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NEW QUESTION 24
Narrow or weak Al can be useful to robots.
Which of the following is an example of narrow Al?
- A. NLP – Natural LanguageProcessing.
- B. Artificial General Al.
- C. Conscious simul-ation.
- D. Conscious integration.
NLP – Natural Language Processing is an example of narrow AI. It is a type of AI system that is able to understand, interpret, and generate natural language. NLP has become increasingly popular over the past few years, as it has been used to create applications such as chatbots, virtual assistants, and search engines. NLP systems are able to learn language and the context in which it is used, and they are able to understand the nuances of language and its different meanings. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/
NEW QUESTION 25
What does TRL stand for?
- A. Transform Reinforced Learning
- B. Technical Robotic Level.
- C. Transport Ready Level.
- D. Technology Readiness Level.
Technology Readiness Level (TRL) Technology Readiness Levels (TRL) are a method of estimating the technology maturity of Critical Technology Elements (CTE) of a program during the acquisition process.
NEW QUESTION 26
How could machine learningmake a robot autonomous?
- A. Use OCR, optical character recognition, to read documents
- B. Use NLP (Natural Language Processing) to listen
- C. Use actuators to modify its environment
- D. Learn from sensor data and plan to carry out a task.
Machine learning can be used to make robots autonomous by allowing them to learn from sensor data and plan how to carry out a task. This involves using algorithms to analyze data from sensors and use this data to make decisions and take actions. By using machine learning, robots can learn from their environment and become more autonomous. References:
 BCS Foundation Certificate In Artificial Intelligence Study Guide, “Robotics”, p.98.  APMG-International.com, “Foundations of Artificial Intelligence”  EXIN.com, “Foundations of Artificial Intelligence”
NEW QUESTION 27
With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what type of machine learning?
- A. Big Data learning.
- B. Batch learning.
- C. Online learning.
- D. Patchwork learning.
NEW QUESTION 28