Decision Trace Model — A Framework for Turning Human Decision-Making Processes into Organizational Assets
When discussing AI systems, many people tend to focus on topics such as:
Model accuracy
Data volume
...
人工知能:Artificial Intelligence
Can AI Approach Meaning? — Graph Neural Networks: A Technology Between Continuous Approximation and the Discontinuity of Meaning —
In the previous article, I explained a three-layer structure for describing AI decisions:
Ontology
DSL (...
How Should AI Decisions Be Described? — The Decision Representation Structure Required by the Decision Trace Model —
In previous articles, we have described AI systems as
factories that mass-produce decisions.
AI is not merely software...
Decision Trace Model and Ledger — Why AI Systems Need “Immutable History” —
When designing AI systems, many companies typically think in the following way:
Build a model
Create an ...
AI Quality Engineering — Why the Quality Engineering Becomes Important Again in the Age of AI —
When people talk about AI, most discussions tend to focus on topics such as:
Model accuracy
Data volume
...
AI Factory Model — AI Will Become a Manufacturing Industry, Not Just Software
AI Factory Model — AI Is Becoming a Manufacturing Industry
When people talk about AI, most imagine the same thing.
AI ...
Boundary Design: The Seven Boundaries That Safely Stop AI — What AI systems need is not “capability,” but “stopping conditions” —
When designing AI systems,most discussions focus on a single question:
What can AI do?
However, in real systems,there ...
Yield and Boundaries — Why Semiconductor Factories and AI System Design Are Surprisingly Similar
In semiconductor manufacturing,there is one metric that matters more than anything else.
That metric is
Yield.
Yield ...
Five Design Patterns for Successful AI Customer Support — The Key Is Not the Model, but Boundary Design —
Many companies are introducing AI customer support.
However, the outcomes are clearly divided into two groups.
In some...
Can Meta-Learning Learn “Types”? — The Structural Relationship Between Meta-Learning and Ontology Design —
Meta-learning is often described as
“learning how to learn.”
It enables adaptation with very little data.It allows mod...