Prediction Markets Beyond Crypto
Build New Markets Around Real World Predictions
What it does
Prediction Markets Beyond Crypto is developed for businesses exploring market-based forecasting beyond traditional crypto applications. It focus on transforming prediction market concepts into practical digital platforms that help organizations evaluate uncertainty, surface collective insight and support more informed decisions across complex real world scenarios.
Discover how prediction market development is creating new opportunities across 7 industries through forecast-based trading beyond crypto.
Prediction markets were largely associated with cryptocurrency communities and political forecasting for many years. Today, that perception is rapidly changing. Businesses across multiple industries are exploring forecast based trading platforms to improve decision making, engage users and create new digital revenue sources Powered by blockchain, smart contracts and decentralized infrastructure, modern prediction market platforms allow participants to trade on the outcomes of future events. These events can range from sports matches and financial markets to supply chain interruptions, weather conditions and AI generated forecasts. As organizations increasingly rely on collective…from bidbits.org
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Commerce · 26d ago · equitybee.com
Launched alongside, August 2026
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Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com