Bitcoin mining is slow. It takes about 10 minutes to solve a block because to solve a block, miners must hash six variables, such that they produce a hash value with a high number of leading zeros – this is statistically extremely unlikely. The reason is because most Bitcoin mining operations use large warehouses to pull compute from asics, which costs a lot of money. The technical problem is how to produce low hash values from a hash of the block header. The main existing solution is using application specific integrated circuits or asics, which randomly hash values until a valid solution is found.
The assumption is that it is possible to statistically increase the odds of producing a valid block hash using a neural network to predict block header data. To facilitate machine learning, I constructed and cleaned a Bitcoin Block Header Dataset, which currently contains the data for the six block header variables of every block header from the network’s inception to February 2023. The dataset will be used to train a neural network to predict the next nonce value. By only guessing with nonces that have been predicted to solve a block via the cloud, a mining operation using AI could operate at a fraction of the cost compared to existing miners.
This is important for two reasons. First, it solves a critical technical challenge in the Bitcoin protocol, which will allow the network transaction times to speed up. Second, a miner who successfully uses a superior hashing algorithm via artificial intelligence will be able to mine Bitcoin on a laptop, so long as it has approximately 4TB of data space available. As a result, this would create a decisive competitive advantage compared to traditional mining operations which use thousands of asics computers.