HomeEthereumPancakeSwap Deploys AI-Based Ether Prediction Market in the Arbitrum Ecosystem

PancakeSwap Deploys AI-Based Ether Prediction Market in the Arbitrum Ecosystem


PancakeSwap has launched a new prediction market on Arbitrum in collaboration with Allora, an AI and ML firm. With that, PancakeSwap lets users bet on crypto prices, with price feeds delivered directly to the platform.

The novelty comes from Allora’s AI integration, the AI assisting users in making the right bets by guessing which way the price of a digital asset will swing. This is not Allora’s first rodeo in the predictions market—it has been integrated Into such platforms for various asset types, depicting prediction accuracies between 95% and 99% for some asset types.

PancakeSwap’s product manager, Chef Gyoza, spoke about how this platform will work, “PancakeSwap users will be able to follow or oppose the AI’s prediction. With the AI’s performance and record in our tests achieving close to 65% accuracy, users must choose when to oppose the AI, which will naturally have higher odds.” Allora’s AI model will only improve with time, with payouts adjusted with its prediction accuracy.

Presently, Arbitrum users can predict Ether prices, harnessing price feeds sourced straight from Allora. Users can bet on more assets once they make their way to the platform.

Of course, with any product like this, users worry about market manipulation. However, its transparency and reliance on chains like Arbitrum and smart contracts to execute payouts based on users’ predictions prevents any manipulation.

Gyoza added, “Users can track all round history, price feed history, and AI prediction history via a history tab on the prediction page. All results are also settled on-chain via our prediction v2 contract.”

PancakeSwap is now relying heavily on AI-based technologies to offer unseen use cases to blockchain and DeFi users. It recently partnered with Bril Finance to deploy a portfolio management application that leverages AI to enhance risk management and tailor investment strategies based on the user.

Image by Gerd Altmann from Pixabay


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