Add ERC: Decentralized Embedding Registry #87
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Co-authored-by: Andrew B Coathup <28278242+abcoathup@users.noreply.github.com>
Co-authored-by: Andrew B Coathup <28278242+abcoathup@users.noreply.github.com>
cryptitalk
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There has been no activity on this pull request for 2 weeks. It will be closed after 3 months of inactivity. If you would like to move this PR forward, please respond to any outstanding feedback or add a comment indicating that you have addressed all required feedback and are ready for a review. |
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@abcoathup could you please assign this ticket to a proper reviewer? |
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The application https://app.cryptitalk.com/ will implement this proposal, we are about 70% done |
Need to wait for an ERC editor to review. |
eip-review-bot
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The commit 0ed91ab (as a parent of ce79b61) contains errors. |
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| ## Abstract | ||
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| By establishing a standardized RESTful API registration contract that handles requests for vectorized embeddings and responds with JSON-formatted output, any enrolled service provider can offer search or AI services, including conversational AI and completion tasks. This allows users to select their preferred knowledge source in a decentralized fashion. |
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I'm not particularly familiar with AI, and I suspect most of the EIP audience isn't either. Can you expand your abstract so that it's friendlier to readers more familiar with blockchain? For example, what is a "vectorized embedding"?
Further, your abstract should give a high-level (but still technical) overview of how your proposal solves the problem.
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| ## Motivation | ||
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| The emergence of embedding technologies enables information providers to arrange their data semantically using vectors of size N and to facilitate information retrieval or question-answering by measuring vector distances. One limitation of Google Search or ChatGPT AI is that it serves as a singular source of information, constrained to providing answers based on its pre-indexed or trained data sets. Given that Google/OpenAI may not possess exhaustive datasets and that individuals may have varying contexts for their searches or questions, there's a significant need for a decentralized system. Such a system would allow for the registration of various search or AI services, empowering users to explore and select their preferred data sources to align with their specific informational contexts. |
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Is "vectors of size N" a term of art, or could it be written as "arbitrarily sized sectors"?
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| The emergence of embedding technologies enables information providers to arrange their data semantically using vectors of size N and to facilitate information retrieval or question-answering by measuring vector distances. One limitation of Google Search or ChatGPT AI is that it serves as a singular source of information, constrained to providing answers based on its pre-indexed or trained data sets. Given that Google/OpenAI may not possess exhaustive datasets and that individuals may have varying contexts for their searches or questions, there's a significant need for a decentralized system. Such a system would allow for the registration of various search or AI services, empowering users to explore and select their preferred data sources to align with their specific informational contexts. | ||
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| ## Specification |
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Your specification section is way too sparse to be implementable. You'll need to fill this section out to the point that a reader can create a compatible implementation.
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There has been no activity on this pull request for 2 weeks. It will be closed after 3 months of inactivity. If you would like to move this PR forward, please respond to any outstanding feedback or add a comment indicating that you have addressed all required feedback and are ready for a review. |
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This pull request was closed due to inactivity. If you are still pursuing it, feel free to reopen it and respond to any feedback or request a review in a comment. |
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