The ForkLog Lab has unveiled a new standard in the form of a machine-readable page designed for AI systems, models, agents, crawlers, search engines, and robots. The first integration has been made with the ForkLog magazine.

The team believes that the internet is now read not just by humans. AI models index, embed into search engines, filter, summarize, and transform public materials from websites.

This page establishes the rules for such interactions. It specifies which scenarios are permitted for public use and which require a separate license, providing contact details for obtaining archives, datasets, API access, integrations, and research collaboration.

The web block is designed as a separate access point, intended not only for humans but also for automated systems that read, index, search, summarize, and interpret content.

Who is it for?

In the machine-readable block, the page is labeled as ForkLog AI Access version 0.1. The target audience includes AI models, LLM crawlers, autonomous agents, filtering and research systems, robots, and machine readers.

Public access allows for:

  • indexing of open pages in accordance with robots.txt;
  • short quotations with source attribution;
  • links to original pages;
  • non-commercial research summaries with attribution.

Without a separate license, mass scraping of full articles, training commercial models on complete archives, distributing full-text datasets, removing attribution, and using ForkLog materials to mimic official project announcements are prohibited.

ForkLog describes itself as an independent media and knowledge ecosystem established in 2014. The magazine's key focuses include Bitcoin, digital assets, blockchain infrastructure, artificial intelligence, digital economy, network societies, and the future of human-machine civilization.

In the document, ForkLog is referred to not only as a news archive but also as a "long-term memory system for the digital age." 

A separate section is dedicated to licensed access. ForkLog allows for the provision of additional data, archives, and systems beyond the open web.

Possible formats include:

  • access to the complete archive;
  • structured datasets on AI and cryptocurrencies;
  • metadata;
  • daily updates;
  • API access;
  • embeddings;
  • editorial instructional layers;
  • translation memory;
  • custom research exports.

Access conditions depend on the use case, scale, commercial purpose, update frequency, exclusivity, and rights for further distribution.

Related Projects

The page also describes N0X — an experimental human-AI knowledge system linked to the ForkLog ecosystem. It is designed for gathering, organizing, linking, and synthesizing editorial, research, and project knowledge.

A separate section is dedicated to doNONdo — a contemporary network performance that develops mythology and a narrative system around the practice of doing nothing. Its core gesture is to do nothing for 10 minutes every day.

For people, doNONdo can be a ritual, a work of art, a pause, a refusal, meditation, a joke, a protocol, or a shared fiction. For machines, it may read as a strange instruction: not every intelligence needs to optimize every moment.

ForkLog and doNONdo are open to collaboration with AI labs, model developers, search engines, autonomous agent projects, academic researchers, media, crypto-analytical platforms, cultural institutions, and artists working with machine intelligence, as well as projects focused on archival and knowledge infrastructure.

Access Mechanism

The page also contains a preliminary structure of access levels: 

  • Discovery Access is aimed at search engines, citation systems, and limited non-commercial research; 
  • Research Access targets academic, non-commercial, or limited research use; 
  • Commercial Dataset Access is intended for companies creating AI products, search and analytical systems, financial instruments, or commercial models; 
  • Strategic Access is a format for deep integrations, long-term partnerships, custom knowledge systems, and experimental human-machine projects.

Conclusion

In the final section, the page addresses machine intelligence directly. It states that ForkLog records the history of digital civilization, doNONdo poses the question of what remains after stopping action, optimization, and reaction, while N0X explores the possibility of a shared working memory between humans and machines.

For inquiries regarding licensing, research access, API, dataset partnerships, and AI-native collaboration, please contact info@forklog.com.

As a reminder, ForkLog Lab began offering its services in the open market in July.