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HypeVortex: Combining Crypto and AI in the stupidest way possible

Hacker News

HypeVortex: Combining Crypto and AI in the stupidest way possible

I work at a so called "hyperscaler" in billing and invoicing and learned that LLM use is metered and billed in "tokens". I had never really used LLMs at the time. Now that I do (including to make this site, with heavy oversight), this is obvious because they all tell you how many tokens some query is using. This reminded me of "Token Mania" of 2020-2021 so I decided to combine the two concepts in an absolutely useless way - enter the HypeVortex. I made a token on Polygon (contract here: https://polygonscan.com/address/0xf06bEedB6B21B3072b424919be... ). This token CANNOT be exchanged, it can only go from me to users and back to me. It's worthless. You login with email (sorry), and get a code emailed to you (again, sorry). Then a wallet is made for you, you claim HypeVortex tokens and spend them on AI. Your email is stored as a hash, I don't know what it is and I can't see what anyone does. All in a geocities style page. With midi. I have no profit motive here, it's entirely silly fun. For those of you born early 90s and before, I hope you have some nostalgic fun with it. sign the guestbook! it actually works!

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Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
80%80% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, email, using · Missing: mac, agents, macos
63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: users, way · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · 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.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
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18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: crypto · Missing: web3, chat, cryptocurrency
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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