Distributed Agentic Multi-Modal LLM Deployments

Future enterprise architectures for edge AI inference will be multi-modal. With core foundation model (FM)/LLM functions centralized (attention, MLP-FFNN, layer normalization, residual connection) and some functions distributed to edge (retrieval-augmented generation, input processing-tokenization/vector embedding/position encoding [maybe], guardrails, caching, inference optimization-sampling/beam search). In addition, in multi-modal architectures, convolutional neural networks (CNNs) will be integrated with the FM/LLM.