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PancakeSwap's New AI Prediction Market Goes Live on Arbitrum

Key Takeaways

  • PancakeSwap launches an AI-powered prediction market in collaboration with Allora Network, allowing users to bet with or against AI price predictions;
  • The AI models introduce a new dynamic to PancakeSwap's prediction market;
  • The AI-powered market will adjust payouts based on AI performance, with higher rewards for predicting against the AI when its accuracy is low.
PancakeSwap's New AI Prediction Market Goes Live on Arbitrum

PancakeSwap, a leading decentralized exchange (DEX), has introduced a new artificial intelligence (AI)-driven prediction market on the Arbitrum network through a partnership with Allora Network.

This new feature will use Allora's advanced machine learning to provide price feed data, enhancing the user experience in forecasting Ether (ETH) price movements.

Traditionally, PancakeSwap's prediction market allowed users to bet on whether the price of ETH would rise or fall within a 20-minute window. In this updated version, users will have the opportunity to make their predictions either in alignment with or against AI-generated forecasts. 

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The Allora team emphasized their impressive track record, noting that their predictive models have accurately forecasted prices for over 400 million assets with a confidence level of 95-99% for the most accurate predictions over the past three years.

Chef Gyoza, Product Manager at PancakeSwap, expressed enthusiasm for the collaboration, stating:

We're excited to integrate Allora's AI models into our prediction market. Now our users can test their prediction skills against AI, which will create another exciting form of prediction for our users.

Allora's AI models will forecast the likelihood of various crypto asset prices rising or falling within the next 20 minutes. Users can choose to predict in agreement or disagreement with the AI's predictions.

The payout structure will adapt based on the AI's accuracy over time, offering higher rewards for users predicting against the AI when its accuracy dips, and lower rewards when the AI performs well.

Addressing concerns about potential market manipulation, Chef Gyoza assured that various measures are in place. Users can access histories of rounds, price feeds, and AI predictions through a dedicated tab on the prediction page. Furthermore, results are settled on-chain via the platform's prediction v2 contract.

Gyoza also commented on the impact of the prediction market on liquidity and volatility within PancakeSwap, explaining:

At the moment, we don’t think that it'll influence the market to a large extent, as it's still a nascent product. However, we believe that with Allora as a partner, we can expand the predictions to many other markets, both on and off-chain.

The new development is set to bring a fresh, AI-driven twist to PancakeSwap's users and demonstrate the transformative potential of AI in DeFi.

In other news, another DEX, Uniswap, has recently acquired the on-chain game "Crypto: The Game" as it prepares to launch its third season.

Aaron S. Editor-In-Chief
Having completed a Master’s degree in Economics, Politics, and Cultures of the East Asia region, Aaron has written scientific papers analyzing the differences between Western and Collective forms of capitalism in the post-World War II era.
With close to a decade of experience in the FinTech industry, Aaron understands all of the biggest issues and struggles that crypto enthusiasts face. He’s a passionate analyst who is concerned with data-driven and fact-based content, as well as that which speaks to both Web3 natives and industry newcomers.
Aaron is the go-to person for everything and anything related to digital currencies. With a huge passion for blockchain & Web3 education, Aaron strives to transform the space as we know it, and make it more approachable to complete beginners.
Aaron has been quoted by multiple established outlets, and is a published author himself. Even during his free time, he enjoys researching the market trends, and looking for the next supernova.

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