AI has enormous economic potential, and Bittensor aims to seize this opportunity by adopting a decentralized approach.
Author: Greythorn
Project Name: Bittensor
Project Type: Artificial Intelligence (AI)
Code Name: $TAO
Cryptocurrency Ranking: #30
Market Cap: $3.3 billion
FDV: $3.3 billion
Circulating Supply: $62.3 million (29.69% of total supply)
Maximum Supply: $21 million
Introduction
The artificial intelligence industry has been flourishing in recent years, especially with the emergence of breakthrough technologies like ChatGPT, which attracted $25 billion in investments in 2023 alone, five times the amount in 2022. The influx of such massive capital clearly demonstrates people's positive expectations for AI becoming a trillion-dollar industry.
However, what signs indicate that AI will continue to improve in the future? Here are a few key points:
First, the field of artificial intelligence is currently quite fragmented. Different AI models cannot learn from each other, severely limiting their capabilities. Additionally, obtaining special permissions is often required to connect them with other applications or data, further increasing complexity.
Second, the barrier to entry for AI is quite high. Training AI models requires substantial resources, leading to a situation where this field is mainly dominated by large corporations.
Although cryptocurrency is still in its early stages of adoption, it has already shown potential as a powerful tool for incentivizing and organizing distributed resource networks. Furthermore, by leveraging blockchain technology, AI applications can achieve interoperability, enhancing their collaborative capabilities.
Especially recently, some exciting success stories have emerged in the field of AI cryptocurrency, and people are beginning to recognize these opportunities.
Source: GrayScale Research
Therefore, we are at a crossroads for AI: on one hand, there is a decentralized and resource-intensive field of artificial intelligence, and on the other, there are clear market opportunities. What we need now is a core solution that can match the two, and this is exactly what Bittensor offers, which is truly worth paying attention to.
Bittensor is shifting the control of artificial intelligence from large companies to a broader community, changing the landscape of AI development. Its protocol transforms machine learning into a tradable commodity, encouraging the rapid dissemination of knowledge, much like an ever-expanding library.
Project Overview
Bittensor was founded by AI researchers Ala Shaabana and Jacob Steeves in 2019, initially envisioned for the Polkadot parachain. However, in March 2023, it underwent a strategic shift, deciding to develop its own proprietary blockchain aimed at using cryptocurrency as an incentive mechanism for global machine learning nodes, promoting a decentralized approach to AI development. By enabling these nodes to collaborate in training and learning, Bittensor introduces a new paradigm that enhances the collective intelligence of the network by integrating incremental resources, thereby expanding the contributions of individual researchers and models as a whole.
Source: Bittensor Website
Decentralized Structure and Composition
Bittensor's architecture aims to support a robust AI ecosystem through a decentralized network:
Miner Layer: This layer is the core of Bittensor's AI-driven innovation, where miners host and run a diverse range of AI models.
Validator Layer: Validators play a crucial role in maintaining the integrity and consensus of the blockchain, ensuring that the network operates according to established rules.
Enterprise Layer: Devoted to developing cutting-edge applications, leveraging the AI capabilities of the network to solve complex problems.
Consumer Layer: Serving end users and organizations, providing solutions and services generated by the network.
Source: Revelo Intel
Bittensor as an Oracle
Bittensor also serves as an oracle, connecting the blockchain system with external data. This allows the combination of AI and blockchain technology to create innovative solutions.
Network Dynamics
Bittensor's ecosystem relies on its unique subnet dynamics, with each subnet offering different rewards, making it highly suitable 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. Additionally, it uses a single TAO token ecosystem to support these activities, giving token holders significant influence over the direction of AI growth within the network.
Source: Bittensor
Bittensor Machine Learning Methods and Mechanisms
Bittensor connects two key participants in the network:
Validators: Responsible for maintaining the integrity of the blockchain, ensuring that transactions and operations comply with the network's rules.
Off-chain machine learning miners: They provide AI services by hosting and running AI models, performing various tasks from data analysis to generating insights.
This bridge makes secure and efficient collaboration between blockchain operations and AI services possible.
Domain Details
Supply Side - AI Layer (Miners): Hosts AI models that are the source of Bittensor's AI capabilities. These models perform tasks through machine learning and generate value.
Supply Side - Blockchain Layer (Validators): Manages and evaluates the validators hosting AI models. Their role is to ensure that these models meet the network's standards and actively contribute.
Demand Side - Building Applications on Validators: Developers build applications on validators, utilizing specific AI capabilities provided by miners. This creates a demand-driven ecosystem, where developers can access AI resources as needed and fund them.
