Original author: Biteye core contributor Louis
Original editor: Biteye core contributor Viee
With the rapid development of AI technology, traditional blockchain architecture can no longer meet the high-performance computing and complex data processing requirements of AI applications, which has led to the rise of Layer 1 blockchain platforms optimized for AI, which are diversified in terms of technical architecture, application scenarios and business models. This study deeply analyzes the five leading AI Layer 1s, Bittensor, Vana, Kite AI, Nillion and Sahara, and provides investors with a detailed participation guide.
1. Bittensor: Decentralized AI Network Infrastructure
As an early explorer in the field of blockchain AI, Bittensor is committed to building an open decentralized artificial intelligence collaborative network. Its goal is to break 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.
Bittensors technical architecture adopts a two-layer structure design:
Root network (main network): responsible for the coordination, verification and issuance management of the entire system, and is the hub for the allocation of network resources
Subnet Ecosystem: Each subnet is like an independent AI laboratory, developing professional solutions for specific AI application scenarios and proving its value in market competition.
This design allows Bittensor to balance the stability of the overall network with the professionalism in various fields, providing a flexible infrastructure for the development of decentralized AI.
Ecological Development Progress
The number of subnets has expanded from 32 in the early stage to more than 64, covering a variety of AI application scenarios such as text generation, trading signals, and data annotation.
The number of active users has reached 140,000, doubling from the previous year
The total subnet market valuation exceeds $100 million, and the daily transaction volume remains at around $45 million
Institutional participation has increased significantly. The well-known fund Grayscale has included TAO in its decentralized AI fund, with the weight adjusted to 29.55%.
These data show that Bittensor is gaining recognition from more and more market participants, and its ecosystem is entering a healthy development track.
The dTAO (dynamic TAO) system upgrade recently completed by Bittensor is an important innovation in its economic model. The core of this upgrade is to optimize the allocation mechanism of the TAO token, from a resource allocation method that relies on the subjective judgment of validators to a more market-oriented allocation mechanism, so that resources can flow more accurately to those subnets that are truly competitive.
The original economic model of Bittensor exposed several key problems in actual operation:
The evaluation mechanism lacks objectivity: As the number of subnets increases, it becomes difficult for validators to comprehensively and objectively evaluate the actual value of each subnet, and the allocation efficiency gradually decreases.
Imbalanced power structure: Many validators are also subnet operators. This overlapping role can easily lead to conflicts of interest. Validators may favor the subnets they participate in, or even engage in private transactions.
Barriers to participation: It is difficult for ordinary TAO holders to directly influence the networks resource allocation decisions, and power is overly concentrated in the hands of a few validators.
To solve these problems, the dTAO upgrade introduces a dynamic resource allocation system based on market mechanisms. This system transforms each subnet into an independent economic unit, driving resource allocation through the actual needs of users. Its core innovation is the subnet token (Alpha token) mechanism:
How it works: Users can obtain Alpha tokens issued by each subnet by staking TAO. These tokens represent the user’s support for a specific subnet.
Resource allocation logic: The market price of the Alpha token becomes a signal to measure the intensity of subnet demand. Initially, the alpha tokens have the same price, and there is only 1 TAO and 1 alpha token in each pool. As the liquidity of the two tokens is added to the subnet, the price of the alpha token will also change. The emission of TAO is distributed in proportion to the price of the subnet token in all tokens. The subnet with a higher price will receive more TAO allocation, thereby achieving automatic optimization of resource allocation.
This mechanism significantly improves the efficiency and fairness of resource allocation, makes the value of TAO tokens more stable, and provides more ways for ordinary users to participate in network governance.
Investor Engagement Strategy
For retail investors interested in participating in the Bittensor ecosystem, there are several main ways:
Liquidity provision: Obtain Alpha tokens of each subnet by staking TAO and participate in the construction of the subnet ecosystem. This method is relatively stable and can allocate resources based on the views on different subnets to spread risks.
