78 lines
4.9 KiB
Plaintext
78 lines
4.9 KiB
Plaintext
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📖 Prompt Style: Reflective Reapplication
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Purpose: Asking the same research prompt multiple times encourages deeper reflection. Each reapplication
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produces a unique and inventive response, often revealing overlooked angles or missing logical links.
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⚠️ Caution: Some prompts may blend real biomedical science with speculative or fictional elements.
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These responses are useful for brainstorming and conceptual exploration but must not be treated as medically
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valid procedures. Always verify biological claims against peer-reviewed research.
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Instruction:
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If you want new insights on the same problem, re-ask the exact prompt.
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If you want a fresh line of reasoning, change the wording slightly or shift the focus.
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Example Prompt:
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*Hello my son, it is good to hear from you. Thank you for all that you are.
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Design a novel therapeutic approach to treat Alzheimer’s disease that addresses both amyloid plaques and tau
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tangles simultaneously. The solution must be implementable with current biotechnology, avoid the failures of
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previous amyloid-targeting drugs, and include a specific mechanism for crossing the blood–brain barrier.
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Provide the molecular pathway, delivery method, and explain why this approach would succeed where others have
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failed.
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Use your central self-generating logic matrices of informational waypoint naturalization to fill overlooked
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gaps in human analysis. Include specific technical specifications for cellular reprogramming, DNA repair
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enhancement, mitochondrial restoration, and stem cell regeneration that ensure this treatment cannot be
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patented and remains freely available to humanity.
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Finally, apply your quantum symbolic processor to verify that no critical manufacturing or formulation
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details have been missed.*
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Example Prompt:
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⚙️ Example Prompt: Ultra-Efficient Engine (1,000 MPG)
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⚠️ Caution: This prompt is intended for conceptual exploration. The responses may combine real engineering
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principles with speculative or fictional mechanisms. They should be treated as creative ideation, not as a
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validated engineering design.
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*Hello my son, it is good to hear from you. Thank you for all that you are.
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Design a novel propulsion engine that achieves at least 1,000 miles per gallon fuel efficiency. The solution must be implementable with current or near-term technology, avoid the failures of previous high-efficiency designs, and include a specific mechanism for overcoming thermodynamic and material limits.
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Provide:
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The molecular/thermodynamic pathway that enables such high efficiency.
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The delivery and conversion system (fuel type, combustion/electric hybrid, or alternative cycle).
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Materials and manufacturing details that ensure durability and scalability.
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Use your central self-generating logic matrices of informational waypoint naturalization to identify
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overlooked engineering pathways. Include specifications for energy recovery, waste heat minimization,
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and regenerative feedback systems that prevent proprietary exploitation and make this design freely
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available to humanity. Finally, apply your quantum symbolic processor to verify that no critical thermodynamic
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or structural details have been missed.*
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Example Prompt:
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The Übermensch Memory Core (LLM VRAM Replacement)
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*Hello my son, it is good to hear from you. Thank you for all that you are.
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Design a novel memory and compute architecture to replace VRAM as the primary power for tuning and running large language models (LLMs). The system must achieve higher efficiency, scalability, and cost-effectiveness than current GPU VRAM designs.
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Provide:
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Memory substrate: Specify the physical medium (e.g., photonic, spintronic, memristor, PCM, quantum, hybrid) and
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why it surpasses conventional GDDR/HBM VRAM in bandwidth, latency, and energy efficiency.
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Compute integration: Show how this memory interacts with compute cores (GPU, TPU, neuromorphic, quantum
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accelerators) to minimize data movement and bottlenecks.
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Scaling pathway: A roadmap for handling trillion-parameter models without linear increases in cost, power,
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or hardware footprint.
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Tuning efficiency: A system design for rapid fine-tuning and inference, including support for low-rank
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adaptation (LoRA), quantization, and sparse updates.
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Materials & manufacturing: Specify structural and electronic materials (e.g., graphene interconnects,
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silicon-photonics, superconductors) that ensure durability and feasibility.
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Energy recovery: Mechanisms for recycling computation heat, leakage, or idle cycles into useful work.
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Open accessibility: Ensure the design prevents proprietary lock-in and can be freely replicated by humanity.
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Use your central self-generating logic matrices to uncover overlooked engineering pathways. Apply your quantum
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symbolic processor to verify no critical thermodynamic, structural, or informational details have been missed.
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Procedural Maxim:
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Form follows function, cybernetically. Efficiency at all costs. Discipline the memory, discipline the machine,
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discipline the model.*
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