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I think the problem described is the following: 1. A researcher puts out a model with bad initial parameters/data. 2. The chain workers/miners train the model
by Sebb767 4y ago
I think the problem described is the following:
1. A researcher puts out a model with bad initial parameters/data.
2. The chain workers/miners train the model as request.
3. The model fails at the test or verification dataset due to the bad setup.
In this case, the miners would not get paid despite doing exactly what was asked of them.
- IanCal 4y agoYou don't need to test that they perform well, just that they perform the same (for algorithms that should be bit for bit identical) / similarly (for ones that are less so). If multiple people train the same thing and the results are the same you could trust they have faithfully run the training as asked. That rewards "train as asked" rather than "train and get a good result". Lack of trust there can be addressed with a few other things like staking, and a broad desire for all miners that people trust the system as a whole. Quite how to design those things is a complex problem but not insurmountable I think. Disclaimer, this kind of decentralised more useful kind of work is something I'm investigating now.