Hello everyone,
I recently had an idea about incentivizing miners to help machine learning engineers and AI researchers train deep learning models. Instead of using computation power to guess numbers for SHA256, the idea is to switch to computing the loss function threshold, which is a measure of how well an AI model performs on given inputs.
Here’s how it would work:
- A machine learning engineer submits a deep learning model implementation to the blockchain and requests for training. The value of the loss function of the AI is easy to compute given some input.
- The node providers see the assignment and begin training the models.
- Suppose a node provider has superior hardware and is able to train the AI faster than other miners. Once they finish training, they start broadcasting the weights of the model to other miners, which is the result of a well-trained AI.
- Other miners receive the weights and compute the loss function and the Delta of the loss function. If both values are below some threshold that the machine learning engineer required, then the AI is considered good enough and can no longer be significantly optimized.
- If the other node providers agree that the AI is well-trained, then consensus is reached, and the node provider who trained the AI receives tokens as an incentive.
The main idea is to switch from the number guessing game to computing the loss value, while keeping the rest of the process the same.
However, there are some unclear parts, such as whether validators who verify the value of the loss function should be incentivized. According to the logic of BTC, they should not. Also, not every machine learning engineer may be able to define a robust AI, and it is possible that the loss can never reach the required threshold. For example, the gradient may not be able to go down because the data or model is not good enough.
What do you think about this idea?