Show HN_Mnemosyne: A 10^38 Joule Thermodynamic Barrier for Post-Quantum Edge AI

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Mnemosyne: A blueprint for computational pluralism via physical laws. -Security: Establishes a 10^38 Joule physical floor (kappa >= 804 bits) derived from Landauer’s Principle and the Margolus-Levitin limit. Infrastructure: Targets 2GB RAM edge devices using BFT-MESI cache coherence. -Verification: Formally specified in TLA+; preliminary TLC verification completed for minimal configurations (n=4, f=1). -Economics: Proof of Useful Work (PoUW) for socially beneficial AI compute. -Current Openings: Seeking PhD positions (Security/Distributed Systems). Providing RAG architecture consulting. -Full Manuscript (175 pages, 14 original theorems): https://www.researchgate.net/profile/Bo-Jun-Han -LinkedIn: www.linkedin.com/in/hbjun

Visit product View on Hacker NewsMar 28, 2026

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nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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Product HuntUnlikely to reach the leaderboard · Strong signals: physical, using, open · Missing: mac, agents, macos

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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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