the following major areas, each chosen for its relevance to the UOR-Prime Template:
The Model-Context-Protocol (MCP) is an open standard introduced by Anthropic in late 2024 to enable AI systems (like large language model agents) to seamlessly connect with external data sources and tools. This report provides a deep dive into MCP’s architecture and its role in agentic workflows – multi-step, tool-using AI “agents” that coordinate tasks. We will cover MCP’s core concepts, how to develop MCP-compliant agents (both client and server sides), strategies for orchestrating multiple MCP-based agents (coordination, conversation state management, and tool chaining), ensuring interoperability and schema compliance, and finally compare MCP’s approach to other leading agent frameworks (LangGraph, CrewAI, OpenDevin, AutoGen, etc.), evaluating compatibility, strengths, and limitations.
MCP Overview: MCP is not a programming framework or a single toolchain – it is a protocol (a
Title: Toward a Deterministic, Semantic, and Dynamically Coherent LLM: Integrating Infomorphic Neurons, UOR Digest Encoding, and Hamiltonian Mechanics
Abstract
This paper introduces a unified theoretical and implementation framework for constructing advanced language learning models (LLMs) that transcend the limitations of token-based architectures. Integrating three frontier paradigms—(1) Infomorphic Neurons via Partial Information Decomposition (PID), (2) Universal Object Reference (UOR) with 512-bit Prime Digest Encoding, and (3) Hamiltonian Mechanics as a governing model of semantic trajectory dynamics—we propose a deterministic, reversible, and fully interpretable semantic engine. This triadic approach enables the construction of dynamic, on-the-fly evolving neural knowledge graphs with canonical semantic addressability, physically grounded coherence, and intrinsically lossless transformation.
Language models have traditionally relied on probabilistic token prediction, which fragments
The UORS Semantic Addressing Engine is a revolutionary framework that provides a mathematically coherent, multi-dimensional addressing system for digital objects. It enables universal, language-independent object references that remain stable across representations, languages, and domains.
This reference implementation demonstrates the core concepts of UORS using Clifford algebras, manifold structures, and coherence-based validation to create a robust semantic addressing system.
This document tracks the implementation progress of the Phase 1 MVP for our new Infrastructure as Code (IaC) architecture. The goal of Phase 1 is to implement the full core module architecture and establish functional provider modules for AWS, Azure, and Kubernetes that comply with our design principles.
Last Updated: March 18, 2025
The Prime Framework presents an innovative fusion of number theory, algebra, and geometry, proposing a novel way to encode natural numbers in Clifford algebras and interpret them within a fiber algebraic structure. While it introduces fresh perspectives on long-standing mathematical conjectures, its viability under the pressure of solving these problems must be critically assessed.
Strengths of the Prime Framework
The framework ensures a unique representation of numbers across all bases, reinforcing classical number theory results like the Fundamental Theorem of Arithmetic.
