The development of narratives is similar to that of novels, with plots having lows and highs, certainly accompanied by various controversies, just like there are some who question whether the AI x Crypto trend is just riding the coattails of the rapidly growing AI industry without substantial use cases.
However, in terms of data and popularity, this trend is surpassing memes and is also creating tangible applications. Infrastructure like TAO, which promotes decentralized AI, is on the rise, along with decentralized GPU markets that are crucial for AI computation.
Currently, AI agents are excelling in market analysis, trade execution, and social media user interactions. However, to achieve greater scalability, agents need access to a broader range of information. For instance, to act on behalf of individuals by understanding their preferences, hobbies, and values, agents must handle data related to personal privacy. Even for non-personalized applications, agents need access to sensitive data that is typically difficult to obtain, in order to permeate various aspects of life.
However, allowing nodes in a decentralized network to operate in a unique, non-blockchain manner, Nillion @nillionnetwork creates a form of 'blind computation' to address the privacy data issues mentioned above.
The foundation of Nillion is composed of multiple nodes that can transmit, store, and compute data without requiring direct access to it. For example, these nodes can sign transactions on your behalf. While traditional computing requires a private key to sign transactions, blind computation distributes your private key among the nodes in parts called 'shares'. Through cryptographic protocols, nodes holding different shares can collectively sign transactions without reconstructing the private key, thus preventing any information leakage. This is blind computation.
Blind computation is a key technology. It is not to say that Web2 services are superior to Web3 in all aspects. In the past, we handed our personal data over to Web2 companies with little protection, allowing them unrestricted access to private information. In 2018, after the Cambridge Analytica scandal broke, the Senate held hearings on Facebook, where personal data from millions of users was collected without consent, revealing the negligence in managing user data. Blockchain emerged as a solution to these problems.
But, blockchain is not a perfect solution either. While it can address data ownership issues, its inherent transparency limits its use cases, as it prevents the on-chain storage of private data. This is where blind computation becomes crucial.
In addition to simple encrypted data storage, the ability to compute data without decrypting it allows us to simultaneously: solve user data ownership issues through blockchain technology; and overcome data onboarding limitations caused by blockchain transparency through blind computation.
However, what we are discussing now is just one pillar of Nillion. The ultimate goal of Nillion's blind computation is to leverage this technology to create various use cases. These use cases will be realized on the blockchain network, which is the role of Nil Chain.
Nil Chain is a blockchain network based on the Cosmos SDK, serving as the coordinating layer within the Nillion network. Users pay fees through Nil Chain, and without Nil Chain verifying the fee payment, users cannot receive the blind computation results from PETnet. Nil Chain coordinates all actions within the Nillion network and operates without the need for smart contracts.
As mentioned above, to make artificial intelligence a personal assistant for handling daily tasks, it needs access to a lot of highly private data. Without blind computation, there are almost no safe methods to train AI on personal data. Therefore, Nillion's blind computation may become the key infrastructure for creating the perfect personalized AI assistant.
The Nillion ecosystem is rapidly expanding, with significant advancements in both foundational platforms and innovative applications, dedicated to building networks in this field. Leading artificial intelligence infrastructure platforms (such as Virtuals, Capx, Ritual, and Skillful) have signed agreements or committed to integrating Nillion. In terms of applications, end-user solutions such as Pindora (personal social agent), Fulcra (health advisor agent), and Space of Mind (mental health advisor agent) are actively building Nillion to develop their applications.
This is where Nillion intervenes in the healthcare sector, offering a groundbreaking approach to medical privacy. Their technology enables organizations to store, process, and analyze sensitive medical data while maintaining complete encryption. Through its decentralized architecture, healthcare institutions can collaborate effectively and securely, opening new avenues in personalized medicine, predictive medical analytics, and large-scale medical research.
In the field of mental health, Space of Mind is leveraging Nillion's technology to provide evidence-based mental health support through group therapy. Their platform integrates AI-driven tools while directly addressing privacy concerns - for example, enabling private analysis of journal entries' emotions while protecting user privacy and trust.
Data markets built on Nillion technology are revolutionizing the way personal data is processed and monetized. This innovative approach opens new possibilities for individuals, allowing them to benefit from the ever-expanding data economy without sacrificing control over their personal information. Nillion's technology plays a crucial role in these markets, facilitating the secure and proactive use of data while maintaining encryption and protecting sensitive information from unauthorized access.
Some pioneering projects are already leveraging Nillion's capabilities. ZAP stands out, focusing on analyzing user data pools to create new AI training datasets while providing valuable user insights. Their initial product, AI Lingo, has attracted nearly 40,000 users. Fulcra is another notable example, specializing in generating collective insights from smart device data. Meanwhile, Humanity is committed to integrating social, health, and entertainment data from various platforms to help users monetize personal insights.
The transparency of blockchain has always been a double-edged sword. While it ensures fair access through transparency and traceability, it is this very transparency that hinders key institutional participants from adopting public blockchains. Not everything benefits from complete transparency. While data privacy may be abused, I believe the main obstacle to the widespread adoption of Web3 and blockchain is not scalability, but transparency.
Some of the most valuable data in the world is likely to be private. While this privacy may enhance its value, someone needs to use this data to build services that enable Web3 to compete with Web2 services. With infrastructure capable of computing encrypted data in a distributed environment without decryption, Web3 can create highly useful applications using sensitive or private data.
While blockchain is significant for achieving self-hosting in the digital world, it is only a partial innovation if the data it handles is limited. If private data computation is realized in a trustless blockchain environment, we can truly anticipate the mass adoption of Web3 products.
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