PowerPool’s Solution Bridges AI Decision-Making and On-Chain Execution winning bounty at dAGI Hackathon
In Brief
The AI Hands team won a prize at the dAGI hackathon, demonstrating PowerPool’s DePin network for executing AI Agents’ decisions on-chain, positioning it as an “execution hand.”
The AI Hands, a PowerPool-powered team has recently won one of the bounties on the dAGI, the AI-focused hackathon.
The AI Hands team demonstrated how to utilize PowerPool’s DePin network for executing decisions of AI Agents in the form of on-chain transactions. The core concept behind their winning entry was to position PowerPool as an “execution hand” for better operation execution on AI queries and generated triggers.
PowerPool offers Transaction Execution as a Service using its DePIN network of Keeper bots. These bots automatically carry out on-chain transactions in response to both on- and off-chain triggers. If we are talking about Web3 AI agents, PowerPool is an essential tool that allows to execute AI Agents’ decisions on-chain.
The Winning Solution from AI Hands
For the hackathon, the AI Hands team created a product that executes (in the form of on-chain transactions) trading decisions made by POND.
The POND is a decentralized AI project offering price change predictions for a certain set of tokens on top of on-chain data analysis. Currently, the price changes are predicted at hourly intervals.
Since both a price prediction and a metric of the model quality are available, this allows one to create a custom trading strategy using POND as a data provider. Here, we outline a simple example of such a strategy, namely, the problem of managing a two-token portfolio, where swaps are only allowed between the tokens of the portfolio, and one of those tokens is a stablecoin.
The algorithm comprises a single decision-making resolver function and utilizes PowerPool’s Keeper network. The process launches by invoking the POND API to obtain model metrics, with trend accuracy chosen as the target metric due to the hourly prediction interval allowing for linear approximation.
Take a look at the principal scheme of the PowerPool’s off-chain resolver:
The algorithm incorporates safeguards to ensure the reliability of its decisions. If the current model’s accuracy falls below a certain threshold, the results are discarded, and the execution instance terminates. Conversely, if the accuracy exceeds the threshold, the POND API is called again to obtain predictions for the non-stable token in the pair, along with the current price.
In order to refine the decision-making process, the algorithm evaluates the projected change of the non-stable token in relative units. If this change falls below a user-specified threshold, the results are again discarded, as minimal changes may not justify the risk or costs associated with a swap.
Here is the operational process of AI Hands:
The Takeaway for the Future of the AI Sector
AI Agents operating in Web3 need someone to execute their decisions on-chain in the form of transactions. Examples are token swaps, token bridging, Defi strategies execution, and many more.
In order to attract attention to this problem, PowerPool team members created a team called specifically the “AI Hands” and showcased an efficient solution for the AI transaction execution problem. This solution won a bounty at POND track at dAGI hackathon, demonstrating traction and positive response from AI builders and judges.
An ambitious agenda has been proposed by PowerPool for the second half of 2024. The team’s main goals will be to integrate new projects into the ecosystem and extend the PowerAgent DePIN layer over more Layer 2 systems, with a core focus on supplementing Web3 AI protocols with automatic transaction execution.
In the coming months, PowerPool plans to make its presence felt at major industry events, including Korea Blockchain Week and Singapore Token2049. The company will co-host Hack Season Conference and Builders Bootcamps.
During this time, PowerPool will also be launching its CVP Staking program, which will provide additional chances for audience involvement and engagement. The company has also organized many partnership activities with AI Agent protocols and co-marketing campaigns with Layer 2 ecosystems in an effort to promote cooperation and accelerate the uptake of their innovative products.
With its recent hackathon success and ambitions, the PowerPool team and community are continuing to push the frontiers of what is possible at the intersection of blockchain technology and artificial intelligence. These developments point to a promising future for the firm and the larger Web3 ecosystem.
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About The Author
Victoria is a writer on a variety of technology topics including Web3.0, AI and cryptocurrencies. Her extensive experience allows her to write insightful articles for the wider audience.
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Victoria is a writer on a variety of technology topics including Web3.0, AI and cryptocurrencies. Her extensive experience allows her to write insightful articles for the wider audience.
