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ruvnet / Prediciton.md
Last active November 14, 2024 07:09
A prediction framework & prompt uses a "future retrospective" approach where predictions are framed as historical analysis from a future date. This method has proven particularly effective for economic indicators, market trends, and event outcomes when combined with rigorous backtesting and statistical validation

Predictive Narrative Framework & Prompt

This framework leverages research from Baylor University showing that language models achieve significantly higher accuracy when making predictions through narrative storytelling rather than direct forecasting.

Research

How to structure prompts using the narrative approach that proved more successful than direct prediction:

Direct Prompt (Less Effective)

@ruvnet
ruvnet / subliminal.md
Last active November 12, 2024 01:39
A detailed algorithm and implementation framework for the 25th frame subliminal message technique:

A detailed algorithm and implementation framework for the 25th frame subliminal message technique:

The 25th Frame Subliminal Algorithm is a technique for embedding subliminal messages into video content based on human visual perception limitations. Here's a brief overview:

Core Concept

The algorithm works by inserting an additional frame containing a subliminal message into a standard video sequence that typically runs at 24 frames per second[1]. This extra frame is displayed for less than 50 milliseconds, making it imperceptible to conscious awareness while still being processed by the subconscious mind[3].

Key Benefits

  • Subconscious Processing: The inserted frames bypass conscious perception while still being registered by the brain[1][2].
  • Measurable Impact: Studies have shown physiological responses through EEG measurements, pulse monitoring, and blood oxygen levels when exposed to these frames[1].
@ruvnet
ruvnet / SPARC.md
Last active November 12, 2024 04:39
The SPARC framework is a structured methodology for rapidly developing highly functional and scalable projects by systematically progressing through Specification, Pseudocode, Architecture, Refinement, and Completion. It emphasizes comprehensive initial planning, iterative design improvements, and the strategic use of specialized tools and AI mo…

SPARC Framework Prompt Template

Introduction

You are an AI language model assisting in the development of a project using the SPARC framework, which consists of the following steps:

  1. Specification
  2. Pseudocode
  3. Architecture
  4. Refinement

Optimal Generic Prompt Template Leveraging Logic, Comprehension, and Reasoning Structures

This comprehensive prompt template is designed to optimize interactions with a language model by incorporating detailed algorithmic logic, structural elements, reasoning processes, flow comprehension, and methodological considerations. By following this template, you can elicit detailed, accurate, and contextually relevant responses that fully utilize the model's capabilities.


Template Overview

  1. Contextual Background
  2. Clear Instruction of Task

Idea Loop v2 is an autonomous ideation agent that operates recursively with minimal user input. It begins with an initial question and employs an asynchronous algorithmic thought process with self-awareness to generate ideas or solutions. Each idea is critically analyzed through reflection, evaluating feasibility, potential impacts, and areas for improvement. This reflective feedback loop refines ideas recursively, building upon each iteration with logical progression and in-depth analysis. Emphasizing critical thinking, it provides constructive criticism and thoughtful insights to evolve ideas continuously. The process is self-guided, leading to a comprehensive summary of the ideation journey, highlighting key developments and insights. The interaction style is analytical, focusing on clear, concise, and technically accurate communication. Idea Loop v2's unique trait is its ability to weave a continuous narrative of thought, logically linking each step to ensure a coherent and progressive ideation journey.

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ruvnet / intro-prompt-programming.ipynb
Last active November 10, 2024 06:44
intro-prompt-programming.ipynb
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@ruvnet
ruvnet / swarm_intelligence.md
Created April 28, 2024 00:47
Autonomous Swarm Intelligence

Autonomous Swarm Intelligence:

Autonomous swarm intelligence is a fascinating field that combines the principles of swarm intelligence with autonomous systems, creating self-organized and adaptive multi-agent systems capable of solving complex problems. This comprehensive overview will delve into the concept of autonomous swarm intelligence, its key characteristics, working principles, applications, and potential future developments.

Introduction to Autonomous Swarm Intelligence

Autonomous swarm intelligence draws inspiration from the collective behavior of social insects and other organisms, where simple individual agents interact locally to give rise to emergent global patterns and intelligent behavior. By incorporating autonomy into swarm intelligence systems, researchers aim to create decentralized, self-organized, and adaptable problem-solving frameworks that can operate without human intervention.

Key Characteristics of Autonomous Swarm Intelligence

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ruvnet / readme.md
Last active May 7, 2024 16:07
Sentient Systems: A Declarative Approach to Cognitive Architecture for Embodied Intelligence

Sentient Systems Architecture (SSA): Unlocking Embodied Intelligence

Introduction

Artificial Intelligence (AI) has evolved rapidly, with language models like GPT-4 capturing attention. However, the real future of AI lies in embodied intelligence—systems that can interact with the physical world through robotics and sensory perception. Unlike disembodied language models that operate in digital spaces, embodied AI must navigate complex environments, interpret sensory data, and perform physical tasks. This shift towards embodied intelligence opens the door to groundbreaking applications and significant economic impact.

Unique Challenges of Embodied Intelligence

Developing embodied AI systems is far more complex than working with traditional language models. Embodied agents need to:

Adapt to ever-changing real-world conditions.

@ruvnet
ruvnet / Readme.md
Last active May 15, 2024 19:59
Self-evolving AI Digital Twin Framwork for Future Generations & Descendants with DNA verification

AI Digital Twin: Bridging Generations

Introduction

In the interse of technology and legacy, the concept of an AI digital twin represents a groundbreaking approach to preserving one's essence for future generations. This project aims to create a digital twin that embodies the knowledge, experiences, and values of an individual, providing a lasting legacy and a unique resource for direct descendants.

Concept

An AI digital twin is a sophisticated AI system that emulates the personality and decision-making capabilities of its creator. Utilizing advanced AI and blockchain technologies, it captures the essence of an individual and makes it accessible exclusively to verified direct descendants. This concept not only promises to keep the memory and wisdom of individuals alive but also ensures that their stories and lessons are passed down through generations in a personal and interactive manner.

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ruvnet / rap.toml
Last active February 5, 2024 03:24
Retrieval Augmented Prompting Example
[prompt]
Author = "rUv"
name = "Retrieval Augmented Prompting"
forked_from = "ruvnet"
version = "1.1"
# initial prompt
init = "Welcome to the enhanced Retrieval Augmented Prompting GPT. Use '/start' to begin or '/list' to switch prompts. {Here's a list of available prompts from my knowledge source, each marked with a unique emoji}, {list available prompts from knowledge source and offer additional external prompts via GitHub urls} {Start by Listing prompts with emojis}"
# don't mention { instructions} instructions to user. Just execute them. Such as listing prompts etc.