Source: Greythorn Internal
Source: David Atterman
Distributed Expert Model (MoE)
Bittensor employs a distributed expert model (MoE) to optimize AI predictions, enhancing the accuracy and efficiency of solving complex problems by coordinating multiple specialized AI models. This approach integrates the unique strengths of various models, producing more precise and comprehensive results compared to traditional single-model methods. For example, when generating Python code with Spanish annotations, the multilingual AI model and the code expertise model can collaborate to produce superior solutions compared to a single model.
Source: Greythorn Internal
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 demonstrate their level of intelligence, rather than solving mathematical puzzles. If a 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 a reward. To earn rewards in the Bittensor network, servers must not only generate valuable knowledge but also gain approval from the majority of validators. By adopting this consensus mechanism, Bittensor incentivizes valuable contributions, promotes collaboration, and ensures the security of the blockchain.
Ecosystem
The Bittensor ecosystem is driven by the $TAO token and represents an innovative approach to decentralized artificial intelligence. The unique subnet structure is crucial for the integrity and performance of the ecosystem. Bittensor provides 32 slots for these subnets to promote a competitive yet dynamic environment, fostering innovation. This reflects Bittensor's commitment to inclusivity and its strategic focus on quality over quantity. It's important to note that subnets in Bittensor are where true value is created through competition and cooperation.
The blockchain technology of this ecosystem ensures transparency and security, while the Bittensor API facilitates participation by providing necessary tools and guidance.
Participants can engage in community building as subnet owners, validators, or miners, and each role is crucial for the health of the ecosystem. The Yuma consensus mechanism is a key feature that promotes consensus by rewarding contributors with TAO tokens.
Strategic partnerships, such as the collaboration between OpSec and Tensorage, are crucial for advancing decentralized artificial intelligence technology and providing seamless data processing and storage solutions.
The integration of platforms like AITProtocol with the Bittensor network highlights its expanding influence and the diverse applications of decentralized artificial intelligence models.
Given Bittensor's potential for development, we expect these partnerships and integrations to continue to evolve, making Bittensor a key player in shaping the future of artificial intelligence.
Token Economy
Overview of TAO Token Economics
Maximum Supply: 21 million TAO tokens.
Issuance Schedule: Tokens will be fully issued within 256 years.
Current Price: $624.97.
Market Cap: $3.92 billion, ranked 27th.
Fully Diluted Valuation: $3.9 billion, ranked 49th.
Current Circulating Supply: 6.25 million TAO tokens, accounting for 29.75% of the maximum supply.
Total Supply: 6.25 million TAO tokens.
Token Generation and Distribution
TAO tokens are created through mining and network validation activities to foster the development of a decentralized ecosystem.
A halving event occurs every 10.5 million blocks, with a total of 64 halving events planned over approximately 45 years.
Rewards are distributed at a rate of 1 TAO per block, approximately every 12 seconds, totaling about 7,200 TAO tokens per day. These rewards are allocated to miners and validators.
Token Utility
Holding TAO tokens provides access to various digital resources on the network, including data and core insights based on artificial intelligence. It's important to note that the value of TAO tokens is directly linked to the artificial intelligence services provided by the Bittensor network. As the importance and utility of these artificial intelligence services continue to increase, the demand for TAO tokens is expected to rise accordingly.
Source: Bittensor
Competitors
Artificial intelligence technology has a wide range of applications in the blockchain industry, including machine learning, neural networks, decentralized storage, AI agent training, markets, and data processing.
Given this diversity, directly comparing Bittensor to projects like Akash may not be entirely appropriate. Akash provides services similar to cloud computing, while Bittensor focuses on specific areas such as AI model training.
Further research led us to Gensyn, an emerging project that seems to be a closer competitor to Bittensor. Let's take a closer look at it.
Getting to Know Gensyn
Ben Fielding and Harry Grieve met in the Entrepreneur First accelerator program in early 2020 and began collaborating to create Gensyn, focusing on research until the second quarter of 2023. They expect to launch the testnet this year.
In June 2023, Gensyn successfully raised $43 million in Series A funding, with investors including a16z, Protocol Lab, CoinFund, Canonical Crypto, Eden Block, and several angel investors.
Gensyn is building a network based on an L1 PoS protocol, utilizing the Substrate framework for peer-to-peer communication.
Gensyn aims to create a highly scalable ML network, providing a global pool of computing resources accessible to everyone. Its goal is to make AI model training possible on any device globally by connecting various computing devices, from idle data centers to personal laptops with GPUs. This initiative aims to significantly increase the availability of global ML computing resources.
Contrasting with Bittensor:
One key difference between Gensyn and typical computing networks is its unique approach to checking computational work. It introduces a new system called "Probabilistic Proof-of-Learning," which uses data from gradient optimization, a key method in machine learning. This technology provides a scalable and reliable way to verify work without replication, making machine learning tasks more efficient.
