What is the difference between reactive machines and limited-memory AI?
A.
Reactive machines can improve their functionality over time by learning from past data, while limited memory AI operates solely on present data
B.
Reactive machines have conscious understanding of their existence and a sense of self, whereas limited memory AI does not
C.
Reactive machines operate solely on present data, while limited memory AI can temporarily store and learn from past data to improve over time
The Answer Is:
C
This question includes an explanation.
Explanation:
Reactive machines: These are the simplest form of AI systems. They operate only on current inputs and do not store past data (e.g., IBM’s Deep Blue chess computer).
Limited-memory AI: These systems can use past data to make better decisions and predictions — commonly seen in machine learning models like those used in autonomous vehicles.
Therefore, Option C correctly highlights that reactive machines lack memory and operate only on real-time inputs, whereas limited-memory AI can utilize recent past information for learning.
[Reference:, , ISO/IEC 22989:2022, Clause 3.7 – Types of AI systems, , ISO/IEC TR 24028:2020 – Overview of Trustworthiness in AI, includes capability taxonomy, , PECB AI Lead Auditor Study Guide, Chapter 2.2 – AI System Classifications, , ===========, ]
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