The fundamental tension is that unlike web distribution of static content, which has enormous scale advantages due to very low marginal costs, the RAG [Retrieval-Augmented Generation] pattern has high marginal costs (10-1000X) that scale linearly. While token costs remain high, for general scholarly applications outside of specialty practitioners, the central business or product challenge will be how to generate sufficient incremental revenue to offset the vastly higher compute costs to use GenAI technology to generate responses to queries.
| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |
