Kup Gensyn (AI) w Japan

Gensyn is a decentralized Web3 protocol focused on machine learning computation. Its core mission is to unify computing power from around the world into a global supercluster, making it accessible for training artificial intelligence and deep learning models. This initiative aims to address the current limitations and high costs associated with centralized AI compute resources, thereby democratizing access to AI infrastructure. The Gensyn network functions as a Layer-1 trustless protocol, enabling individuals or entities with spare computing capacity, such as GPUs and CPUs, to contribute their resources. These contributors, known as "solvers," are compensated with tokens for performing machine learning tasks. Developers requiring AI model training can submit tasks to the network. The protocol uses smart contracts to manage task distribution and payments, operating without administrative oversight. A crucial aspect of Gensyn's technology is its verification system, which employs cryptographic proofs and game theory to ensure that computations are performed correctly and reliably. This system is designed to be more efficient than simply re-running entire tasks for verification. Gensyn was founded in 2020 by Ben Fielding and Harry Grieve. It is built on an Ethereum rollup, integrating machine learning capabilities directly into the Web3 ecosystem. The long-term vision is for Gensyn to become a foundational layer for ML compute, much like Ethereum is for smart contract execution. The network is designed to be permissionless and open to participants globally, with governance intended to transition to a decentralized council over time. Regarding its token, it is designed for various utilities within the network, including rewarding compute providers, enabling access to AI training compute, supporting staking, and facilitating governance. Users should be cautious of unofficial sources; the CEO has previously warned against fraudulent token sales, emphasizing that official community discussions are primarily conducted on Discord. Dowiedz się więcej