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Everything about Inference engine

Component of artificial intelligence systems

In the field of artificial intelligence, an inference engine is a software component of an intelligent system that applies logical rules to the knowledge base to deduce new information. The first inference engines were components of expert systems. The typical expert system consisted of a knowledge base and an inference engine. The knowledge base stored facts about the world. The inference engine applied logical rules to the knowledge base and deduced new knowledge. This process would iterate as each new fact in the knowledge base could trigger additional rules in the inference engine. Inference engines work primarily in one of two modes either special rule or facts: forward chaining and backward chaining. Forward chaining starts with the known facts and asserts new facts. Backward chaining starts with goals, and works backward to determine what facts must be asserted so that the goals can be achieved. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Inference engineA 5-minute orientation
  2. Skim a recent paper: READ-Optimized 28nm HKMG Multibit FeFET Synapses for Inference-Engine ApplicationsInfluential work since 2022
  3. Pick up a classic book: The Elements of Statistical LearningThe most-reprinted book on the subject
  4. Read the landmark paper: UltraNest - a robust, general purpose Bayesian inference engineCited 481 times
  5. Go sideways: Expert systemA closely related topic
  6. Go sideways: Reasoning systemA closely related topic

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🗂️ The subject at a glance

  1. Architecture
  2. Implementations

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

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