has: self-operating-computer

Cognition

  • Agency
    • Willpower
    • Mindfulness
  • Intelligence
    • Problem Solving
  • Retention
    • mnemonics:
      • Mind palace
      • etc
    • Space Repetition
    • Epistemic system / noded / ensamblable knowladege
      • What I mean is to have asystem where new information can rain and pasivally find its place in your existing knowledge.
  • Retrival
    • Accesibility / Ergonomics
    • Semantic similarity
  • Embodiement
  • Plan
  • converse (augmented human interaction)

https://medium.com/tag/augmented-intelligence

Carl Jung Obsidian Ideazz

Having a carl jung taking notes next to you and coming up with great ideas what you are talking about. To search who is thinking the same than you (Social).

Open-source tools/meritocratic model for RLHF


Example
Can you return (float 0 to 1) how thought provoking are the following statements:
  • I want to eat a burger
  • I think therefore I am
  • Macbook pro price is 2300$
  • We need to use LLMs towards aiding humans with a form of augmented epistemology

It’s difficult to quantify thought-provokingness in a range of 0 to 1, as this is subjective and depends on the individual’s interests and background knowledge. However, I can attempt to give a rough estimate for each statement.

  1. I want to eat a burger: 0.1
    • This statement is more of a personal preference or desire and doesn’t bring up any deep or philosophical ideas.
  2. I think therefore I am: 0.8
    • This famous philosophical statement by René Descartes touches on the nature of existence and consciousness. It is a classic thought-provoking idea that has inspired much discussion and debate.
  3. Macbook pro price is 2300$: 0.05
    • This statement is a simple fact and does not provoke much thought beyond the cost of an electronic device.
  4. We need to use LLMs towards aiding humans with a form of augmented epistemology: 0.7
    • This statement discusses the potential application of large language models (LLMs) in enhancing human understanding and knowledge acquisition. It can be thought-provoking for those interested in artificial intelligence, ethics, and the future of human-computer interaction.

Please note that these scores are only rough estimates and might differ significantly based on an individual’s background and interests.


Chains Modules 🦜🔗
  • Construct Goal
  • split in subtasks
  • assign probabilities
  • error handling
  • split strategies
    • Test different paths and test them simultaneously
  • Ask for help?
  • Offer options to human driver
  • Check scientific literature
  • Plot info
  • Bayesian Reasoning

Augmented Cognition 🦜🔗 + 🧠 | Bayesian Reasoning | ONLY invested participants

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