Author: Biteye Core Contributor Louis

Editor: Biteye Core Contributor Denise

With the rapid development of AI technology, traditional blockchain architectures can no longer meet the high-performance computing and complex data processing needs required by AI applications. This has led to the rise of Layer 1 blockchain platforms optimized specifically for AI, which exhibit diverse characteristics in terms of technical architecture, application scenarios, and business models.

This study provides an in-depth analysis of five leading AI Layer 1 projects: Bittensor, Vana, Kite AI, Nillion, and Sahara.

01. Bittensor: Decentralized AI Network Infrastructure

As an early explorer in the blockchain AI field, Bittensor is dedicated to building an open decentralized artificial intelligence collaboration network.

Its goal is to break down the centralized barriers in traditional AI research and development, allowing more participants to contribute and benefit together.

Unlike traditional centralized AI systems (such as companies like OpenAI), Bittensor has created an open peer-to-peer ecosystem where participants can receive corresponding rewards based on their contributions to the network.

Bittensor's technical architecture adopts a dual-layer structure design:

• Root Network (Mainnet): Responsible for the coordination, verification, and management of TAO token issuance for the entire system, serving as the central hub for resource allocation across the network.
• Subnet Ecosystem: Each subnet acts like an independent AI laboratory, developing specialized solutions for specific AI application scenarios and proving its value in market competition.

This design allows Bittensor to balance the overall stability of the network with the specialization of various fields, providing a flexible infrastructure for the development of decentralized AI.

Ecological Development Progress

• The number of subnets has expanded from an initial 32 to over 64, covering various AI application scenarios such as text generation, trading signals, and data labeling.
• The active user base has reached 140,000, achieving a doubling growth compared to the previous year.
• The total market valuation of subnets exceeds $100 million, with daily trading volume maintained at around $45 million.
• Institutional participation has significantly increased, with the well-known fund Grayscale incorporating TAO into its decentralized AI fund, adjusting its weight to 29.55%.

These data indicate that Bittensor is gaining recognition from an increasing number of market participants, and its ecosystem is entering a positive development track.

The recent dTAO (Dynamic TAO) system upgrade is an important innovation in its economic model. The core of this upgrade is to optimize the distribution mechanism of the TAO token, shifting from a resource allocation method reliant on the subjective judgment of validators to a more market-oriented distribution mechanism, allowing resources to flow more precisely to truly competitive subnets.

Bittensor's original economic model exposed several key issues during actual operation:

1. Lack of objectivity in the evaluation mechanism: As the number of subnets increases, it becomes difficult for validators to comprehensively and objectively assess the actual value of each subnet, leading to a gradual decline in allocation efficiency.

2. Imbalance in power structure: Many validators are also subnet operators, and this role overlap can easily lead to conflicts of interest, with validators potentially favoring the subnets they participate in, even leading to private trading situations.

3. Participation barriers: Ordinary TAO holders find it difficult to directly influence the network's resource allocation decisions, with power overly concentrated in the hands of a few validators.

To address these issues, the dTAO upgrade introduces a dynamic resource allocation system based on market mechanisms.

This system transforms each subnet into an independent economic unit, driven by users' actual needs for resource allocation. Its core innovation is the subnet token (Alpha token) mechanism:

• Operating principle: Users can stake TAO to obtain Alpha tokens issued by various subnets, which represent users' support for specific subnets.
• Resource allocation logic: The market price of Alpha tokens becomes a signal for measuring the demand intensity of subnets. Initially, the prices of Alpha tokens are the same, with each pool containing only 1 TAO and 1 Alpha token. As liquidity of the two tokens in the subnet increases, the price of Alpha tokens will also change. The emission of TAO is proportionally allocated based on the price of subnet tokens among all tokens, with higher-priced subnets receiving more TAO allocation, thus achieving automatic optimization of resource allocation.

This mechanism significantly improves the efficiency and fairness of resource allocation, stabilizing the value of TAO tokens and providing more avenues for ordinary users to participate in network governance.

