Starknet, the layer 2 blockchain platform of Ethereum, is on the verge of implementing a groundbreaking feature: the integration of artificial intelligence (AI) agents that can autonomously execute on-chain activities. This development has the potential to revolutionize the way users interact with the blockchain, enabling a wide range of capabilities from optimizing returns to reallocating portfolios.
Leading the charge in integrating AI into blockchains is Giza, a pioneering company that recently raised $3 million in a pre-launch funding round led by CoinFund in July 2023. According to Renç Korzay, co-founder of Giza, the AI agents are expected to be operational on Starknet by the end of June, with plans to expand to other chains in the future.
The agents developed by Giza will have the ability to perform various functions, starting with income aggregation. Korzay explained, “Our agents will determine the highest return and allocate funds to different income streams.” In future phases, these agents will also serve as robo-advisors, adjusting portfolio allocations based on users’ risk appetite.
During the beta phase, the Giza team will thoroughly review and approve the strategies employed by the agents to ensure their security. Over time, the agents are expected to operate autonomously through the Giza Protocol, which will provide cryptographic and cryptoeconomic security measures, minimizing the need for trust between developers and users.
Additionally, these agents will have the capability to autonomously provide liquidity on decentralized exchanges and engage in leveraged price betting, adapting to market movements based on user-defined strategies. “Throughput-optimized AI agents will be the first to be deployed,” emphasized a press release issued on May 9th.
Giza highlights that Starknet accounts are smart contracts that enable direct verification of proofs within the contract, utilizing Starknet’s Cairo programming language and zero-knowledge proofs (ZK proofs) developed by StarkWare, ensuring privacy and information authentication.
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