Part 9/11:
Scaling Towards Human-Like Intelligence
The ultimate vision is for this architecture to evolve with scale:
As memories grow into the trillions
As models are refined through continuous self-evaluation and meta-learning
As the integration of semantic search accelerates data retrieval
The researcher emphasizes that big data fuels AI development, with the Nexus serving as the central repository. Microservices will periodically extract relevant data subsets for training, fine-tuning, and performance assessment, akin to autoML and ML ops cycles.