Currently, the most active subnets include:

• Subnet 4 Targon: Focused on AI inference services for text generation, characterized by fast response times and low costs.
• Subnet 64 Chutes: Provides various LLM API interfaces, allowing developers to build and deploy AI applications on the Bittensor network.
• Subnet 8 PTN: Focused on the financial sector, incentivizing miners to generate accurate trading signals through a reward mechanism, covering various financial markets such as forex and cryptocurrencies.
• Subnet 52 Dojo: Engaged in data labeling, encouraging users to earn tokens through data annotation. Recently entered Yzi Labs, which announced an investment in its parent company Tensorplex.

02. Vana: Data Sovereignty and Value Reconstruction Platform

The Vana project focuses on addressing a core issue in today's digital economy: the ownership and value distribution of personal data. In the current internet ecosystem, users' data is mostly monopolized and controlled by large tech companies, while the users who actually create this data rarely benefit from it. Vana's innovation lies in establishing an ecosystem where users truly own and control their data while being able to derive economic returns from it.

As an EVM-compatible Layer 1 blockchain network, Vana's technical architecture consists of five core components:

1. Data Liquidity Layer: This is the core of the Vana network, achieving the incentivization, aggregation, and verification of data assets through data liquidity pools (DLP). Each DLP is a smart contract specifically designed to aggregate certain types of data assets, such as social media data, browsing history, etc.
2. Data Portability Layer: Ensures that user data can be easily transferred between different applications and AI models, enhancing the flexibility of data usage.
3. Universal Connectome: Tracks real-time data flow within the entire ecosystem, forming a data ecological map to ensure system transparency.
4. Unmanaged Data Storage: An important innovation of Vana is its unique data management approach. Users' raw data is not put on-chain but is stored in locations chosen by users, such as cloud servers or personal devices, ensuring complete control over their data.
5. Application Ecosystem: Based on data, Vana has built an open application ecosystem where developers can utilize the data accumulated in DLP to create various innovative applications, including AI applications, while data contributors can receive dividend rewards from these applications.

This design allows Vana to create a more equitable data value distribution mechanism while protecting user data privacy, providing an important data foundation for the development of decentralized AI.

Latest Development Updates

Vana's financing and partnership expansion continue to progress:

• In February 2025, YZi Labs announced a strategic investment in Vana, with Binance founder CZ joining as an advisor.
• In terms of ecological construction, Vana has built multiple data projects covering various fields, from social media data to financial forecasting data, including: Finquarium (financial forecasting data), GPT Data DAO (ChatGPT chat data), Reddit Data DAO (Reddit user data), Volara (Twitter data), Flirtual (dating data), etc.
• Recently, Vana organized a hackathon during Eth Denver, offering a prize pool of up to $50,000 to incentivize developers to build DataDAOs and AI applications based on Vana data, further expanding its ecosystem.

These developments indicate that Vana is actively building a complete ecosystem around data ownership and value realization, and its development momentum is worth paying attention to.

03. Kite AI: Technical Breakthrough of AI-Native Public Chain

Kite AI is a native Layer 1 blockchain project focused on the AI field, built on the Avalanche framework. It aims to address various challenges faced by traditional blockchains when handling AI assets, particularly how to achieve clear rights and incentives for contributions of AI data, models, and agents. Kite AI proposes four core technological innovations:

1. PoAI Consensus Mechanism: Proof of Attributed Intelligence is a consensus mechanism pioneered by Kite AI, which accurately tracks the value contributions of data, models, and AI agents through an on-chain verifiable contribution record system. The project has designed a dynamic reward pool mechanism that allocates profits based on contribution ratios, effectively addressing issues such as "data black box" and "model theft" in the traditional AI economy.

2. Composable AI Subnets: Kite AI adopts a modular architecture, allowing developers to build industry-specific AI collaboration ecosystems as needed. For example, in a medical subnet, patient data can be encrypted and selectively authorized to pharmaceutical companies for AI model development, with profits distributed among data subjects, model developers, and subnet maintainers in a certain proportion, creating a win-win ecosystem.

