Williams, Andy2024-03-202024-03-202020-04-27https://doi.org/10.31730/osf.io/hpzb7https://africarxiv.ubuntunet.net/handle/1/1056https://doi.org/10.60763/africarxiv/1009https://doi.org/10.60763/africarxiv/1009https://doi.org/10.60763/africarxiv/1009The AI industry continues to enjoy robust growth. With the growing number of AI algorithms, the question becomes how to leverage all these models intelligently in a way that reliably converges on AGI. One approach is to gather all these models ingo a single library that a system of artificial intelligence might use to increase it's general problem solving ability. This paper explores the requirements for building such a library, the requirements for that library to be searchable for AI algorithms that might have the capacity to significantly increase impact on any given problem, and the requirements for the use of that library to reliably converge on AGI. This paper also explores the importance to such an effort of defining a common set of semantic functional building blocks that AI models can be represented in terms of. In particular, how that functional decomposition might be used to organize large scale cooperation to create such an AI library, where that cooperation has not yet proved possible otherwise. And how such collaboration, as well as how such a library, might significantly increase the impact of each AI and AGI researcher’s work.AGIArtificial General IntelligenceFunctional ModelingHuman-centric