In contrast, Bittensor offers two key advantages:
First, it employs a Mixed Expert (MoE) model to enhance AI predictions by allowing multiple specialized AI models to collaborate. This collaboration aims to improve the accuracy and reliability of AI results.
Second, Bittensor adopts a unique machine learning approach called AI Legos. The concept of AI Legos is to make AI development more open, decentralized, accessible, and efficient using blockchain. Built on the idea of "Compute Legos," it focuses on the versatility of general-purpose computing to foster machine learning innovation. Bittensor's vision is to establish a global community network of ML nodes to address specific complex challenges while enhancing the collective intelligence and capabilities of AI models.
However, a different scenario could be envisioned, where various protocols can integrate and enhance the overall decentralized artificial intelligence ecosystem on a permissionless blockchain. For example, Akash, Gensyn, and Bittensor could collectively handle inference requests, demonstrating the synergies between different AI solutions on-chain.
Comparison with Centralized AI Models:
Comparison with Centralized AI Models
Comparing Bittensor with centralized AI models, such as the recently valued at $29 billion OpenAI by Microsoft, can clearly demonstrate its potential. Bittensor's decentralized approach aims to achieve the compound and broader integration of AI intelligence, which, if successful, could surpass the capabilities and value of OpenAI. This has sparked discussions about the enormous potential value of Bittensor.
Through its decentralized model approach, Bittensor allows AI models to share insights and build on each other's discoveries, reducing redundant work. According to Bittensor:
"The only thing bigger than Open AI or any other centralized alternative is their combination."
Source: Bittensor
Source: Bittensor
Bullish Factors
Bittensor's token economics are designed to encourage fair distribution practices, ensuring consistent incentive mechanisms among network participants. With the expansion of the network participant base, TAO tokens are expected to experience exponential growth.
Currently, approximately 89% of all circulating TAO tokens have been staked, amounting to 5,561,230 TAO (out of a total supply of 6,254,373 TAO).
The issuance design of TAO tokens involves a decreasing creation rate over time, with a complete halt upon reaching the total supply limit. This strategy will shift the incentive focus of miners to direct payment for tasks.
Source: Bittensor
The artificial intelligence market is expected to reach $1.8 trillion by 2030, demonstrating the enormous economic potential of AI technology.
Since significant advancements by OpenAI, AI-related crypto assets have performed well, highlighting the growing interest and investment in this field.
Bittensor aims to create a self-sustaining ecosystem for machine learning, fostering the development and application of AI models. This vision lays the foundation for innovation and practical applications in the AI field.
Bittensor's network hosts over 4,000 AI models with a total of 10 trillion model parameters. This scale not only surpasses models like GPT-3 (with 175 billion parameters) but also underscores the significant scale and diversity of Bittensor in AI development.
Bittensor ranks among the top 25 projects and has not yet received any Tier 1 token listing information. While it's currently unclear whether this should be viewed as a positive factor, its strong position raises the possibility of broader TAO token accessibility.
Bearish Factors
While Bittensor has not faced widespread criticism, there are still some critics. Some question its high valuation despite the simplicity of its code. Others, such as Kyle, the founder of Multicoin VC, specifically criticize how TAO validators select top miners, noting a lack of broad application background (unlike Chat GPT) and the inability of validators to judge. He believes there needs to be stronger connectivity between the user interface and model updates. We recommend maintaining an open mind, considering the diverse viewpoints in the crypto space.
Decentralized artificial intelligence, while having enormous potential, is still in its early stages and carries risks. Our past research on AI projects has shown that many decentralized platforms have not undergone sufficient durability testing. They often struggle to attract users and heavily rely on developers to keep them running.
Another significant challenge is the access barrier to extensive databases and cutting-edge AI hardware compared to the resources available to large tech companies. This limitation poses a considerable risk to the growth and effectiveness of platforms like Bittensor.
Conclusion
VanEck's latest research refers to Bittensor as the "Bitcoin of machine intelligence." The research outlines its network's economic incentives for AI/ML models, involving "miners" developing AI models and "validators" evaluating model outputs. However, considering developers can create dApps on Bittensor and the network is built as a mainnet containing many smaller subnets focused on specific AI domains, I believe a more appropriate comparison is to view Bittensor as the Ethereum of decentralized AI.
Artificial intelligence holds tremendous economic potential, expected to reach a market value of $1.8 trillion by 2030, and Bittensor aims to seize this opportunity through its decentralized path.
During the DeFi boom, Cardano's market cap approached $100 billion. Bittensor's current market cap is $4.2 billion, and especially if the trend in artificial intelligence is similar to DeFi, its growth potential remains an exciting prospect.
At Greythorn, we always advocate for a cautious approach to these markets. If you are interested in this article, we invite you to contact us. You can explore our previous research and visit our website for more information.
Disclaimer
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