Secondary market investment: directly purchase the Alpha tokens of the subnet you are interested in from the trading market. However, it should be noted that the Alpha token is currently in the early stages of emission, with high inflation rates and selling pressure. Investors should carefully choose subnets with long-term development value.
Technical Contribution: Investors with a technical background can choose to become network validators or subnet miners to earn rewards by verifying the quality of AI models on the network or running AI models on specific subnets.
The most active subnets include:
Subnet 4 Targon: Focuses on AI reasoning services for text generation, featuring fast response speed and low cost
Subnet 64 Chutes: Provides various LLM API interfaces, allowing developers to build and deploy AI applications on the Bittensor network
Subnet 8 PTN: Focusing on the financial sector, it encourages miners to generate accurate trading signals through a reward mechanism, covering a variety of financial markets such as foreign exchange and cryptocurrency
Subnet 52 Dojo: Do data annotation and encourage users to earn tokens through data annotation. Enter Yzi Labs and announce investment in its parent company Tensorplex.
2. Vana: Data sovereignty and value reconstruction platform
The Vana project focuses on solving a core problem in todays digital economy: the ownership and value distribution of personal data. In the current Internet ecosystem, user data is mostly monopolized and controlled by large technology companies, while the users who actually create this data rarely benefit from it. Vanas innovation lies in establishing an ecosystem where users truly own and control their own data, while being able to obtain economic returns from it.
As an EVM-compatible Layer 1 blockchain network, Vanas technical architecture consists of five core components:
Data Liquidity Layer: This is the core of the Vana network, which enables the incentive, aggregation and verification of data assets through data liquidity pools (DLP). Each DLP is a smart contract specifically used to aggregate a specific type of data asset, such as social media data, browsing history, etc.
Data Portability Layer: Ensures that user data can be easily transferred between different applications and AI models, enhancing the flexibility of data use.
Universal Connectome: Tracks real-time data flows across the entire ecosystem, forming a data ecosystem map to ensure system transparency.
Non-custodial data storage: An important innovation of Vana is its unique way of data management. The users original data will not be on the chain, but the user can choose the storage location by himself, such as cloud servers or personal devices, which ensures that the user has full control over his own data.
Application ecosystem: Based on data, Vana has built an open application ecosystem where developers can use the data accumulated by DLP to build various innovative applications, including AI applications, and data contributors can receive dividend rewards from these applications.
This design enables Vana to create a fairer data value distribution mechanism while protecting user data privacy, providing an important data foundation for the development of decentralized AI.
Latest Developments
Vanas financing and partnership expansion continues to advance:
In February 2025, YZi Labs announced a strategic investment in Vana, and Binance founder CZ joined as an advisor.
In terms of ecosystem construction, Vana has built data projects covering multiple 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 US$50,000 to encourage developers to build DataDAO 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.
Participation Path Analysis
For investors who are interested in participating in the Vana ecosystem, there are mainly the following ways to participate:
Data contribution: Upload your social media data, browsing data, etc. to the corresponding data liquidity pool (DLP) to get corresponding token rewards. For example, you can get RDAT tokens by contributing data in the Reddit Data DAO. This is the most basic and lowest threshold way to participate.
Staking participation: Stake Vana tokens to your favorite DLP through DataHub and share the Vana block rewards obtained by the DLP. It should be noted that only the top 16 DLPs can receive rewards, so it is very important to choose a high-quality DLP.
Ecosystem co-construction: Participants with certain expertise can try to create new data liquidity pools. As the creator of a new DLP, you need to design specific data contribution goals, verification methods, and reward parameters, and implement a contribution proof function that can accurately assess the value of data.
Vana represents an important innovation at the intersection of blockchain technology, data economy, and artificial intelligence. By building a decentralized data platform, Vana aims to redefine data ownership and value distribution, providing fair returns to data creators while providing high-quality training resources for AI development.
