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Forget training behemoths: ADMs slash memory overhead to just twice the inference footprint while guaranteeing geometric correctness and continuous adaptation.
Unlock geometric algebra's performance potential in neural networks and spatial computing by compiling directly from multi-way relationships, eliminating manual specialization and ensuring geometric correctness.
Imagine a compiler that understands the size and lifetime of your data so well it can automatically optimize memory allocation and representation, giving you design-time insights into performance.