Exploring WebAssembly AI Services on Cloudflare Workers

Edge networks present a significant opportunity for AI performance and applicability. Deploying edge AI services can be hard because AI is both computational and memory bandwidth intensive. Latent AI's mission is to enable ambient computing, regardless of any resource constraints. They develop developer tools that greatly reduce the computing resources needed to process AI on the edge while being completely hardware-agnostic. Their compression uses quantization algorithms to convert parameters for the AI model from 32-bit floating-point toward 16-bit or 8-bit models, with minimal loss of accuracy. The key benefit of moving to lower bit-precision is the higher power efficiency with less storage needed. Optimized AI services can process data closest to the source and perform inferences at the distributed edge.