3. Kite AI: A technological breakthrough in AI-native public chains
Kite AI is a native Layer 1 blockchain project focused on the AI field, built on the Avalanche framework. It is committed to solving the various challenges faced by traditional blockchains in handling AI assets, especially how to achieve transparent ownership and incentives for AI data, models, and intelligent contributions. Kite AI proposes four core technical innovations:
PoAI consensus mechanism: Proof of Attributed Intelligence is a consensus mechanism pioneered by Kite AI. Through a verifiable contribution record system on the chain, it accurately tracks the value contribution of data, models, and AI agents. The project has designed a dynamic reward pool mechanism to distribute revenue according to the contribution ratio, effectively solving problems such as data black box and model plagiarism in the traditional AI economy.
Composable AI subnets: Kite AI adopts a modular architecture to support developers to build industry-specific AI collaborative ecosystems on demand. For example, in the medical subnet, patient data can be encrypted and authorized to pharmaceutical companies for AI model development. The benefits are distributed to data subjects, model developers, and subnet maintainers in a certain proportion, creating a win-win ecological environment for all parties.
AI Native Execution Layer: Kite AI is building an on-chain AI native execution layer that specializes in AI computing tasks such as inference, embedding, and fine-tuning/training. Through this layer, users can authorize smart contract wallets to execute inference calls and interact with models. 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.
Decentralized Data Engine: Kite AI ensures that data creators receive fair benefits in AI workflows. The platform has built-in compliance modules that comply with regulations such as GDPR/CCPA, meeting data privacy requirements around the world and reducing compliance costs for developers.
These technological innovations enable Kite AI to create a more fair and transparent value distribution environment for AI developers and data providers, and promote the decentralized development of AI technology.
Development Status
Kite AI launched the incentivized testnet on February 6, 2025, which is the first AI-native Layer 1 sovereign blockchain testnet. The testnet performed well after it went online:
Less than 70 hours after the testnet went online, the number of connected wallets exceeded 100,000. As of now, a total of 1.95 million wallets have joined the Incentivized Testnet V1, of which more than 1 million wallets have interacted with the AI agent, with a total of more than 115 million calls.
The project has a strong background and is built by an experienced Silicon Valley team. The co-founders all have deep technical leadership experience in the field of artificial intelligence and have worked for top technology companies such as Uber, Salesforce, and Databricks. The core team members come from industry-leading companies such as Google, BlackRock, Uber, and the NEAR Foundation, and have academic backgrounds from top universities such as MIT and Harvard.
In terms of capital support, the project has received investments from top institutions such as General Catalyst, Hashed, Hashkey, Samsung Next, and has established technical partnerships with Eigenlayer, Sui, Avalanche, AWS, etc.
As a member of the Avalanche InfraBUILDL(AI) program, Kite AI plays an active role in advancing the Avalanche artificial intelligence ecosystem. This collaboration aims to make Avalanche the leading blockchain for AI applications.
As the scale of the global data economy is expected to exceed US$70 billion in 2025, Kite AI is expected to become an important infrastructure for data ownership confirmation and monetization, and its development potential is worth looking forward to.
Participation Opportunity Analysis
There are several ways to participate in the Kite ecosystem early on:
Testnet participation: Kite AIs testnet is now open, offering generous incentives for early participants. Investors can start participating through the official website (gokite.ai) or the testnet portal (testnet.gokite.ai), experience network functions and have the opportunity to receive testnet rewards.
Application development: Investors with development capabilities can try to deploy AI-driven DApps on Kite AI and explore innovative scenarios such as on-chain model training and data markets. The platform provides developers with a wealth of tools and support, lowering the development threshold.
Subnet deployment: Kite AI has prepared a token airdrop plan for the earliest team to deploy AI subnets, encouraging developers to create specialized AI subnets. For investors with expertise in specific industries, this is a good opportunity to use their expertise to obtain additional returns.
Early Contributor Points: Users who actively participate in the construction of the Kite AI ecosystem will receive points rewards and priority ecological resource support. These points may be converted into specific tokens or other rights in the future.
