Privasea has partnered with Zama to explore the fields of AI, data security, and ML

*“Recently, the Privasea ecosystem has continued to make substantial ecological progress. After receiving a new round of strategic PE round financing, Zama has reached a strategic partnership, and the two parties will be bound for a long time. This is not only Zama’s recognition of Privasea’s technical solutions, long-term development prospects, and narrative direction, but also an important step forward in the application of privacy protection in the field of machine learning.” *

Zama is a technology company dedicated to promoting the application of fully homomorphic encryption technology (FHE) in the field of Blockchain and artificial intelligence, and in the past four years, it has continuously transformed FHE from abstract mathematical theory into practical code, greatly improving the ability of developers to apply FHE technology. Recently, Zama successfully raised $73 million in its Series A funding round, which further confirms the market’s confidence in Zama’s technical strength and growth potential.

Zama has developed long wick candle FHE libraries and solutions that are developer-friendly and continues to optimize for performance, with the launch of fhEVM, which has achieved significant results in privacy smart contracts for Blockchain applications, and has been integrated with longest projects including Fhenix, Shiba Inu, and Inco, marking a step forward in the utility of privacy protection in Blockchain.

Artificial intelligence, machine learning, etc. are potential areas that Zama hopes to promote the widespread adoption of FHE technology, such as its Concrete ML tool to serve these cutting-edge fields, and in order to further make substantial progress in this direction, Zama has recently reached a strategic partnership with Privasea, and has formed a deep technical integration with each other. Based on this, Zama will provide technical support for Privasea’s FHEML solution for a long time, and Privasea will also become an important piece of the puzzle for Zama to apply its FHE solution to AI and ML fields.

Through this partnership, both Privasea and Zama will play an indispensable role in each other’s ecosystems, and both ecosystems will be bound for a long time. At the same time, the conclusion of this partnership also indicates that the application of privacy-preserving technology in the field of machine learning is about to usher in a new breakthrough.

The narrative of the Privasea ecosystem

Privasea is an AI+DePIN-driven, PHE-based privacy-preserving computing platform dedicated to providing a secure and sustainable AI and machine learning computing environment. We see that data security and privacy protection have always been a long-term and complex challenge in the field of AI, and Privasea’s FHE solution has a high level of data confidentiality and compliance, and is able to comply with laws and regulations such as the European Union’s General Data Protection Regulation (GDPR).

At the heart of the Privasea network is a robust FHE pipeline that is based on TFHE-RS and Concrete-ML and specifically tailored to Privasea’s needs long wick candle. This component provides a solid fortress for data security, so that the user’s data is encrypted and protected throughout the calculation process, even during collaborative computing. So we see that Zama is an important source of Privasea FHE, and its support for the Privasea network is long-term and ongoing.

Through its APIs, Privasea provides developers with the tools and capabilities to access Privasea’s AI network capabilities, allowing them to seamlessly integrate AI capabilities into their applications while keeping their data secure and private. Privasea also launched Privanetix, a compute-centric DePIN network that aggregates distributed computing resources to process encryption data securely and efficiently. Each Node of the network is equipped with the appropriate FHEML pipeline, enabling distributed Nodes to efficiently perform machine learning calculations without exposing sensitive data.

The Privanetix network is powered by Privasea’s suite of smart contracts, ensuring that compute Nodes in the network can be accurately tracked and rewarded. Smart contracts provide incentives for network participants while maintaining transparency and fairness, and are the economic foundation for the sustainable operation of the entire network.

Another advantage of Privasea is that it allows users with no cryptography or programming background to easily access and leverage the network’s capabilities. This not only greatly drop the barrier to entry for the use of advanced FHE AI computing, allowing more long users to safely enjoy the convenience of AI, but also seamlessly expanding this set of privacy AI computing capabilities to various fields. At the same time, the Privasea network supports compliance audits while protecting user data, and meets various national laws and regulations, including AML laws. This off-chain computing solution not only ensures data security, but also ensures that the behavior of the network can be reviewed when necessary, providing users with a safe and reliable computing environment.

Based on this, Privasea can be highly integrated with various long scenarios that long have verification and computational analysis needs for data protection, including biometrics, healthcare, finance, secure cloud data computing, anonymous voting systems, and more.

We see that Privasea is promoting the large-scale adoption of FHE solutions, and at the same time providing impetus for the in-depth integration and widespread adoption of AI technology in various scenarios under the premise of ensuring data security and complying with data regulations, and the ecosystem is also expected to become a new value carrier for the trillion-dollar application market.

Privasea and Zama’s “two-way street”

At present, the cooperation between Privasea and Zama has made substantial progress, and the core of the cooperation between the two is Algorithm integration. Privasea not only supports mainstream TFHE solutions, but also integrates Zama’s advanced TFHE-rs library into its own network to improve the privacy and security of AI operations. At the same time, Privasea will work closely with Zama’s technical team to ensure that the TFHE solution can be seamlessly integrated into Privasea’s infrastructure, and through stress testing and security audits on the testnet, the two parties will jointly ensure the stability and security of the technology integration.

In addition to system integration, Privasea and Zama will discuss emerging features such as ZAMA’s global secret key model and develop them to lay the foundation for future deployments. At the same time, Privasea will also develop a series of privacy-preserving AI applications based on the ZAMA-ConcreteML platform, covering key areas such as biometrics, medical image recognition and financial data analysis, and plans to test the applications on its own network. Through these specific use cases, Privasea and Zama were able to translate theory into practical user value, while also verifying the effectiveness of encryption technology in a real-world environment.

In addition, Privasea and Zama plan to establish a knowledge-sharing platform to facilitate the exchange of technologies, ideas and best practices through regular technical workshops and workshops. In addition to a series of technical cooperation, the two also plan to carry out in-depth cooperation at the market level, such as market expansion strategies, joint product promotion, etc.

So overall, Privasea will enhance the privacy and security of AI operations by integrating Zama’s TFHE-rs library into its network, and this new integration will accompany the development of the Privasea ecosystem. As an ecosystem that has seen the application of FHE technology to AI, ML and other fields, Privasea is expected to provide long-term support for Zama’s AI layout and provide important support for the computing resources required by FHE solutions, which cannot be given by other partners of Zama. On this basis, Privasea is expected to be an important piece of the puzzle for Zama to apply its FHE solution to the field of AI and ML.

In fact, Privasea and Zama’s ecological vision is the same, on the one hand, both are promoting the adoption of FHE technology in different fields, and both parties are also supporters of AI, ML and other fields, and this cooperation is also seen as a “two-way street”.

Zama’s brand new Web3 profile

With the ecological vision of building an end-to-end encryption network HTTPZ (“Z” stands for “Zero Trust”), the Zama ecosystem provides an ecosystem of open source FHE tools for Web2 and Web3 applications on the one hand, and makes it easier for developers to use FHE for various use cases in areas such as Blockchain and artificial intelligence by building longest open source products.

On the other hand, it is building a new Web3 framework to better realize the vision.

We have seen that Zama has established cooperation with three Web3 facilities in different directions but with FHE as the core technology, including Inco, Fhenix and Privasea, to further expand its FHE technical solutions. Inco represents the Layer 1 direction of the Zama framework, Fhenix represents the Layer 2 direction, and Privasea serves as the Depin AI facility direction.

Based on Zama’s Open Source framework, FHE technology is expected to expand deeper into more long areas and build a series of innovative and real-world solutions to enhance privacy in the Web3 world and establish a new standard in the field of online data privacy with its ecosystem partners.

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