In this work, we propose a straightforward method to derive Elliptic Curve Digital Signature Algorithm (ECDSA) key pairs from embeddings created using Deep Learning and Metric Learning approaches. We also show that these keys allows the derivation of cryptocurrencies (such as Bitcoin) addresses that can be used to transfer and receive funds, allowing novel Blockchain-based applications that can be used to transfer funds or data directly to domains such as image, text, sound or any other domain where Deep Learning can extract high-quality embeddings; providing thus a novel integration between the properties of the Blockchain-based technologies such as trust minimization and decentralization together with the high-quality learned representations from Deep Learning techniques.
As we mentioned in the previous section, there are very few published works related to AI Machine Learning and Blockchain cryptocurrencies. In @cite_23 , the author explores some Blockchain applications in a highly-speculative manner. One of the applications that the author cite is the usage of the Blockchain by AI entities as a mean to provide a permanent transparent public record that can be reviewed and inspected.
@cite_23
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Reports on the concept of blockchains, a new form of information technology that could have several important future applications. One is blockchain thinking, formulating thinking as a blockchain process. This could have benefits for both artificial intelligence and human enhancement, and their potential integration. Blockchain thinking is outlined here as an input-processing-output computational system.