# Connecting AI Learning and Blockchain Mining in 6G Systems

arXiv: https://arxiv.org/abs/2104.14088 · HTML: https://mlsanity.com/paper/2104.14088/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 15 references that are in the map.
- First posted on arXiv 29 Apr 2021.

## Builds on (most cited first, 5 of 5)

- [In-Datacenter Performance Analysis of a Tensor Processing Unit](https://mlsanity.com/paper/1704.04760/) (2017)
- [The Roadmap to 6G -- AI Empowered Wireless Networks](https://mlsanity.com/paper/1904.11686/) (2019)
- [A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks](https://mlsanity.com/paper/1805.02707/) (2018)
- [Energy-recycling Blockchain with Proof-of-Deep-Learning](https://mlsanity.com/paper/1902.03912/) (2019)
- [Proof of Luck: an Efficient Blockchain Consensus Protocol](https://mlsanity.com/paper/1703.05435/) (2017)

## Abstract (arXiv)

The sixth generation (6G) systems are generally recognized to be established on ubiquitous Artificial Intelligence (AI) and distributed ledger such as blockchain. However, the AI training demands tremendous computing resource, which is limited in most 6G devices. Meanwhile, miners in Proof-of-Work (PoW) based blockchains devote massive computing power to block mining, and are widely criticized for the waste of computation. To address this dilemma, we propose an Evolved-Proof-of-Work (E-PoW) consensus that can integrate the matrix computations, which are widely existed in AI training, into the process of brute-force searches in the block mining. Consequently, E-PoW can connect AI learning and block mining via the multiply used common computing resource. Experimental results show that E-PoW can salvage by up to 80 percent computing power from pure block mining for parallel AI training in 6G systems.