Deep Probabilistic Decision Learning Returns Perfect Flow to Operations

FlowOps enables optimal experience, predictions and decisions in the operations of factories and supply chains. In human brains, there are three key learning functions related to how we sense, predict and decide. Findings in computational neuroscience [1, 2] suggest that different parts of brain areas play a distinct but connected role in each function. These can be equated with the three Explainable AI (XAI) engines in Noodle.ai's The interplay between deep learning and probabilistic learning are similar to a human brain's thinking fast and slow like in Kahneman's System 1 and System 2. System 1 is a fast, intuitive, heuristic, deterministic, differentiable, and more affective mind, whereas System 2 is a slow, deliberate, logical, probabilistic, integrating, and more cognitive mind. Deep learning (Sentinel) enables fast, scalable, and associative pattern detections from high-dimensional, noisy and temporally correlated data, using differential optimizations on flexible functions with deterministic model parameters.