DeepThought AI – Give your Python 'if' statements an AI boost

Hacker News

DeepThought AI is a satirical Python library that gives your humble 'if' statements an absurd AI upgrade. It transforms simple boolean logic into an over-engineered, GPU-hungry decision engine. Key features: - Neural Network If-Else Evaluator (10-billion parameters) - AI-Powered Condition Analyzer - Parallel Universe Simulation for each decision This tongue-in-cheek project pokes fun at AI hype, startup culture, and the trend of applying complex solutions to simple problems. It claims to increase your chances of achieving unicorn status by 1000-fold!

Visit product View on Hacker NewsJul 17, 2024

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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Hacker NewsMay not resonate with HN audience · Strong signals: lua, 000, io · Missing: https docs, excited, just released

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

21%21% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

15%15% 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

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

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