Exploring Nesa — The Future Of Decentralized AI
Nesa is developing a Layer 1 blockchain specifically designed for AI. The Nesa platform enables applications, protocols, and smart contracts to integrate seamlessly with AI technologies.
However, Nesa is not only building a Layer 1 blockchain for AI but also aims to democratize AI and make it accessible globally. It is the first network to implement decentralized model querying.
Basically, Nesa is designed to execute critical AI inference on queries requiring high levels of privacy, security, and trust. It employs advanced on-chain methods such as zero-knowledge machine learning (ZKML) and split learning (SL) to achieve this.
Nesa AIVM
Nesa also introduces the world’s first AI virtual machine network, which runs inference queries on-chain using trusted execution and secure multi-party computation (SMPC) for privacy-preserving operations. It incorporates zero-knowledge proofs (ZKP) schemes to ensure verifiability.
Nesa Overview
Nesa is building a Decentralized Solution and a large AI model store for Web3 that is powered by a reward economy for AI developers, queriers, miners, and model reviewers. Think of this as a decentralized repository for AI.
Nesa’s decentralized inference is a central feature of its platform, designed to enable secure and private AI computations. Here’s how it works: Users initiate inference requests, which are essentially queries they want to run through an AI model. These requests are then managed by smart contracts — self-executing contracts with the terms of the agreement directly written into code. The smart contracts are responsible for verifying the requests and aggregating the results in a trustworthy manner.
The platform incorporates a unique hybrid approach to ensure both security and privacy. It blends several advanced techniques to protect sensitive information. For instance, it uses methods that keep the details of the users’ queries confidential, preventing anyone from accessing them. At the same time, it safeguards the private details of the AI models themselves, so that those running the models can protect their proprietary information.
This comprehensive approach ensures that while users’ queries remain hidden and secure, the integrity and confidentiality of the underlying models are also maintained. By integrating these privacy-preserving mechanisms into a decentralized system, Nesa provides a robust solution for conducting AI inference in a secure and private manner.
Nesa stands out as the pioneering platform in offering private inference within decentralized systems.
Unlike traditional systems where privacy concerns are often managed through centralized controls, Nesa introduces a novel approach that ensures data privacy and security directly on the blockchain. By leveraging advanced technologies like zero-knowledge machine learning (ZKML) and secure multi-party computation (SMPC), Nesa allows users to perform inference queries in a way that keeps their data confidential and protected.
This groundbreaking capability not only enhances the privacy of individual users but also integrates privacy-preserving methods into the decentralized framework, setting a new standard in secure and private AI computations.
Nevertheless, Nesa’s Layer 1 blockchain enables trustless querying of AI models off-chain while ensuring that both the model parameters and the output remain confidential. This means that users can interact with AI models without exposing sensitive details about the models or the results they generate. The system handles these queries securely and privately, protecting the integrity of the information and the AI model’s proprietary aspects.
The network consists of this main players :
- AI models that are available on the Nesa system by the model developers
- Users of Nesa who need affordable, private inference
- Node runners who execute the decentralized jobs on the Nesa system, including validation, inference, and more
Importance of Private inference
Privacy is crucial across many sectors and applications, particularly when using AI. Ensuring that data remains secure is essential, especially for sensitive information. Private inference is vital for users dealing with such data, as it ensures that the data remains confidential during the model inference process. This means that not only is the data itself protected from exposure, but even the AI models processing the data do not have access to it. This level of privacy helps safeguard sensitive information from being compromised or misused.
Ensuring data is not leaked to outside channel is very important in key industries such as health, investigation, legal sectors, Finance sector and so much more.
Introducing Nesa Node
By runnig Nesa node you contribute to the system and nesa network growth. The node runners execute the actual inference task assigned by the orchestrator, where the aggregated results will be returned to the user who request the job and also the nodes helps to validate new transactions and blocks to ensure they follow the network rules.
This nodes can be run by individuals or firm which will earn them rewards either as a validator node runner or a miner.
The Nesa miner Program is live, by Installing the miner software, you earn points.
How to run Nesa Nodes ? Follow this link
Join Nesa Ambassador Program
You want to support the vision of decentralized AI. Then you shouldn’t miss this opportunity to join the Nesa ambassadors. You can read more on the Nesa official blog. HERE
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