The team needs to be composed of experienced MeTTa and Prolog programmers having wide ranging experience with the addition of seasoned project management.

Recruit lower level developer and manager/evangelist.

$1 USD

Arguably this is the most important step. We need a team ready to really push Mettalog into mainstream. Without a synergy here we shouldn't proceed.

Deliver new server functionality and clear documentation to enable MeTTa programs running on Mettalog to respond to network requests.

MeTTa programs will load once upon initial invocation persist in memory and serve multiple users concurrently. With Python as the main control language developers will be able to use standard web servers like Apache and nginx as well as cloud services such as AWS EC2. Integration with popular libraries such as LangChain will allow MeTTa to be used as part of larger pipelines that combine symbolic reasoning with language model output. The system will support communication through the Model Context Protocol (MCP) enabling external language models (e.g. Claude ChatGPT) to send queries and receive structured responses from MeTTa programs.

$20,000 USD

This step is successful if the described functionality has been thoroughly exercised with documentation. Mettalog needs to reliably handle these scenarios.

New built in command(s) to enable the MeTTa knowledge graph to be a system of record supporting concurrent users not just read-only analytics.

Presently there is a “get-atom” MeTTa method. This will be extended to a new “get-atom-lock” method to prevent asynchronous updates. Other methods will be introduced if necessary. Thus the deliverable is source code enhancements for above as well as test cases documented.

$20,000 USD

This step is successful if tests are passed and documentation produced.

The MeTTa language is a unique language with a variety of potential uses but it is arguable that MeTTa lacks a determinate identity. Is it a knowledge graph? Is it LISP? Is it an alternative to a procedural language? Why does it insist on giving you all possible results? This makes it problematic to appeal to mainstream developers who in the age of LLMs do fundamentally need the stability of knowledge graphs for augmented generation and could potentially benefit. Some of the essential features of MeTTa are: * Reminds one of a network type database can be updated like a database (CRUD) * Capable of Turing completeness * Processes/returns all possible paths and results of a call by default while providing means of managing such an explosion (eg. the "collapse" statement) * Suited for general ontologies while also able to act as narrow AI * Poised to be anti-hallucinogenic stabilizer vis a vis generative AI * Could act in a RAG type role that is as a KNOWLEDGE GRAPH

This deliverable will concentrate on clear examples of MeTTa based applications in a symbolic Turing complete knowledge graph role and how this can support mainstream use (eg. LLMs).

$25,000 USD

This is probably the most challenging step of the project. The step will be successful if a completely coherent message can be made to mainstream developers supporting MeTTa's role in neurosymbolic architectures taking the form of an LLM front end and MeTTa back end.

Mettalog is a maturing fast MeTTa interpreter and transpiler based upon Prolog. Although largely complete some additional shoring up may be needed (if not covered under other funding).

1) Enable the easy installation of mettalog by apt docker and similar means without complexity or any suspense whatsoever regarding whether or not it works. It will work. 2) A highly reliable LSP server for programmer assistance (gives help while coding). 3) A largely functioning transpiler. If the transpiler is incomplete we must have a "fall through" for the interpreter. There is a working interpreter now, still reasonably fast, but it is slower than the transpiler which generates Prolog code directly.

$9,999 USD

All of the above work reliably.