Research Summary
The report explores the intersection of cryptocurrency and artificial intelligence (AI), focusing on the potential of decentralized machine learning. It discusses the evolution of the internet and Bitcoin, highlighting the role of crypto-economic incentive schemes in coordinating decentralized efforts. The report also examines the potential of AI as the next frontier, the challenges of centralization, and the role of projects like Bittensor in creating a decentralized AI and machine learning training platform. It concludes by questioning the necessity of blockchain and tokens in this field.
Key Takeaways
Decentralized Machine Learning: A New Frontier
- AI and Crypto Intersection: The report explores the potential of combining AI and cryptocurrency to build a decentralized machine learning and intelligence market. This could democratize AI, similar to the self-custodial, permissionless, open-source DeFi system.
- Bitcoin’s Role: Bitcoin’s design created a decentralized supercomputer that automated task coordination, work verification, and payment settlement. This invention could be generalized beyond payments and smart contracts to include tasks like assigning and coordinating work among computers and humans.
- Centralization Challenges: The report highlights the centralization of AI technology due to the high costs of accessing compute resources from major cloud computing platforms. This centralization has undesirable effects and limits the development of cutting-edge models.
- Bittensor’s Role: Bittensor is a decentralized AI and machine learning training platform aiming to create a peer-to-peer market for machine intelligence. It rewards miners and validators with TAO tokens, leading to a competitive system where the best machine learning models are selected to receive relevant user queries.
- Questioning the Need for Blockchain and Tokens: The report questions the necessity of a token or native blockchain in this field. It suggests that rewards could be paid in other digital tokens, and a blockchain distributed consensus might not be necessary for reward allocation.
Actionable Insights
- Investigate the Potential of Decentralized AI: The report suggests exploring the potential of decentralized AI and machine learning platforms like Bittensor. These platforms could democratize AI and reduce the centralization of AI technology.
- Consider the Role of Crypto-economic Incentive Schemes: The report highlights the role of crypto-economic incentive schemes in coordinating decentralized efforts. These schemes could be used to solve complex problems and provide an alternative to centralized services.
- Assess the Need for Blockchain and Tokens: The report suggests assessing the necessity of blockchain and tokens in the field of AI and machine learning. It proposes that rewards could be paid in other digital tokens, and a blockchain distributed consensus might not be necessary for reward allocation.
