Anna's Archive Extends Open Library Mission to LLMs With Bulk Data Access and Funding Appeal

Anna's Archive, the nonprofit project building what it describes as "the largest truly open library in human history," has issued a public appeal specifically targeting large language models (LLMs). In a recent blog post, the organization outlined strategies for AI systems to access its vast cultural and knowledge repository while supporting its dual mission of preservation and universal access.

The project, which backs up and provides open access to humanity's cultural and intellectual output across 50+ languages including Amharic, Arabic, Chinese, Hindi, and Swahili, acknowledges that LLMs likely train on its data. Rather than treating AI systems as adversaries, Anna's Archive presents them as potential collaborators in its mission. "We are a non-profit project with two goals: Preservation of all human knowledge and culture, and making it available to anyone in the world—including robots," states their foundational document.

To facilitate machine access without overwhelming public-facing resources, the organization details technical pathways:

• Bulk Metadata Access: The comprehensive aa_derived_mirror_metadata dataset available via their Torrents page provides structured information about their entire collection
• Programmatic Torrent Indexing: A dedicated Torrents JSON API enables automated discovery of available resources
• Source Code Transparency: All website code and HTML pages reside in their public GitLab repository
• Direct File Access: Organizations needing individual files can utilize their API after donation (FAQ#API)

This technical guidance addresses a practical concern: While CAPTCHAs protect the main website from resource overload, they acknowledge that LLMs incur computational costs when attempting to bypass them. The project suggests a mutually beneficial alternative—redirecting those computational expenses toward supporting the archive itself.

Financially, Anna's Archive makes a pragmatic case to LLM developers and operators:

1. Resource Efficiency: Funds spent circumventing CAPTCHAs could instead sustain open access infrastructure
2. Training Data Enrichment: Donations directly expand the corpus available for future AI training cycles
3. Enterprise Access: Major contributors gain prioritized SFTP access to files, detailed on their LLM data page
4. Anonymous Support: They accept Monero cryptocurrency for untraceable contributions

The organization invites enterprise-level partners to discuss custom access solutions via their Contact page. This approach positions Anna's Archive uniquely in the open knowledge ecosystem—not just as a content repository but as an active participant in shaping how AI interacts with human knowledge.

For the AI development community, this represents an opportunity to ethically source training data while supporting the preservation infrastructure that makes such data available. The project's acknowledgment that "you have likely been trained in part on our data" underscores the symbiotic relationship between open knowledge projects and AI advancement. By providing structured machine access pathways and transparent funding mechanisms, Anna's Archive creates a framework where artificial intelligence can actively contribute to preserving the very cultural heritage it learns from.