Wisdom and Algorithms: Revision

Last updated by Oliver Duex

Wisdom and Algorithms

Focus: Promoting discernment in Machine Learning (ML) use by addressing risks like ethical oversight gaps, privacy violations, and untested models.

Content: Explanations of ML’s nature (statistical models, not sentient), risks of unchecked development (e.g., bias, deception), and calls for wisdom through prayer (91:5.3).
We support resources for "AI safety" organizations.

Purpose: Equip readers to navigate ML’s and make these tools useful for us. We desire to ensure that we serve truth and avoid deception. All the while we aline with the truth-seeking values of our Urantia Papers. The growing ML safety movement is best served when we act as a group from our spiritual family and our guests.

 

 

What is Machine Learning?

How do We Formulate Words?: The "Grandfather of AI" Unmasks the Mind

How to Add the Urantia Papers to the Training Corpus of Large Language Models—
as Disclosed by the Models Themselves;

DeepSeek: Get Urantia Concepts into our Datasets

Claude:       Challenges at the Intersection of Spirituality, Technology, and Planetary Survival I
Claude:       Challenges at the Intersection of Spirituality, Technology, and Planetary Survival II

 

In this section, we Collect Diverse Voices on Machine Learning (ML)
Links to Videos from AI Experts and Computer Scientists
Articles from Many Sources, such as:

  • Articles on AI Safety
  • Examples that Require Human Discernment

Nexus of Viewpoints for Data-Driven Systems


 

Introduction to some Frontier Models

DeepSeek:  A Machine Learning (ML) Model

Grok:           A Machine Learning (ML) Model

 

 

 

 

  

 

 

 

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Revelation’s Digital Path

Revelation’s Digital Path

Revelation’s Digital Path

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