Joseph Dung
Project OwnerResearcher and Software Developer
Our technical approach leverages the latest advances in self-improving LLMs, paraconsistent logic, formal concept analysis, conceptual blending, and evolutionary algorithms to create a seamlessly integrated system that demonstrates emergent capabilities beyond what any individual component could achieve. The implementation in MeTTa and Hyperon provides a concrete path toward realizing these theoretical advances in practical systems with applications spanning scientific discovery, materials science, drug development, and sustainable technology innovation. This proposal builds upon prior work in hybrid concept synthesis while significantly leveraging where necessary AI models for self play.
This RFP seeks proposals that experiment with concept blending techniques and formal concept analysis (including fuzzy and paraconsistent variations) using the MeTTa programming language within OpenCog Hyperon. The goal is to explore methods for generating new concepts from existing data and concepts, and evaluating these processes for creativity and efficiency. Bids are expected to range from $30,000 - $60,000.
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The goal is to perform exhaustive background research in developing a working Technica Paper along side developing the practocal Software Components that will 1. Link our AI models inspired by the aformentioned brealthroughs with the Metta eco-system 2. Finetune ways by which bi-directional learning can occur within these contradictory worlds (Statistical versus Symbolic) using a derived Knowledge Graph as he bridge betwee the two worlds.
Exhaustive Technical Paper offering insights on the possibility of Symbolic systems leveraging the generalization advantages from statistical systems to improve or fine tune their concept blending proceses. Software demonstrating this process with the benchmarks to show how these systems can co-exist or evolve together and their coparative benchmarks measured against pure symbolic or pure statistaical methods.
$60 USD
Pushing forward to AGI where Metta's Symbolic systems effortlessly concept blend but are behind the scenes Statistical systems that underpin their connective capabilities. In the end the ability of the new approach to succesfully apply cross domain knowledge to generate entirely novel types of knoweldge or discoveries will be a welcome success.
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