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Evidence, methods, and operating insight for decisions that must work in the field.

23Published articles

Bayesian

Calibrating Probability Before Committing Sales Resources

In the previous Parts 1 and 2 of the [BA02. Exa Bayesian Inference: The Invisible Hand of Sales—A 60-Day Gamble] episode, we explored how the Bayesian engine establishes 'prior beliefs' and tracks the trajectory of probabilities through 'signals' and 'silence.' Now, we hold in our hands the pure posterior probability $ P_{raw} $, precisely calculated by the Bayesian parameters α and β. However, it is not over yet. The final decision-making process remains. Even with a 60% probability, the weight of the decision can vary completely depending on whether it was derived from a single meeting or dozens of negotiations.

January 5, 202614 min read

Bayesian
likelihood
bayesian

Business Theory

When Silence Becomes Evidence

BA02.[App. 2] The Paradox of Silence: Entropy and the Geometry of Logarithmic Weighting

January 3, 20267 min read

Bayesian
Likelihood
Logarithmic Weighting

Business Theory

Turning Sales Evidence into a Live Probability

This article explains the mathematical principles and effectiveness of the Bayesian engine covered in the [BA02 Episode]. The goal is to precisely predict sales success probabilities in an uncertain business environment. At its core, it addresses the process of deriving optimal decision-making indicators by combining the Beta distribution, which quantifies past experiences, and the Binomial distribution, which captures real-time signals from the field. In particular, it emphasizes maximizing the system’s real-time performance and computational efficiency by utilizing Conjugate Prior distributions, which allow for immediate updates without complex calculations. Furthermore, this model adopts a Recursive Estimation method that makes immediate judgments whenever data occurs, securing technical validity optimized for modern business. Consequently, this document clearly demonstrates how sophisticated mathematical modeling transforms vague intuition into reliable, data-driven insights.

January 2, 202610 min read

Bayesian
Bayes Factor
Bayesian Update

Business Decision Science

The Invisible Hand of Sales

An ExaWin+ decision case that updates field observations and customer responses as Bayesian evidence, tracks win probability over 60 days, and allocates limited sales resources to better customers and actions.

January 1, 202612 min read

Bayesian
Bayes
Bayesian

The History of Reinforcement Learning: From the Bellman Equation to Deep Reinforcement Learning

I chose Reinforcement Learning (RL) as the first topic of this blog because of my personal interest in a field that has developed from classical theory along a different trajectory from rapidly advancing deep learning and LLM AI agents, while continuing to influence the real world, and because reinforcement learning is also being integrated into Exa-Solution, Exavion’s extended ERP and AI-integrated enterprise application.

December 20, 20257 min read

AI
Reinforcement Learning
RL

Bayesian

The Silent Factory: Bayesian Diagnosis of a Short Shot

Quantifying the realm of intuition: A case study of dynamic decision-making using Bayesian updates. How does data become a weapon for decision-making in a manufacturing site ruled by uncertainty? This article vividly shows a real-world application of Bayesian statistics through the process of resolving 'Short Shot' defects in an injection molding factory.

December 19, 20258 min read

Bayesian
MCMC
Inference

Reinforcement Learning Before Mathematics: From Behavioral Experiments to MDP

Many learners who are new to Reinforcement Learning struggle early on because they do not clearly understand the conceptual difference and relationship between the Markov Decision Process (MDP) and Reinforcement Learning (RL). To reduce this confusion, it is necessary to first clarify how the two concepts are related.

July 8, 20255 min read

AI
Reinforcement Learning
RL

All Articles

23 articles in the current library

Calibrating Probability Before Committing Sales Resources

When Silence Becomes Evidence

Turning Sales Evidence into a Live Probability

The Invisible Hand of Sales

The History of Reinforcement Learning: From the Bellman Equation to Deep Reinforcement Learning

The Silent Factory: Bayesian Diagnosis of a Short Shot

Reinforcement Learning Before Mathematics: From Behavioral Experiments to MDP

All Articles

23 articles in the current library

Calibrating Probability Before Committing Sales Resources

When Silence Becomes Evidence

Turning Sales Evidence into a Live Probability

The Invisible Hand of Sales

The History of Reinforcement Learning: From the Bellman Equation to Deep Reinforcement Learning

The Silent Factory: Bayesian Diagnosis of a Short Shot

Reinforcement Learning Before Mathematics: From Behavioral Experiments to MDP