The chapter "Semantic Information Processing" in the book edited by Marvin Minsky, published by The MIT Press, covers a range of topics related to the processing and understanding of semantic information. The chapter includes an introduction by Minsky, which provides a survey of the field, discusses the organization of the book, and explores the cybernetic background of artificial intelligence. It also delves into formality, generality, learning, knowledge, grammar, syntax, parsing programs, machine translation, and the practical challenges of mechanizing large models. The chapter then features several articles by different authors, each contributing to the understanding of semantic information processing. Bertram Raphael's article introduces SIR, a computer program for semantic information retrieval, detailing its representations, behavior, and formalization. Daniel G. Bobrow's work focuses on natural language input for a computer problem-solving system, discussing semantic generation, analysis, and the transformation of English into a deductive model. M. Ross Quillian's piece explores the role of semantic memory and its memory model, including its application in language comprehension. Thomas G. Evans presents a program for solving geometric-analogy intelligence test questions, detailing the solution process and results. Fischer Black discusses a deductive question-answering system, explaining the deduction process and efficiency. John McCarthy's article focuses on programs with common sense, particularly the Advice Taker and the concepts of situation, actions, and causal laws. Finally, Marvin L. Minsky's concluding chapter addresses the relationship between matter, mind, and models, exploring the dualism of world models and the role of heuristics in quasi-separate models.The chapter "Semantic Information Processing" in the book edited by Marvin Minsky, published by The MIT Press, covers a range of topics related to the processing and understanding of semantic information. The chapter includes an introduction by Minsky, which provides a survey of the field, discusses the organization of the book, and explores the cybernetic background of artificial intelligence. It also delves into formality, generality, learning, knowledge, grammar, syntax, parsing programs, machine translation, and the practical challenges of mechanizing large models. The chapter then features several articles by different authors, each contributing to the understanding of semantic information processing. Bertram Raphael's article introduces SIR, a computer program for semantic information retrieval, detailing its representations, behavior, and formalization. Daniel G. Bobrow's work focuses on natural language input for a computer problem-solving system, discussing semantic generation, analysis, and the transformation of English into a deductive model. M. Ross Quillian's piece explores the role of semantic memory and its memory model, including its application in language comprehension. Thomas G. Evans presents a program for solving geometric-analogy intelligence test questions, detailing the solution process and results. Fischer Black discusses a deductive question-answering system, explaining the deduction process and efficiency. John McCarthy's article focuses on programs with common sense, particularly the Advice Taker and the concepts of situation, actions, and causal laws. Finally, Marvin L. Minsky's concluding chapter addresses the relationship between matter, mind, and models, exploring the dualism of world models and the role of heuristics in quasi-separate models.