3. AI-Native Execution Layer: Kite AI is building an on-chain AI-native execution layer specifically for handling AI computing tasks such as inference, embedding, and fine-tuning/training. Users can authorize smart contract wallets to execute inference calls and interact with models through this layer. This execution layer not only supports blockchain transactions and state changes but also integrates confidential computing environments (such as Trusted Execution Environments, TEE) to ensure data security and privacy protection during the computing process.

4. Decentralized Data Engine: Kite AI ensures that data creators receive fair compensation within the AI workflow. The platform includes compliance modules that meet regulations such as GDPR/CCPA, satisfying data privacy requirements worldwide and reducing compliance costs for developers.

These technological innovations enable Kite AI to create a fairer and more transparent value distribution environment for AI developers and data providers, promoting the decentralized development of AI technology.

Current Development Status

Kite AI launched its incentive testnet on February 6, 2025, marking the first AI-native Layer 1 sovereign blockchain testnet. The testnet has performed impressively since its launch:

• Within less than 70 hours of the testnet going live, the number of connected wallets exceeded 100,000. As of now, a total of 1.95 million wallets have joined the incentive testnet V1, with over 1 million wallets interacting with AI agents, totaling more than 115 million calls.

• The project has a strong background, developed by an experienced Silicon Valley team. The co-founders have extensive technical leadership experience in the field of artificial intelligence, having worked at top tech companies such as Uber, Salesforce, and Databricks. Core team members come from industry-leading companies like Google, BlackRock, Uber, and the NEAR Foundation, with academic backgrounds from top institutions like MIT and Harvard.
• In terms of capital support, the project has secured investments from top institutions including General Catalyst, Hashed, Hashkey, and Samsung Next, and has established technical partnerships with Eigenlayer, Sui, Avalanche, and AWS.
• As a selection committee member of Avalanche's InfraBUILDL(AI) program, Kite AI plays an active role in promoting the development of the Avalanche AI ecosystem, aiming to position Avalanche as a leading blockchain for AI applications.
• With the global data economy expected to exceed $70 billion by 2025, Kite AI is poised to become an important infrastructure for data rights confirmation and monetization, and its development potential is worth looking forward to.

04. Nillion: Frontier Exploration of Privacy Computing

Nillion is redefining the way sensitive data is processed through its unique "blind computing" technology, paving new paths for future digital privacy protection.

Nillion is a decentralized public network based on an innovative cryptographic primitive called Nil Message Compute (NMC), allowing network nodes to operate in a non-traditional blockchain manner. Founded in November 2021 and led by forward-thinking innovators like Alex Page and Andrew Masanto, the project aims to create a system that can securely handle high-value data without exposing sensitive details.

Nillion's core advantage lies in its "blind computing" capability—a process that allows data to remain encrypted throughout its lifecycle, including storage, transmission, and processing. Its technical architecture integrates various cutting-edge privacy protection technologies:

• Multi-Party Computation (MPC): Enables multiple nodes to collaboratively compute functions without revealing their private inputs, achieving joint computation without data sharing.
• Fully Homomorphic Encryption (FHE): Allows direct operations on encrypted data, ensuring that data remains encrypted from start to finish, providing end-to-end privacy protection.
• Zero-Knowledge Proofs (ZKP): Provides a method to verify computations without disclosing any underlying data, enhancing the system's credibility.
• Nada Language: A domain-specific language designed for creating secure MPC programs, simplifying the development process of privacy protection applications and lowering the learning curve for developers.

Nillion's network architecture consists of three main layers: the processing layer (responsible for secure computation), the coordination layer (NilChain, managing communication between nodes), and the connection layer (serving as a gateway to connect external systems). This multi-layer architecture allows Nillion to provide powerful computing capabilities while protecting data privacy, meeting the needs of various privacy-sensitive scenarios.