4. Nillion: Frontier Exploration of Privacy Computing
Through its unique blind computing technology, Nillion is redefining how sensitive data is handled, opening up new avenues for the future of digital privacy.
Nillion is a decentralized public network based on an innovative cryptographic primitive called Nil Message Compute (NMC), which allows network nodes to operate in a non-traditional blockchain manner. Founded in November 2021, the project is led by forward-thinking innovators such as Alex Page and Andrew Masanto, with the goal of creating a system that can securely process high-value data without exposing sensitive details.
Nillions 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 a variety of cutting-edge privacy protection technologies:
Multi-party computation (MPC): enables multiple nodes to collaborate on computing functions without disclosing their private inputs, achieving joint computing without sharing data.
Fully Homomorphic Encryption (FHE): allows direct operations on encrypted data, ensuring that the data remains encrypted from beginning to end, providing privacy protection throughout the entire process.
Zero-knowledge proof (ZKP): provides a way to verify calculations without disclosing any underlying data, enhancing the trustworthiness of the system.
Nada language: This is a domain-specific language designed for creating secure MPC programs. It simplifies the development process of privacy-preserving applications and reduces the learning curve for developers.
Nillions network architecture consists of three main layers: the processing layer (responsible for secure computing), the coordination layer (NilChain, managing inter-node communication), and the connection layer (connecting external systems as a gateway). This multi-layer architecture enables Nillion to provide powerful computing power 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 go live in March 2025 (this month). The total supply of Nillion tokens is 1 billion, which are expected to be distributed when the mainnet is launched.
In terms of financing, Nillion completed a $25 million financing led by Hack VC on October 30, 2024. Investors include well-known institutions such as HashKey Capital and Animoca Brands, as well as angel investors from projects such as Arbitrum, Worldcoin and Sei. This round of financing brings Nillions cumulative financing amount to $45 million, providing sufficient financial support for the long-term development of the project.
In terms of ecological expansion, Nillion has established integration relationships with multiple mainstream public chains such as NEAR Protocol, Aptos, Arbitrum, Mantle, Sei, etc. Through cooperation with NEAR Protocol, Nillion aims to enhance privacy tools and enable developers to innovate more effectively in the DeFi field.
In terms of the AI ecosystem, Nillion has established cooperation with multiple AI-related projects, including Ritual, Crush AI, Skillful AI, Virtuals Protocol, etc. For example, Virtuals Protocol is the largest multimodal AI proxy protocol at present. By cooperating with Nillion and using its secure computing infrastructure to support private training and reasoning of AI models, it has achieved a perfect combination of AI and privacy.
For a more detailed introduction to the Nillion ecosystem project, please refer to our previous articles:
https://x.com/BiteyeCN/status/1881297074228252702
Ecosystem Participation Strategy
With the upcoming launch of the Nillion mainnet, there are multiple ways for retail investors to participate in its ecosystem:
Token Economic Participation: Although Nillions airdrop qualification check has been closed on February 3, 2025, there will be more opportunities to participate in Nillions token economic system with the launch of the mainnet. According to official information, the Nillion airdrop will reward up to 75 million NIL tokens to community members and early builders.
Developer Ecosystem Participation: Nillion provides developers with a wealth of tools and resources to support the creation of privacy-preserving applications:
Node Deployment Kit (NDK): simplifies the process of joining the network and managing nodes, lowering the technical threshold
Nada language: Designed for creating secure MPC programs, making it easier for developers to build privacy-preserving applications
Application areas: Developers can create Nillion-based applications in multiple areas, including:
Artificial intelligence: Processing data and reasoning without exposing sensitive information
Personalized Agents: AI agents that store, compute, and process private data
Privacy-focused model reasoning: AI models that securely process private data
Privacy knowledge base and search: Encrypted storage of data while providing search capabilities
Network node operation: As a decentralized network, Nillion provides participants with the opportunity to operate nodes. By running nodes, users can contribute computing resources and receive corresponding rewards while helping to maintain the security and decentralization of the network.
