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Answer :
Final answer:
One of the factors that differentiates theoretical Artificial General Intelligence (AGI) from Narrow AI is the level of adaptability and flexibility. AGI possesses the capability to transfer knowledge and skills from one domain to another, allowing it to learn and perform tasks across a wide range of domains. In contrast, Narrow AI systems are designed for specific tasks and lack the ability to generalize beyond those tasks.
Explanation:
Artificial General Intelligence (AGI) and Narrow AI are two different concepts in the field of artificial intelligence. AGI refers to the hypothetical intelligence of a machine that can understand or learn any intellectual task that a human being can do, while Narrow AI refers to AI systems that are designed for specific tasks or problems.
One of the factors that differentiates AGI from Narrow AI is the level of adaptability and flexibility. AGI is expected to possess the capability to transfer knowledge and skills from one domain to another. It can generalize its knowledge and apply it to new and unfamiliar situations. This adaptability and flexibility allow AGI to learn and perform tasks across a wide range of domains.
In contrast, Narrow AI systems are designed for specific tasks and lack the ability to generalize beyond those tasks. They are trained and optimized for a particular problem or domain. While Narrow AI systems can excel in their specific tasks, they lack the adaptability and flexibility of AGI.
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Final answer:
One of the factors that differentiates theoretical Artificial General Intelligence (AGI) from Narrow AI is the level of adaptability and flexibility. AGI is expected to possess the capability to transfer knowledge and skills from one domain to another, while Narrow AI systems are typically designed for specific tasks and lack the ability to generalize their knowledge.
Explanation:
Artificial General Intelligence (AGI) and Narrow AI are two different approaches to artificial intelligence. AGI aims to replicate human-level intelligence across a wide range of domains, while Narrow AI focuses on specific tasks or problems.
One of the factors that differentiates AGI from Narrow AI is the level of adaptability and flexibility. AGI is expected to possess the capability to transfer knowledge and skills from one domain to another, allowing it to generalize its intelligence. This means that an AGI system can apply its knowledge and skills to various domains, similar to how humans can transfer their expertise from one area to another.
In contrast, Narrow AI systems are designed for specific tasks and lack the ability to generalize their knowledge. They are optimized for performing well in a particular domain or problem but may struggle when faced with tasks outside their specific area of expertise.
Therefore, the ability to adapt and generalize across domains is a key factor that differentiates AGI from Narrow AI.
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