Latest Development Progress

According to the latest information, the development of the Nillion network is progressing steadily:

• The Nillion mainnet is scheduled to launch in March 2025 (this month). The total supply of Nillion tokens is 1 billion, which is expected to be distributed at the mainnet launch.
• In terms of financing, Nillion completed a $25 million funding round led by Hack VC on October 30, 2024, with investors including well-known institutions like HashKey Capital and Animoca Brands, as well as angel investors from projects like Arbitrum, Worldcoin, and Sei. This round of financing brings Nillion's total funding to $45 million, providing ample financial support for the project's long-term development.
• In terms of ecosystem expansion, Nillion has established integration relationships with several mainstream public chains, including NEAR Protocol, Aptos, Arbitrum, Mantle, and Sei. Through collaboration with NEAR Protocol, Nillion aims to enhance privacy tools, enabling developers to innovate more effectively in the DeFi space.
• In the AI ecosystem, Nillion has formed partnerships with several AI-related projects, including Ritual, Crush AI, Skillful AI, and Virtuals Protocol. For example, Virtuals Protocol is currently the largest multimodal AI agent protocol, and through collaboration with Nillion, it utilizes its secure computing infrastructure to support the private training and inference of AI models, achieving a perfect combination of AI and privacy.

05. Sahara AI: Building a New Economy for AI Assets

Project Development

The core idea of Sahara AI is to build a "human-AI collaboration network" that enables ordinary users, developers, and enterprises to participate in the creation, deployment, and monetization of AI assets. Through this collaborative model, Sahara AI aims to lower the entry barriers to AI, allowing every participant to share in the industry's growth dividends. The project has successfully raised a total of $43 million in funding led by Binance Labs, Polychain Capital, and Pantera Capital.

The platform's technical architecture includes three key components:

1. Sahara Blockchain: Provides a secure and transparent foundation for transactions and efficient AI lifecycle management within the ecosystem.
2. AI Infrastructure: Supports distributed collaborative training and service capabilities for advanced algorithms and computing frameworks.
3. Sahara AI Marketplace: A decentralized trading center for AI assets.

These components together form a complete ecosystem that supports the entire process from data collection and labeling to model training, deployment, and monetization.

Latest Development Progress

The Sahara AI project is in a rapid development phase, and its testnet has undergone several important stages:

• In December 2024, Sahara AI launched the Beta version of its first phase data service platform testnet, attracting over 780,000 user applications, with more than 10,000 candidates receiving the first batch of participation qualifications. During this phase, participants could contribute to the AI ecosystem by completing data collection, optimization, and labeling tasks and earn rewards.
• In February 2025, Sahara AI initiated the second phase of the testnet, expanding the contributor base of the platform and introducing additional reward opportunities. This phase further strengthened user participation in shaping the future of decentralized AI.
• The latest development is that Sahara AI announced the launch of a public testnet called "SIWA" on March 10, 2025. This is considered the last major test before the launch of the Sahara AI mainnet and TGE, and it may also be the last opportunity for participants to earn airdrop rewards (referred to as "points").

Sahara AI has released its roadmap for 2024-2025, which includes several key milestones:

• Q4 2024: Launched the data service platform and testnet, allowing users to earn rewards through data collection and labeling.
• Q1 2025: AI Marketplace goes live, providing development tools and data service expansion capabilities, supporting model development, training, and deployment, and introducing an early access program.
• Q2 2025: Launch of the Sahara Studio toolkit, covering model training, deployment, and workflow management, further optimizing the developer experience.
• Q3 2025: Launch of the Sahara Chain mainnet, providing secure and transparent on-chain infrastructure for large-scale decentralized AI, while supporting the assetization and trading of data and models.

On March 1, 2025, Sahara AI launched an incubator program aimed at discovering and supporting the world's most promising AI x Web3 innovation projects. This program focuses on two tracks: AI infrastructure and AI applications, welcoming teams with MVP or higher maturity to participate. Successfully selected projects will have the opportunity to fully integrate into the Sahara AI ecosystem, receiving exclusive technical support, market expansion resources, and investment opportunities.

06. Conclusion

AI Layer 1 is at a critical stage of rapid evolution. This emerging track is reconstructing the underlying architecture of AI technology through decentralized infrastructure. From data rights confirmation to computing resource allocation, from model training to application deployment, these platforms are breaking through the limitations of traditional centralized AI systems, building a more open, transparent, and efficient technological ecosystem. In the future, this track will continue to drive technological innovation and advance artificial intelligence towards a more decentralized and collaborative development direction.

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