The surge in interest in artificial intelligence (AI) and machine learning (ML) has resulted in a shortage of hardware resources and expensive cloud service costs. However, decentralized infrastructure has the potential to challenge the reliance on centralized players.
During the ETHGlobal event in London, Harry Grieve, co-founder of machine learning compute network Gensyn, spoke exclusively to Cointelegraph about how peer-to-peer computing networks could disrupt Web2 services like Amazon Web Services.
Gensyn is a decentralized network under development that will allow individuals to connect to various devices across the internet to train machine learning models. The company has received backing from several Web3 venture capital firms and raised $50 million from Andreessen Horowitz in 2023.
Grieve believes that the network has significant potential as the internet evolves into a more dynamic representation of information, enabling “self-sovereignty and computational liberty online.”
Gensyn has been in development since 2020, with Grieve and co-founder Ben Fielding researching machine learning computing for training and decentralized verifiable systems. They aim to address a threefold problem with blockchain-based technology.
Grieve explained the challenge of building the network, which involves verifying completed ML work. This process intersects complexity theory, game theory, cryptography, and optimization.
Gensyn’s litepaper describes the protocol as “a layer-1 trustless protocol for deep learning computation.” Participants in the network are directly and immediately rewarded for providing computing resources and performing ML tasks.
Grieve drew inspiration from the ideals of the Bitcoin protocol and emphasized his belief in the early days of Bitcoin laptop mining. The long-term plan for Gensyn is to make it accessible to a wide range of users and hardware for ML training, but the initial launch will focus on users with more GPUs due to their ability to provide quick feedback.
Grieve envisions a future where individuals with laptops can download Gensyn’s client and connect to the network, and he expects people to build more user-friendly applications on top of Gensyn.
The emergence of Apple Silicon chips, which power Apple devices, offers significant potential for protocols like Gensyn. Research shows that Apple M2 and M3 chips are comparable to mid-tier Nvidia RTX GPUs, unlocking vast global computing resources. Additionally, these chips are versatile and can be emulated by other manufacturers.
Grieve believes that future edge devices will be more powerful than current smartphones, making decentralization across multiple devices and device-agnostic verification crucial.
In a related development, Solana-based decentralized network io.net will incorporate Apple Silicon chip hardware for its AI and ML services.
Overall, the increasing interest in AI and ML, coupled with the challenges posed by centralized infrastructure, has paved the way for decentralized solutions like Gensyn, which aims to revolutionize machine learning computing and empower individuals in the digital landscape.