Evidence, methods, and operating insight for decisions that must work in the field.
A missing submarine and airliner, a codebreaking war fought on paper, and navigation to the Moon. Through dramatic episodes in history, discover how priors, likelihoods, posteriors, and the weight of evidence change the next judgment.
The Dreyfus affair and the authors of The Federalist, insurance premiums and spam filters, combined models and superforecasters. Follow Bayesian reasoning in everyday life as small pieces of evidence are compared, accumulated, and used to revise judgments.
There is a gap between a busy day and a day spent completing important work. Through ExaRing+’s Rings and execution records, its Bayesian feedback loop, and Jordan’s story, this article examines how judgments about oneself change the next action.
BA03. [On-Time Material Inbound: Bayesian MCMC] The Real Game in Business is the Fight Against Uncertainty
A factory floor of burning dominoes, a fragmented day, and Bayesian recursive estimation: how ExaRing+, Ring, Activity TX, Timebox, AI, and Success Intelligence turned one production manager into an architect of time.
The ultra-high-rise condo pre-sales market in Ho Chi Minh City. A showdown between an intuition-driven ace salesman and a data-driven rookie. This novel format explains how the EXAWin Bayesian engine becomes a tool for victory in the Southeast Asian real estate sales competition. Part 1: The calm before the storm — two salesmen in Saigon.
The conclusion of the 480-unit condo pre-sales war in Ho Chi Minh City. President Phan's contract, Tuấn's awakening, and the turnaround led by Park Jun-hyuk's EXAWin. The showdown between intuition and data finally reaches its conclusion.
This is the first article in a technical explanation series identifying the operating principles of the EXA engine, which played a major role in the novel-style series [BA03 On-Time Material Inbound: Bayesian MCMC]. Since this series covers Mixture Distributions and MCMC (Markov Chain Monte Carlo) Gibbs Sampling—which are advanced techniques in Bayesian inference—the content may be deep and the calculation process somewhat complex. Therefore, we intend to approach this in a detailed, step-by-step manner to make it as digestible as possible, and it is expected to be a fairly long journey. We recommend reading the original novel first to understand the overall context. Furthermore, as Bayesian theory expands its concepts incrementally, reviewing the episodes and mathematical explanations of BA01 and BA02 beforehand will be much more helpful in grasping this content. The preceding mathematical concepts and logic are being carried forward.
