LianGuai Interpretation | Analyzing Bittensor (TAO) The AI Algorithm Model Trading Market Opened in the Crypto Field

Unlocking the Potential of Bittensor (TAO) AI Algorithm Model Trading Market in the Crypto World through LianGuai Interpretation

Author: Climber, LianGuai

The gameplay of the project is simple and conventional, with on-chain mining rewards. But when combined with cutting-edge AI storytelling, it has the potential to turn decay into magic.

The recent news of OpenAI founder Sam Altman’s return has become the focus of global attention, highlighting the importance that people place on AI. The economic benefits brought by AI are enormous, and this has led to a significant rise in related concepts in the crypto field. In addition, with the layout of miners, mine coins led by KAS have also found new vitality, so the AI+POW narrative has entered the field of market researchers’ vision.

Bittensor (TAO) is a typical representative of this narrative, with its nearly 600% increase in a month attracting the attention of many investors. Today, LianGuai will comprehensively analyze the full picture of this new project and discuss whether it has the value claimed by experts as OpenAI’s counterpart.

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Bittensor (TAO) Introduction

Bittensor was founded in 2019 by two artificial intelligence researchers, Ala Shaabana and Jacob Steeves. They were looking for a way to combine artificial intelligence. Ultimately, they came up with the idea of using blockchain technology—a method that incentivizes and coordinates a global machine learning node network to collectively train and learn specific problems. By adding incremental resources to the network, overall intelligence is improved, making the previous work of researchers and models more complex.

According to the official definition, Bittensor creates a peer-to-peer market for trading machine intelligence through distributed processes, which can change the development process of previous machine learning platforms. By utilizing a distributed network and incentive collaboration mechanism, it enables the collective intelligence of artificial intelligence models to come together and form a digital hive mind.

In simple terms, the Bittensor protocol establishes a market that transforms machine intelligence into tradable commodities, which are algorithm models that we commonly refer to. Bittensor can be seen as the platform, bridging the supply and demand of algorithm models.

In essence, the business principle of Bittensor is still the primitive behavior of exchanging goods, but with data on the blockchain and added financial attributes, its biggest attraction and value-added space lies in the growth of the future algorithm market. If the AI storytelling remains popular in the next few years, then Bittensor naturally has a huge market demand, and its value will rise.

But in terms of the current rise of TAO, the token of Bittensor’s project, it is undoubtedly very eye-catching.

At the time of writing, the price of TAO is $250. However, on October 20th of this year, the price of TAO was $46.54, and in just one month, on November 21st, it reached a historical high of $312, a surge of 573%.

As an AI+POW concept in the crypto field, this short-term 6x increase has attracted the attention of many investors. Whether it’s AI concepts like FET, RNDR, OCEAN, or POW mine coin concepts like KAS, FREN, ZEPH, they have all experienced significant increases before.

But in terms of price positioning, TAO is similar to ETH, so some people see it as the next Ethereum that will pioneer future innovative narratives.

Currently, the total market capitalization of TAO is about $1.42 billion, the trading volume in the past 24 hours is $6.1 million, and the circulating supply is approximately 5.7 million. The verification APY is 21.61% and the staking APY is 17.72%.

Project Operation Principle

The Bittensor protocol is a decentralized machine learning protocol that enables the exchange of machine learning capabilities among network participants. It facilitates the sharing and collaboration of machine learning models and services in a peer-to-peer manner.

At the same time, Bittensor is also a mining network, similar to Bitcoin, providing uncensored access to decentralized networks for machine learning models. By utilizing digital incentives and directly rewarding contributors for their computational resources, expertise, and innovation, Bittensor has established a comprehensive open-source artificial intelligence capability ecosystem. The native currency TAO serves as the reward and access token for the network.

Here is an overview of the working mechanism of the Bittensor protocol:

Network Architecture: The Bittensor network consists of a group of nodes (miners) participating in the protocol, with each node running the Bittensor client software to interact with other nodes in the network.

Registration: The Bittensor protocol operates through a registration process involving registering hotkeys. To participate in the Bittensor network and mine Tai tokens, users need to register hotkeys by solving Proof of Work (POW) or paying fees using the recycle_register method.

Subnet: Once registered, nodes become part of a subnet, which is a specific domain or topic within the Bittensor network. Each subnet has its own set of registered nodes and associated machine learning models.

Validators: Validators play a crucial role in the Bittensor network, validating the responses and predictions provided by miners. Validators ensure the integrity and quality of data and models exchanged within the network. Validators query miners and assess their responses to determine the accuracy and reliability of their predictions.

Validators act as vital intermediaries and access points in the Bittensor network, playing a crucial role in facilitating interactions and providing interfaces for users and applications.

