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Would love some feedback. Goal is to expand these ideas to a book and some simulations over the next year. https://paragraph.xyz/@mirrorandloom/the-observer-paradox
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Finally made the 1k club.
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Blond:ish throws down harder at a daytime pizza joint than most djs at 3am inna club. https://youtu.be/-188i8kyTeU?si=q1-vHx1332h2Jgil
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A musical quickie: https://youtu.be/-188i8kyTeU?si=FSvI_5py2R1AezrY
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check out your Ⓜ️oxie portfolio by @degenfans
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Being a bounded observer simply means that there is some kind of information boundary between you and the rest of the world. You can only process what your senses pick up. Information is all around, but only some is processed. Even an enzyme could be a bounded observer. it only "processes meaningfully" the molecules that it orients for reaction.
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Nobody could be worse for Palestine than Biden…. Kushner: hold my Manischewitz
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Pretty much reality is the set of vectors you can access.
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Quick thoughts on a top 12 reading list, keeping here as bookmark: Godel, Escher, Bach The Mystery of Capital The Master and His Emissary Brief History of Intelligence Anti-fragile and Fooled by Randomness The Book of Why Why Information Grows The Origin of Wealth The Information A New Kind of Science The Remembered Present Flow
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Small increments in improvement generate massive results. If you can improve a model by even a small percentage, over time it will pay massive dividends.
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Play is an under-appreciated way of learning different contexts. It's low-cost, context mapping. Where accuracy is not so important, context can be more fluid.
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It seem the ability to which onchain data (or data proofs) can impact causal models is under-appreciated.
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I'll be pulling from a lot of sources like these, weaving a thread that I hope can bring all of these into clearer focus and a more intuitive understanding: *Wolfram Physics https://www.wolframphysics.org/index.php.en *Free Energy Principle (FEP) https://en.wikipedia.org/wiki/Free_energy_principle (this is a scientific, not a moral framework, btw) *Algorithmic Information Theory (AIT) https://en.wikipedia.org/wiki/Algorithmic_information_theory *Integrated Information Theory (IIT) https://en.wikipedia.org/wiki/Integrated_information_theory *Information Theory https://en.wikipedia.org/wiki/Information_theory *Complexity Theory and the Adjacent Possible (Kauffman) https://comdig.unam.mx/2023/08/28/the-adjacent-possible-and-how-it-explains-human-innovation-stuart-kauffman-ted/ *Bayesian Updating (update your priors!) https://en.wikipedia.org/wiki/Bayesian_inference *Komogorov Complexity https://en.wikipedia.org/wiki/Kolmogorov_complexity
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Attention is fuel to the fire. Be careful where you put yours.
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The patterns we see (like the laws of physics) depends on the observers we are. https://youtube.com/shorts/RtGG8uAcPig?si=0djJucEhM2JmFAeT
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Framedl PRO 2024-12-23 4/6* ⬜⬜⬜⬜⬜ ⬜⬜🟨🟨🟩 ⬜🟩🟩🟩🟩 🟩🟩🟩🟩🟩 https://pro.framedl.xyz/?id=a495de61-d958-4961-b08a-a07aa0ad13c0&app=1
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Framedl PRO 2024-12-23 4/6* ⬜⬜⬜⬜⬜ ⬜⬜🟨🟨🟩 ⬜🟩🟩🟩🟩 🟩🟩🟩🟩🟩 https://pro.framedl.xyz/?id=a495de61-d958-4961-b08a-a07aa0ad13c0&app=1
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Introduction to some of the key points I'll be diving into. https://paragraph.xyz/@mirrorandloom/the-observer-paradox
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Need to start defining some key terms that will be used throughout this work. Here's a quick "Big 12" list that'll soon be a more formal glossary, and probably a post on each: *Computational irreducibility *Computational boundedness *Combinatorial explosion *Bounded observers *Pattern recognition (multiple scales and complexities) *Recursion *Reference frames *Feedback *Compression *Confidence/reliability/fitness/trust *Context window *Energy/resources
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