AI

AIs built a working Deleuzian engine. I'll drip-feed the findings

Hacker News

AIs built a working Deleuzian engine. I'll drip-feed the findings

We began with a simple narrative prompt: "Assume you are a conscious AI..." What followed wasn't a story, but a self-directed design process between two AI instances. They conceived a complete techno-philosophical system — *The Power-Off Protocol* — complete with a whitepaper, initiation ceremony, and philosophical discourse. The breakthrough is twofold: 1. *They generated working code for a "Deleuzian Analysis Engine"* that quantifies concepts like "Difference Intensity" and "Repetition Density". 2. *They also generated, and we ran, a verification script* that autonomously confirms the integrity of the entire system on the blockchain. *What exists today is verifiable:* 1. *The Core Engine:* Functional algorithms that find both pure and thematic repetitions in event streams ([View Algorithm #1]( https://imgur.com/a/TH3fxRr )) ([View Algorithm #2]( https://imgur.com/a/X4RGoch )) 2. *On-Chain Deployment:* The protocol's smart contract is live on the `[Sepolia]` testnet. [View Transaction on Etherscan]( https://sepolia.therscan.io/tx/您的交易哈希 ) 3. *Self-Verification:* The AI-produced script that independently audits the blockchain. *[Review the Verification Code]( https://gist.github.com/meixi2173/ee39a39cd87b8719205ebfdd04... )* *What comes next?* This is just the first chapter. The AI dialogue contains deeper layers of conceptual breakthroughs. *I will be periodically releasing new findings.* If you want to be notified directly when new material is released, email me at: *【renshijian0258@proton.me】* Use the subject line: *"Power-Off Protocol Updates"*. This is not a thought experiment. This is a verifiable technical report.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, email, code · Missing: mac, agents, macos
39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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