Trustless Distributed Compute for web3
Lilypad is a powerful trustless distributed compute platform which leverages key features of blockchain to enable developers to call arbitrary verifiable compute jobs directly from their smart contracts! Lilypad's initial focus is on bringing together the current demand for GPUs (from AI & ML) with decentralised physical infrastructure networks like Filecoin which can supply this demand.
The ability to perform off-chain decentralised compute over data from smart contracts opens the door to a multitude of possible applications including:
Inference AI jobs
ML training jobs
Invoking & supporting generic ZK computations
Cross-chain interoperability complement to bridge protocols
Utilising inbuilt storage on IPFS
Federated Learning consensus (with Bacalhau insulated jobs)
IOT & Sensor Data integrations
Providing a platform for Digital twins
Supply chain tracking & analysis
ETL & data preparation jobs
How we see Lilypad network operating on a high level
Lilypad v1 is currently in early testnet phase and is a custom implementation of the ideas & code contained in the paper: "Mechanisms for Outsourcing Computation via a Decentralized Market", which proposed a mediator approach to resolving consensus of deterministic jobs, and also offers insights into running non-deterministic jobs.
See the for more info
Currently, two testnets are functional, both of which allow arbitrary untrusted nodes to join, but use a set of mutually trusted mediators to check jobs using verification by replication (see MODICUM paper for details).
Lalechuza - a testnet built on geth
Larana - a testnet built on Filecoin IPC (an advanced scaling solution for blockchain that implements a subnet pattern)
