For the rule-based approach, which of the following is true?

Question

BlackTom AI · Accepted Answer

To unpack the question, we first consider what a rule-based approach entails in computer systems. 
Option 1: 'All answers are correct.' This is unlikely because rule-based systems typically do not require enormous datasets, and their capabilities in tasks like complex image recognition are limited without additional techniques. Therefore, claiming all options are correct overstates the scope of this approach.
Option 2: 'The approach instructs computers to think by providing many logical rules in its programs.' This accurately reflects the essence of rule-based systems: a programmer encodes explicit rules that guide decisions and inferences, rather than relying on learned patterns from data alone. This statement fits the core concept well.
Option 3: 'It requires a lot of data to be accurate.' While data-driven or statistical methods benefit from large datasets, rule-based methods emphasize codified knowledge and rules rather than big data, so this claim is generally not true for standard rule-based approaches.
Option 4: 'It can identify a panda in a picture.' Pure rule-based systems can, in principle, perform pattern recognition, but identifying objects in images typically requires feature extraction and often learning-based methods. Without additional components, the statement is overstated and not universally accurate for pure rule-based paradigms.
Overall, the second option correctly captures the defining characteristic of the rule-based approach, while the other options misstate its data requirements or capabilities.

For the rule-based approach, which of the following is true?

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