Transforming AI with FHE
Privasea and Zama Announce Partnership
Privasea and Zama Announce Partnership
In a world that’s increasingly digital, data security is becoming more important than ever before. With the skyrocketed use of AI, we all deal with tremendous amounts of data every single day, whether we realize it or not. This has made data security in AI more essential than ever before, and this importance is only growing.
Privasea is dedicated to advancing machine learning through Fully Homomorphic Encryption (FHE) technology. Its partnership with Zama combines Zama’s leading-edge FHE technology with Privasea’s AI design and distributed computing resources, marking the dawn of a new era in secret machine learning.
The Privasea AI Network is a powerful system designed to prioritize the end-to-end data security throughout the AI computation process. It is backed by notable investors, such as Binance Labs, OKX Ventures, Nomura Group's Laser Digital, and the SoftBank-backed incubator Tanelabs.
Privasea uses an innovative technology called Fully Homomorphic Encryption, which enables computations to be conducted on encrypted data without ever needing to decrypt it, producing results that are identical to computations performed on unencrypted data.
Zama is a cryptography company building state-of-the-art FHE solutions for blockchain and AI. It recently completed its Series A funding round, raising a total of $73 million. It aims to make FHE ubiquitous in the domains of blockchain and AI.
Zama offers easy-to-use FHE libraries and solutions for developers. It lays a strong emphasis on performance improvements, and their fhEVM enables confidential smart contracts in blockchain applications. Zama has integrations with projects like Fhenix, Shiba Inu, and Inco. The company’s ultimate goal is to make the entire internet encrypted end-to-end using FHE.
The partnership aims to propel the development of FHE technology, especially looking at practical applications in end-to-end encryption for machine learning. Privasea and Zama will join forces to become standout projects in the Web3 domain.
One of the most exciting parts about this collaboration is the ability for Privasea and Zama to use the technologies the other has developed.
For example, Privasea will now support the mainstream TFHE scheme within its testnet and mainnet. Having received recognition and authorization from Zama, it will invoke Zama’s TFHE-rs library within its networks, integrating Zama’s FHE algorithms into Privasea’s distributed computing resources and AI models to enhance the privacy and security of AI operations.
Integration – Privasea will assess the existing system to determine the technical requirements for integrating the TFHE scheme. In collaboration with Zama’s technical team, it will then invoke the TFHE-rs library for initial technical integration testing and deploy the integrated solution on the testnet for stress testing and security audits.
Advanced R&D – Discussions will be held regarding Zama’s Global Key model and KMS, among other developing features, to selectively follow up with development and later deployment.
Privasea will develop blockchain-based private AI applications based on Zama’s Concrete ML. This will cover areas such as biometric identification, medical image recognition, and financial data analysis, ensuring data security throughout the AI analysis process.
Application Deployment – Building on Concrete ML’s implemented linear models, tree-based models, nearest neighbor models, and neural network, Privasea will collaborate with Zama’s technical team for joint research and development, deploying more private AI test applications on both testnet and mainnet.
Advanced R&D – Focusing on privacy-sensitive areas, such as biometric identification and healthcare, Privasea and Zama will jointly explore new application development targets and requirements, developing and testing new encrypted AI models with FHE technology support from Zama.
Not only does this collaboration allow the two parties to share information and technologies they have already developed; it also allows them to collaboratively work on advancing their technologies towards a better future.
Privasea will also establish a knowledge-sharing plan that includes setting up regular technical seminars and workshops for exchanges with multiple organizations that have an interest in ML applications of FHE.
Privasea will develop a market entry strategy that leverages its strengths and resources to create engaging activities and incentives for its users, including collaborative airdrops aimed at new market segments.
Additionally, Privasea will organize collaborative branding events, such as offline seminars and webinars, to promote the products and services of all involved parties. Activities like AMAs and hackathons will also be employed to enhance community engagement and increase product awareness.
Privasea’s partnership with Zama is of significant importance for advancing FHE technology and the application of private machine learning. We look forward to achieving technological breakthroughs through this partnership into untapped markets.