Summary of Sok: Decentralized Ai (deai), by Zhipeng Wang et al.
SoK: Decentralized AI (DeAI)
by Zhipeng Wang, Rui Sun, Elizabeth Lui, Vatsal Shah, Xihan Xiong, Jiahao Sun, Davide Crapis, William Knottenbelt
First submitted to arxiv on: 26 Nov 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a Systematization of Knowledge (SoK) for blockchain-based decentralized AI (DeAI) solutions. It proposes a taxonomy to classify existing DeAI protocols based on the model lifecycle and analyzes the functionalities of blockchain in enhancing the security, transparency, and trustworthiness of AI processes. The authors identify key insights and research gaps in developing DeAI protocols, highlighting critical avenues for future research. This work aims to provide a comprehensive understanding of state-of-the-art DeAI development, particularly for active industry solutions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary DeAI combines blockchain and AI technologies to make AI systems more transparent, secure, and trustworthy. The paper shows how blockchain helps with this by ensuring fairness, security, and transparency in AI data and model contributions. It also explores the strengths and weaknesses of current DeAI protocols and highlights areas where researchers need to focus. |
