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by lappa
994 days ago
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This seems half-baked and there are numerous faulty assumptions in this article.
For example, Bitcoin miners cannot computer gradients. Their ASICs can only calculate double-sha256. Additionally, the premise of sending gradients of models trained on private data while retaining privacy seems problematic. While you likely can't reverse it to calculate the batch's contents, it is leaky. Further, gradient calculations are not a good proof of work. A good proof of work is difficult to calculate and easy to verify (i.e. an extremely low hash value). The core premise, using blockchains to store terabytes of models and datasets, doesn't make any sense whatsoever. The problems highlighted in this article however are valid, and it would be great to see something like IPFS for datasets and models. |
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Well perhaps one way is you could have another LLM take a look at the data you are submitting and have it predict p(useful|not useful) , and create an incentive for users to generate authentic data