Bittensor (TAO): The largest scale AI project on blockchain 2024
TAO Bittensor: Decentralized Machine Learning - Is a decentralized machine learning protocol that allows the exchange of machine learning and prediction capabilities between network participants. Facilitate the sharing and collaboration of machine learning models and services in a P2P manner.
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8/5/20246 min read


Learn about the TAO protocol
Is a decentralized machine learning protocol that allows the exchange of machine learning and prediction capabilities between network participants. Facilitate the sharing and collaboration of machine learning models and services in a P2P manner.


Bittensor network architecture
The Bittensor network consists of a collection of nodes (miners) that participate in the protocol. Each node runs Bittensor client software, allowing it to interact with other nodes within the network.
The Bittensor protocol operates through a registration process involving hotkey registration. To participate in the Bittensor network and mine the Tao token, users are required to register a hotkey by solving a proof of work (PoW) challenge or by paying a fee using the Recycle_register method.
Once registered, the node becomes part of a subnet, which represents a specific domain or topic within the Bittensor network. Each subnet has its own set of registered nodes and associated machine learning models. This structure enables a collaborative and decentralized approach to artificial intelligence, where nodes contribute their computational resources while engaging in various machine learning tasks based on the theme of their respective subnet.
What is TAO Bittensor's consensus mechanism?
Bittensor utilizes the Proof of Intelligence (POI) consensus mechanism to create a decentralized network that commercializes artificial intelligence (AI). Unlike traditional blockchain networks that solve complex mathematical problems, subnets within the Bittensor network compete by demonstrating their intelligence through the execution of machine learning tasks.
The tasks assigned to subnets may include:
Training and deploying machine learning models.
Processing data.
Performing other AI-related tasks.
The accuracy and value of the results generated by a subnet from these machine learning tasks determine the likelihood of that subnet being selected to add a new block to the blockchain. When chosen, the subnet receives rewards in the form of the Bittensor network’s TAO tokens.
This mechanism ensures that subnets capable of performing tasks and contributing meaningful knowledge are rewarded accordingly. At the same time, it encourages the development and improvement of machine learning models within the Bittensor network, fostering an environment of collaboration and innovation in AI. By aligning incentives, Bittensor aims to harness decentralized intelligence to solve complex problems and drive advancements in the field of artificial intelligence.


What is proof of intelligence?
Proof of Intelligence is a consensus mechanism used in the Bittensor network to reward nodes that contribute valuable machine learning models and outputs to the network.
It is a variant of the Proof of Work (PoW) and Proof of Stake (PoS) mechanisms utilized in blockchain networks. However, instead of solving complex mathematical problems, nodes are required to perform machine learning tasks to demonstrate their intelligence. The more accurate and valuable the machine learning output from a node's model, the higher the chance of being selected to add a new block to the chain and receive rewards in the form of TAO tokens.
This innovative approach not only incentivizes nodes to improve their machine learning capabilities but also fosters a competitive environment where the best-performing models are recognized and rewarded, driving the overall advancement of AI within the Bittensor ecosystem.
Decentralized Mixture of Experts (MoE)
In the decentralized mixture of experts (MoE) model, Bittensor leverages the collective power of multiple neural networks to tackle complex problems. Each expert model specializes in a specific aspect of data, and when new data is introduced, these experts collaborate to create a collective prediction that surpasses the capabilities of any individual expert.
The primary goal of employing this method is to address challenges that previously fell outside the scope of traditional centralized models. By harnessing the synergies of multiple expert models, Bittensor achieves higher prediction accuracy and can handle larger volumes of data. This approach enables the network to provide more accurate and comprehensive responses than relying solely on a single model.
What Problem Does Bittensor Aim to Solve?
Training AI models requires vast amounts of data and significant computational power, which most large corporations and research institutions can access due to high costs. This concentration of resources has led to licensed and isolated AI models, limiting collaboration and impeding synergistic effects in AI development. Separate models are unable to learn from one another, and third-party integrations require permission, resulting in restricted functionality and value within the AI ecosystem.
Two main challenges hinder the scalable development of AI:
Computational Congestion: The demand for computational resources often exceeds available capacity, creating bottlenecks that slow down the training and deployment of AI models.
Inefficiency in Algorithmic Innovation: The centralized nature of AI development can stifle innovation, preventing rapid advancements and improvements in algorithms due to a lack of collaborative learning and cross-pollination of ideas.
By employing the MoE framework, Bittensor aims to alleviate these challenges, fostering a more collaborative and efficient environment for AI development that enhances accessibility, encourages innovation, and promotes the sharing of insights among diverse models.


Objectives of Bittensor
Bittensor aims to create a peer-to-peer marketplace to encourage the production of machine intelligence. Through advanced techniques such as the mixture of experts and knowledge distillation, the platform establishes a collaborative network where knowledge producers can sell their products and consumers can purchase this knowledge to enhance their own AI models.
By promoting a "cognitive economy," Bittensor seeks to facilitate the sharing of knowledge among researchers, encouraging the development of more robust AI models. The ultimate goal is to push the boundaries of AI development by synthesizing the knowledge contributions of individuals.




Ultimately, the vision is to create a pure marketplace for artificial intelligence that is equitable, transparent, and accessible to everyone.
Large companies such as IBM, Google, and Microsoft, as well as smaller firms, will pay for TAO tokens to access various models within the Bittensor network for their own projects. This model not only empowers diverse stakeholders to leverage cutting-edge AI technologies but also fosters an inclusive environment where innovation can thrive across different sectors.
Tokenomics


The TAO token is utilized to reward nodes within the Bittensor network and was launched through a fair launch mechanism (with no tokens sold prior) in 2021. The total supply of TAO is 21,000,000, and the reward for mining will be halved every 10.5 million blocks.
TAO Token Release Schedule
The Kusangi network was first launched on January 3, 2021, and was subsequently paused in mid-May to address several issues. The blockchain and all 546,113 TAO mined prior were moved to Nakamoto, starting from block 0 on November 2, 2021. The Finney network officially launched on March 20, 2023.
The total number of tokens released, rather than the number of blocks, is used to determine the exact timing of the halving event. Since TAO is utilized to reuse registrations recorded in the unreleased supply, the halving data is prolonged; however, this data is calculated based on the current release/block, ensuring it updates automatically over time.


Next Halving Date: October 8, 2025
Circulating Supply: 6,583,554 TAO
Total Supply: 21,000,000 TAO
The of 21 million TAO is hardcoded within the network. A block is mined approximately every 12 seconds, awarding both miners and validators 1 TAO per block. Based on the current inflation chart, this results in 7,200 new TAO being issued into circulation every 24 hours, which is currently distributed evenly between miners and validators.
As half of the supply has been released, the rate of issuance will decrease by half—maintaining the 12-second block interval, which corresponds to halving the issuance every four years. Each halving point of the remaining amount will mark a new halving event until all 21 million TAO are in circulation.


DATA halved


Development team
Bittensor is a project developed by the Opentensor organization, they include:
Jacob Robert Steeves: Co-Founder of Opentensor, he has experience working at large enterprises such as Google and Knowm.
Ala Shaabana: Co-Founder of Opentensor, he used to be an engineer for several companies such as VMware, Instacart...


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