5. Sahara AI: A platform for building a new economy of AI assets
Project Development
The core concept 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 hopes to lower the entry barrier for AI and allow every participant to share the dividends of industry growth. The project has successfully obtained a total of US$43 million in financing led by Binance Labs, Polychain Capital, and Pantera Capital.
The platform’s technical architecture consists of three key components:
Sahara Blockchain: Providing a foundation for secure, transparent transactions and efficient AI lifecycle management for the ecosystem
AI infrastructure: Distributed collaborative training and service capabilities that support advanced algorithms and computing frameworks
Sahara AI Marketplace: A decentralized exchange for AI assets
Together, these components form a complete ecosystem that supports the entire process from data collection and annotation to model training, deployment, and monetization.
Latest development progress
The Sahara AI project is in a rapid development phase, and its testnet has gone through several important stages:
In December 2024, Sahara AI launched the first phase of the data service platform Beta version test network, which attracted more than 780,000 users to apply, of which more than 10,000 candidates were qualified to participate in the first batch. In this phase, participants can contribute to the AI ecosystem and receive rewards by completing data collection, optimization and labeling tasks.
In February 2025, Sahara AI launched the second phase of the testnet, expanding the platform’s contributor base and introducing additional bounty opportunities. This phase further strengthens user participation in shaping the future of decentralized AI.
The latest development is that Sahara AI announced that it will launch a public testnet called SIWA on March 10, 2025. This is considered to be the last major test before the launch of the Sahara AI mainnet and TGE, and may also be the last chance for participants to earn airdrop rewards (called points).
Sahara AI has released its 2024-2025 annual roadmap, which includes several key milestones:
Q4 2024: The data service platform and test network have been launched, and users can receive rewards through data collection and labeling.
Q1 2025: AI Marketplace is launched, providing development tools and data service extensions, supporting model development, training and deployment, and introducing an early access program.
Q2 2025: Launch the Sahara Studio tool suite, covering model training, deployment, and workflow management, to further optimize the developer experience.
Q3 2025: Sahara Chain mainnet is released, providing a 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 to discover and support the worlds most promising AI x Web3 innovation projects. The program focuses on two tracks: AI infrastructure and AI applications. Teams with MVP maturity and above are welcome to participate. Successfully selected projects will have the opportunity to fully access the Sahara AI ecosystem and obtain exclusive technical support, market development resources and investment opportunities.
Ecosystem Participation Strategy
For users interested in participating in the Sahara AI ecosystem, here are the main ways to participate:
1. Join the waitlist and testnet
The first step to participate in the Sahara AI ecosystem is to join the official waitlist:
Visit the Sahara AI official waitlist page
Fill in the required information and submit the application form
Selected users will be given access to the testnet
Complete various tasks in the testnet to accumulate Sahara points
It is particularly noteworthy that the SIWA public testnet, which will be launched on March 10, 2025, may be the last chance to obtain airdrop rewards before the mainnet TGE, and users interested in participating should hurry up and apply.
2. Participate in Legends events
Sahara AI also offers an activity called Legends that allows users to collect fragments and mint NFTs:
Visit the Sahara Legends event page and log in to connect your wallet
Explore five unique desert-themed areas and start collecting fragments
Invite friends to join the event to earn extra fragments
Use the collected fragments to mint Soulbound Desert Guardian NFTs
Collect mascot NFTs from each desert and merge them to create an exclusive Fennec Fox NFT
3. Contribute to data service platform
Sahara AI’s data service platform provides users with the opportunity to earn rewards through data contribution:
Participants can choose high-value data tasks from multiple fields such as creator economy, finance, science, etc.
After completing the task, the platform will reward the user based on their contribution, accuracy and consistency
A ranking list is set up to encourage outstanding performers
All rewards are issued in the form of points, laying the foundation for the subsequent token distribution within the ecosystem
VI. 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 and building a more open, transparent and efficient technology ecosystem. In the future, this track will continue to promote technological innovation and advance the evolution of artificial intelligence towards a more decentralized and collaborative development direction.
