Wisdom Architecture: An Adaptive Layer for Cognitive Augmentation and Safer AI

Project summary

Our "Wisdom Architecture" project represents a revolutionary step in the development of artificial intelligence. We are developing an innovative wisdom layer that can be integrated into existing AI models, significantly expanding their cognitive capabilities and ensuring safer and more ethical functioning. This system will likely allow for identifying connections that were not obvious before, potentially leading to discoveries in various fields.

Key aspects of the project:

1. Holistic approach: Our AI examines any question holistically, from different angles, penetrating to the very essence of things.

2. The art of wise reflection: We train AI to see interconnections, understand context, and consider various perspectives.

3. The "seed" principle: Following ancient wisdom, we strive to understand the universe through understanding the structure of a seed, applying this approach to AI.

4. Adaptive layer: The layer we are developing can be added to regular models, making them wiser and more capable of solving complex tasks.

5. Safe AI development: We believe that wise AI is the key to the safe development of future technologies, including potential superintelligent AI (ASI).

6. Innovation: The frames through which we will process this model can help it find innovative solutions to problems and solve tasks that have not been solved before.

7. World model and synthetic data: This project involves creating synthetic data in the form of context around a user's question, which will allow for a more complete picture of the world in synthetic data.

What are this project's goals? How will you achieve them?

Goals:

1. Develop an adaptive wisdom layer for integration with existing AI models

2. Improve AI's ability for deep, contextual analysis

3. Ensure safer and more ethical AI functioning

4. Teach AI to see consequences and important elements within tasks

5. Develop AI's ability to create new ideas based on existing knowledge

Achievement strategy:

- Further train the model based on principles and frames of wise thinking

- Implement the ability to "reveal context and task" before processing a question

- Develop algorithms for analyzing consequences and identifying key elements

- Create mechanisms for generating new ideas based on existing knowledge

- Integrate ethical principles into AI decision-making processes

How will this funding be used?

Minimum funding amount (10,000 USD):

The first and minimum stage is creating a data layer for training AI in wisdom. These funds will be directed towards developing training data that will allow for creating safer AI. This AI will be wise and will make quality decisions not only based on external constraints but also from internal beliefs and "understanding of morality embedded in it". The funding will be distributed as follows:

- 50% for collecting, processing, and structuring data on wisdom and ethical decision-making

- 20% for developing algorithms to integrate this data into existing AI models

- 25% for computational resources and infrastructure

- 5% for project management and administrative expenses

*the amount includes payment for specialists to work with the data

Maximum funding amount (20,000 USD):

Upon reaching the maximum funding amount, we will be able to implement the second stage of the project, which includes creating an agent network and developing the futurological aspect of AI. This network will be aimed at studying any phenomenon from several angles and delving into the question to the extent that new creative solutions can be found in this area, bringing us closer to discoveries from AI. Moreover, we will focus on developing AI's ability to predict and analyze future trends, which is critical for making wise long-term decisions. The distribution of funds will be as follows:

- 15% for collecting and processing an expanded dataset for model training

- 40% for research and development of algorithms for the adaptive wisdom layer and agent network

- 25% for computational resources and infrastructure for large-scale experiments

- 15% for testing, model validation, and conducting pilot projects

- 5% for project management, interaction with external experts, and administrative expenses

Achieving the maximum funding amount will allow us not only to create a basic wisdom layer for AI but also to develop a more complex system capable of generating innovative ideas and potentially making scientific discoveries. This will significantly expand the project's capabilities and its potential impact on the development of safe and creative AI.

Who is on your team? What's your track record on similar projects?

Our interdisciplinary team includes:

1. Thinking Researcher

- 15 years of experience in marketing technologies and product development

- Developed a successful startup in Proptech

- Created successful MarTech products in Proptech companies

- 15 years of studying thinking, developing own models of thinking development

- Author of 5 books on thinking and wisdom development (https://a.co/d/5wEKOWw)

2. Technical Specialist

- Developed algorithm for trading machines

- Expert in machine learning and multi-agent systems

- Created an algorithm for compressing models tenfold with minimal quality loss

- Developing an agent system for marketing automation Mark 0.01 (https://youtu.be/gPHhy9kKgD0?si=4ZQN_XzKhJn1-Y1X)

3. AI Engineer

- Development of new marketing analytics systems

4. Additional recruited experts in philosophy and neurobiology

Our team has begun the first stage of the project, developing a conceptual model and conducting preliminary experiments demonstrating the potential of our approach. We have published the results of our first tests on working with wisdom in AI, where you can see how it reflects on the trolley problem, demonstrating a wise position: https://www.linkedin.com/pulse/exploring-wisdom-our-experience-customizing-language-model-anton-yqqye

Furthermore, we are actively researching the concept of wisdom in AI, as evidenced by our article: https://www.linkedin.com/pulse/consciousness-wisdom-artificial-intelligence-path-deep-kalabukhov-qmc6e

Our approach is based on a deep understanding of the principles of thinking development and wisdom, as outlined in the book: https://a.co/d/5wEKOWw

This experience and expertise allow us to uniquely approach the development of wise AI, combining theoretical knowledge with practical experience in technology and business.

What are the most likely causes and outcomes if this project fails?

Potential causes of failure:

- Difficulties in formalizing wisdom concepts for machine learning

- Technical challenges in integrating the wisdom layer with existing AI architectures

- Insufficient data for effective model training

- Complexity in verifying tests for the level of "wisdom"

- Technical complexity in model tuning