The artificial intelligence (AI) industry has been booming in recent years, especially with the emergence of breakthrough technologies like ChatGPT, attracting $25 billion in investment in 2023 alone, five times that of 2022. This massive influx of capital fully demonstrates people's positive expectations that AI will become a trillion-dollar industry. However, the AI field is currently quite fragmented, and different AI models cannot learn from each other, which severely limits their functionality. In addition, special permissions are usually required to connect it with other applications or data, which further increases the complexity. To better understand the future development direction of AI, we need to take a deep look at an innovative project - Bittensor.
Bittensor Project Overview
Bittensor is a project founded by AI researchers Ala Shaabana and Jacob Steeves in 2019. Initially, Bittensor was envisioned as a Polkadot parachain, but in March 2023, it made a strategic shift and decided to develop its own proprietary blockchain. Bittensor aims to capture the economic potential of artificial intelligence by taking a decentralized path. Its core concept is to use cryptocurrency as a mechanism to incentivize machine learning nodes around the world and promote a decentralized approach to AI development.
Bittensor's protocol transforms machine learning into a tradable commodity, thereby encouraging the rapid spread of knowledge, like an ever-expanding library. By enabling these nodes to train and learn collaboratively, Bittensor introduces a new paradigm that enhances the collective wisdom of the network by integrating incremental resources, thereby expanding the overall contribution of individual researchers and models.
Center Structure and Composition
Bittensor's architecture is designed to support a robust AI ecosystem through a decentralized network:
Miner Layer: This layer is the core of AI-driven innovation within Bittensor, where miners host and run diverse AI models.
Validator Layer: Validators play a key role in maintaining the integrity and consensus of the blockchain, ensuring that the network operates according to established rules.
Enterprise Layer: Dedicated to developing cutting-edge applications, using the network's AI capabilities to solve complex problems.
Consumer Layer: The final layer serves end users and organizations, providing network-generated solutions and services.
Bittensor as an Oracle
Bittensor also acts as an oracle, connecting blockchain systems with external data. In this way, it allows AI and blockchain technologies to combine to create innovative solutions. The Bittensor ecosystem relies on its unique subnet dynamics, each offering different rewards, which is well suited for a wide range of AI applications. This setup promotes diversity and the generation of new ideas, serving areas that may be overlooked by large AI companies. At the same time, it uses a single TAO token ecosystem to support these activities, giving token holders a big say in the direction of AI growth within the network.
Bittensor Machine Learning Methods and Mechanisms
Bittensor connects two key types of participants in the network:
Validators: responsible for maintaining the integrity of the blockchain, ensuring that transactions and operations comply with the rules of the network.
Off-chain machine learning miners: they provide AI services by hosting and running AI models that perform a variety of tasks from data analysis to generating opinions.
This bridge enables secure and efficient cooperation between blockchain operations and AI services.
Domain Details
Supply Side - AI Layer (Miners): Miners who host AI models, which are the source of Bittensor AI capabilities. These models perform tasks and generate value through machine learning.
Supply-side - Blockchain layer (validators): Validators manage and evaluate AI models hosted by miners. Their role is to ensure that these models meet the standards of the network and actively contribute.
Demand-side - Building applications on validators: Developers build applications on validators to leverage specific AI capabilities provided by miners. This creates a demand-driven ecosystem where developers can acquire and fund AI resources as needed.
Distributed Model of Experts (MoE)
Bittensor uses a distributed model of experts (MoE) to optimize AI predictions, improving the accuracy and efficiency of solving complex problems by coordinating multiple specialized AI models. This approach combines the unique advantages of each model to produce more accurate and comprehensive results, which is better than the traditional single model approach. For example, when we want to generate Python code with Spanish comments, AI's multilingual model and code expertise model can be combined to produce results together. This provides a superior solution compared to a single model.
Proof of intelligence
Proof of intelligence is a mechanism used by the Bittensor network to reward nodes for adding useful machine learning models and results. Similar to proof of work (PoW) and proof of stake (PoS) in blockchain networks, proof of intelligence requires nodes to perform machine learning tasks to prove their intelligence rather than solving mathematical puzzles. If the node's machine learning work is accurate and valuable, it has a greater chance of being selected to add new blocks to the chain and receive TAO tokens as rewards. In order to receive rewards in the Bittensor network, servers must not only generate valuable knowledge, but also be recognized by the majority of validators. With this consensus mechanism, Bittensor incentivizes valuable contributions, promotes cooperation, and guarantees the security of the blockchain.
Ecosystem
The Bittensor ecosystem, driven by $TAO tokens, represents an innovative approach to the field of decentralized artificial intelligence, and its special subnet structure is critical to the integrity and performance of the ecosystem. Bittensor provides 32 slots for these subnets to promote a competitive but dynamic environment that drives innovation. This reflects Bittensor's commitment to inclusivity and its strategic focus on quality over quantity. Note that subnets in Bittensor are where real value is created through competition and cooperation.
The blockchain technology of this ecosystem ensures transparency and security, bringing new possibilities to the field of artificial intelligence.
Conclusion: Bittensor has redefined the development path of artificial intelligence through decentralization. Its unique architecture and mechanism not only breaks the monopoly of the traditional AI field, but also provides opportunities for more developers and researchers to participate. With the continuous development of the Bittensor ecosystem, we have reason to believe that it will occupy an important position in the field of artificial intelligence in the future and become an important force in promoting the advancement of AI technology.