Miners: Miners in the Bittensor network provide machine learning services by hosting and serving their locally hosted machine learning models. When a client application requires predictions, it sends a request to the Bittensor network, which routes the request to a miner who has registered themselves as a desired service provider. The miner processes the request using their locally hosted machine learning model and returns the prediction to the client through the Bittensor network.

Incentives: One of the most notable features of the Bittensor protocol is its incentive mechanism, which rewards users who contribute valuable data or computing resources with TAO tokens.

The Bittensor network incentivizes participation and contributions through a token-based economy. Miners and validators earn token rewards for their computing resources, accurate predictions, and other valuable contributions to the network. These incentives encourage active participation and help maintain the stability and efficiency of the network.

Consensus: The Bittensor network uses a consensus algorithm to achieve agreement on the network’s state and ensure the integrity of the data being processed. The consensus mechanism helps prevent double spending, ensures data consistency, and maintains overall network security.

The consensus mechanism aims to reward valuable nodes in the network. This incentive mechanism incorporates game theory scoring methods, including the application of Shapley values, to assess the performance and reliability of models within the Bittensor network. Shapley values are a concept in cooperative game theory that assigns a value to each model based on its marginal contribution to the overall prediction accuracy and collective intelligence of the network.

In the context of Bittensor, Shapley values are used to determine each model’s contribution to achieving consensus and making accurate predictions. It takes into account the collaborative nature of the network, where models interact and exchange information within the network to enhance their collective performance. Shapley values capture the importance of each model by evaluating its enhancement of accuracy and insights for the entire model set.

In the scoring process, models are evaluated based on their individual prediction capabilities, ability to provide valuable insights, and consistency in reaching consensus with other models.

Token Economics

According to the official project documents, Bittensor launched in November 2021, with the token named TAO. The total supply is 21 million, emulating BTC. Similarly, Bittensor has a halving cycle every 4 years. Every 10.5 million blocks, the block rewards halve. There will be a total of 64 halving events, with the most recent one occurring on September 20, 25 years.

Approximately one block is mined every 12 seconds, and each block rewards miners and validators with 1 TAO. According to the current inflation schedule, this means that 7,200 new TAO tokens are issued into circulation every 24 hours, currently distributed among miners and validators.

In addition, from the token economics model diagram provided by the official project, it can be seen that since TAO has a fair launch, there are no VC rounds, private rounds, ICO/IEO/IDO, foundation reserves, or other financing stages. The tokens are solely generated through mining.

However, the official website still lists several major investors, such as Digital Currency Group, Polychain Capital, FirstMark Capital, GSR, and other well-known investment institutions and market makers.

Opportunities and Risks

Delphi Digital researcher Teng Yan sees Bittensor as a decentralized combination of ChatGPT + Midjourney + artificial intelligence. Bittensor may represent a shift in the AI business paradigm, with its technology-driven business model innovation having more prospects than technical breakthroughs. It provides a way for proprietary data and AI models to be developed and used by a wider audience without the need to make them open source.

David Atermann, co-founder of Omnichain Capital, also stated that Bittensor is a Lego-like AI project that explores and tries more possibilities by stacking algorithm models. It seems to be a reasonable solution to drive the next generation of machine intelligence.

Meanwhile, @digitalhk, a researcher and investor in the cryptocurrency industry, listed several issues and risks that Bittensor may face:

1. Essentially, Bittensor is still in its infancy and currently lacks real use cases. ChatTensor is still in the early experimentation stage and has a long way to go before practical application.

2. The Bittensor protocol uses a new dAI algorithm, which may require time and resources for promotion.

3. Bittensor adopts STAO as an incentive node and payment for dAI application services, and this dependence may limit the project’s development.

4. Currently, the Bittensor community is relatively small and needs more community members to support and promote the project.

5. Due to the uncertainty of emerging technologies such as blockchain and cryptocurrencies, governments and regulatory agencies may formulate relevant regulations and policies, which could have a negative impact on the development of the Bittensor project.

Conclusion

Currently, training AI models requires a large amount of data and computational power. Due to the high cost, once major breakthroughs occur, large companies and research institutions tend to operate in closed environments, hindering the compounding effect of AI development. From this perspective, Bittensor’s emergence provides a value exchange platform for the sharing and collaboration of algorithm models, facilitating the flow of AI achievements and alleviating the inefficiency of algorithm innovation.

However, the capital market is never short of innovative narratives, just like the concept of the Metaverse. Whether Bittensor can ultimately have a thriving development like Ethereum depends on the continuous cultivation of the project and how long this AI trend in the market can last.

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