A Bitcoin-native LLM: dataset, architecture and open questions

This specialized LLM aims to adeptly handle tasks such as script reasoning, UTXO graph traversal, script recommendation, and protocol-specific question-and-answer scenarios. It would require an extensive dataset composed of various sources integral to the Bitcoin ecosystem, including Bitcoin Improvement Proposals (BIPs), technical discussions from mailing lists and Delving threads, annotations from Bitcoin Core, as well as real-world annotated scripts and miniscripts.

The architecture for this Bitcoin-focused LLM includes a bifurcated design, consisting of a base model fine-tuned on a static corpus for script analysis and offline tasks, complemented by a tool-calling layer for live data queries interfacing with resources like Bitcoin's Core RPC and mempool.space API. This structure allows the model to operate effectively both with and without access to live data. The primary goal of this initiative is to facilitate better tools for wallet developers, protocol researchers, and transaction auditors without involving the LLM in direct transaction signing or key material handling.

Concerning benchmarks for evaluating general-purpose LLMs, developing robust (question, answer) pairs is crucial. These should be generated using both automated tools and human oversight to ensure accuracy and relevancy. This process might benefit greatly from community-driven platforms such as Stack Exchange, where insights are regularly included in newsletters, indicating a successful model of integrating community-sourced information into larger projects. Specifically, platforms like Bitcoin Stack Exchange, Bitcoin Ops, and Bitcointalk are identified as valuable resources for sourcing high-level technical content essential for training specialized educational programs.

Furthermore, understanding the diverse opinions and ongoing debates within the Bitcoin community highlights the importance of maintaining attribution in discussions. This ensures that different viewpoints and trade-offs, argued by various experts, are accurately represented, preserving the context in which each argument was made. For instance, the AssumeUTXO discussion illustrates differing expert opinions on trust levels required within the software, emphasizing the importance of not only sourcing accurate information but also presenting it in a way that reflects the multifaceted nature of technical discussions in Bitcoin development. Engaging comprehensively with these materials and discussions can significantly enrich one's understanding of Bitcoin, providing deeper insights into the complex decisions that shape its technology and governance.