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AI faces a trifecta of grand challenges: the Energy Wall, the AlignmentProblem and the Leap from Narrow AI to AGI. Contemporary AI solutions consumeunsustainable amounts of energy during model training and daily operations.Making things worse, the amount of computation required to train each new AImodel has been doubling every 2 months since 2020, directly translating tounprecedented increases in energy consumption.  The leap from AI to AGI requires multiple functional subsystems operating ina balanced manner, which requires a system architecture. However, the currentapproach to artificial intelligence lacks system design; even though systemcharacteristics play a key role in the human brain; from the way it processesinformation to how it makes decisions. System design is the key to alignment,one of the most challenging goals in AI. This difficulty stems from the factthat the complexity of human moral system requires a similarly sophisticatedsystem for alignment. Without accurately reflecting the complexity of thesecore moral subsystems and systems, aligning AI with human values becomessignificantly more challenging.  In this paper, we posit that system design is the missing piece in overcomingthe grand challenges. We present a Systematic Approach to AGI that utilizessystem design principles to AGI, while providing ways to overcome the energywall and the alignment challenges. This paper asserts that artificialintelligence can be realized through a multiplicity of design-specificpathways, rather than a singular, overarching AGI architecture. AGI systems mayexhibit diverse architectural configurations and capabilities, contingent upontheir intended use cases. It advocates for a focus on employing system designprinciples as a guiding framework, rather than solely concentrating on auniversal AGI architecture.

From the Pursuit of Universal AGI Architecture to Systematic Approach to Heterogenous AGI: Addressing Alignment, Energy, & AGI Grand Challenges