Research Summary
The report discusses Bittensor, an open-source protocol that aims to decentralize AI and machine learning through blockchain technology. The project seeks to address the centralization of AI power within a few companies. Bittensor’s ecosystem includes subnets, validators, and miners, with its native token, $TAO, playing a crucial role in the network’s operation and reward distribution.
Key Takeaways
Bittensor’s Decentralization of AI
- Addressing Centralization: Bittensor’s primary objective is to tackle the issue of AI centralization and the concentration of power within a few companies. It aims to democratize AI by providing open access to a repository of machine intelligence for global innovation.
- Subnets for Customization: The introduction of subnets in the Bittensor ecosystem allows anyone to create their own subnetworks with custom incentives and different use cases, fostering a wider range of services within the ecosystem.
Network Growth and Tokenomics
- Network Expansion: Bittensor’s dashboard indicates strong growth in network participants and stakers/validators, with 61.5k accounts and 5 million $TAO staked, representing 88% of the supply.
- Token Supply and Distribution: Bittensor’s native token, $TAO, has a total supply of 21 million. The token was “fair launched” in 2021, with no pre-mined tokens. The token’s halving cycle ensures that rewards per block halve for every 10.5 million blocks.
Decentralized Governance and Funding
- Decentralized Emission Distribution: The Route network distributes emissions across subnets based on consensus from key delegates, removing sole reliance on any single entity.
- Funding Infrastructure Development: Bittensor has no treasury. The Opentensor Foundation funds current infrastructure developments through delegation rewards, while third-party validators fund their own developments through delegation.
Competition and Risks
- Competitive Landscape: Bittensor’s main competitors are centralized AI companies like OpenAI, Midjourney, and Bard (Google). Despite the intense competition, Bittensor aims to disrupt the industry with its decentralized AI solution.
- Potential Risks: The report identifies high operating expenses and intense competition as potential risks for Bittensor.
Investor Participation and Project Development
- Investor Participation: Investors such as DCG, Polychain Capital, FirstMark Capital, and GSR participate in the network as miners or validators. $TAO tokens are not allocated through ICOs, IDOs, private sales, or privileged allocations but must be earned through active participation in the network.
- Project Development: Bittensor was founded by Jacob Robert Steeves & Ala Shaabana in 2019. The original mainnet (Kusangi) went live in Jan 2021 but was later halted and migrated to the current chain, Nakamoto, launched in Nov 2021.
Actionable Insights
- Understanding Bittensor’s Approach: Stakeholders should familiarize themselves with Bittensor’s unique approach to decentralizing AI and machine learning, including its use of subnets and the role of validators and miners in the network.
- Monitoring Network Growth: Observing the growth of Bittensor’s network, including the number of accounts and the amount of $TAO staked, can provide insights into the project’s adoption and user engagement.
- Assessing Competitive Landscape: Stakeholders should assess the competitive landscape of decentralized AI and consider how Bittensor’s approach differentiates it from competitors like OpenAI, Midjourney, and Bard (Google).
- Considering Potential Risks: Stakeholders should consider the potential risks identified in the report, including high operating expenses and intense competition, when evaluating Bittensor.
- Tracking Project Development: Keeping track of Bittensor’s project development, including changes to its mainnet and investor participation, can provide valuable insights into the project’s progress and potential future direction.
