Web3 provides us with the bricks to build decentralised AI marketplaces where data and models could be monetised. However, this stack does not provide the privacy guarantees required to engage the actors of this decentralised AI economy.
Once a data or a model has been exposed in plaintext, any mechanism controlling access to this piece of information becomes irrelevant since it cannot guarantee that the data has not leaked.
In this talk, we’ll explore the state-of-the-art in Secure/Blind Computing that will guarantee the privacy of data or models and enable a decentralised AI vision.
Typically, we will describe a technique known as Federated Learning that enables training AI models on sensitive data while respecting their owners’ privacy, and its potential use in conjunction with Web3 technologies such as the Ethereum blockchain.