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description cover coverY
Tomorrow belongs to those who can hear it coming. — David Bowie ../.gitbook/assets/cover/predictoor_banner.jpg 0

Summary

We dream of a world of 10,000 truly accurate prediction feeds, for everything from rain forecasts to sea level rise, or traffic congestion to ETH price. Ocean Predictoor is an on-chain, privacy-enabled, AI-powered application and stack that is bringing this dream to reality.

Accurate predictions are valuable. With them, one can take action and create value. Conversely, inaccurate predictions lead to disaster. Predictions have value because they're the final step in a data supply chain, right before action is taken by the user.

Prediction feeds are a stream of predictions for a given time series. This could be predicting the price of ETH every 5 minutes, or the sea temperature daily. A feed may be binary, i.e. whether a time series changes up or down: ↑↓↓↓↑↓↑↑. Accurate prediction feeds are valuable.

Alas, accurate predictions are hard. Worse, typical prediction feeds have no accountability on accuracy. If the weatherman says "no rain for today" and then it rains, a farmer could get stuck in the mud, wrecking a portion of his crops. The weatherman doesn't feel the impact of wrong predictions, but the farmers sure care! 

Accountable Predictions - Imagine if there was accountability. Accuracy would go up; the farmer would be stuck less. Imagine accountable prediction feeds for not only for rain, but also wind, sea temperature, road congestion, train delays, ETH prices, NVID prices, housing prices, and more. Imagine tens of thousands of prediction feeds with accountable accuracy. Imagine them globally distributed, and censorship resistant. Imagine accuracy improving with time.

Introduction

Ocean Predictoor is a stack and a dapp for prediction feeds. It has accountability for accuracy, via staking. Its globally distributed and censorship-resistant, by being on-chain. We expect its accuracy to improve over time, due to its incentive structure. Its first use case is DeFi token prediction because users can close the data value-creation loop quickly to make tangible $.

Predictoor is composed of different actors, often referred to as: predictoors and traders. You will learn in the Predictoor Introduction page, you will out more about these actors, how they are structured in the system, and their behaviors. By the time you've completed reading this, you'll know what Epochs are, and have a better understand of what "t+1" means.

Architecture

After obtaining a broad overview of the system and its actors, you should be ready to dive into The Architecture of Predictoor and the pdr-backend repo. You'll become more exposed to the key building blocks and pdr-backend, the integration component for Predictoors and Traders.

We anticipate Predictoor to extend beyond DeFi to other verticals like climate and agriculture. Predictoor agents may evolve into AI DAOs with emergent swarm-like behavior. This is the future.

Earning with Predictoor

Predictoor serves two groups of actors: Predictoors, and Traders. In this section, we'll explore How to Earn with Predictoor and describe how both of these groups can benefit from it. After you are done with this, you should know what steps you need to take next in order to start leveraging the system for your own benefit.

We'll also provide some links and exercise to make this easier for you.

Predictoor Parameters

The Predictoor Parameters page will provide you with details on many topics such as incentives, feed costs, and deployed feeds.

You can find details about Oasis, Testnet, Mainnet, and how to bridge your OCEAN here.

FAQ

The FAQ page has frequently asked questions about Predictoor.

Connect with Us

If you want to talk to other Predictoors, Traders, and contributors to this ecosystem, join us on Discord.

Predictoor Resources

Main:

Intro:

  • These docs are the best starting point to learn about Predictoor:)
  • Original blogpost "Meet Predictoor", Sep 12, 2023 [Link]
  • Original talk "Introducing Prediction Feeds", Dappcon, Sep 12, 2023 [Video][GSlides][PDF]

For thoroughness: