D685 Practical Applications of Prompt - Set 2 - Part 1

Correct Answer: Natural language processing

Natural language processing specifically analyzes sentiment in text, enabling understanding of customer emotions from written reviews for service improvements.
Option a is incorrect because optical character recognition only converts images to text without analyzing emotional content or sentiment patterns.
Option c is incorrect because computer vision analyzes visual data rather than understanding emotional sentiment in written customer reviews.
Option d is incorrect because speech synthesis generates spoken output from text rather than analyzing sentiment in reviews.

Correct Answer: Narrow AI specialization

Narrow AI is task-specific and performs poorly outside its training domain, explaining the model's limitations on untrained tasks.
Option b is incorrect because general AI would theoretically handle various tasks, but currently exists only as a hypothetical concept.
Option c is incorrect because deep learning architecture is a technical approach rather than a limitation causing poor performance.
Option d is incorrect because reinforcement learning is a training method rather than a characteristic explaining task-specific limitations.

Correct Answer: Algorithm transparency necessity

Algorithm transparency ensures AI decisions can be explained and understood by regulators, meeting compliance and accountability requirements effectively.
Option a is incorrect because processing speed doesn't address the regulatory need for explainable decision-making in claim processing.
Option c is incorrect because storage capacity expansion is unrelated to the requirement for explainable AI decisions.
Option d is incorrect because automation efficiency doesn't ensure decisions can be explained to regulatory authorities.

Correct Answer: Persona role specification

Persona specification defines the professional role and voice, ensuring consistent technical terminology and appropriate language throughout documentation.
Option a is incorrect because context provides background facts rather than maintaining consistent professional terminology and language style.
Option b is incorrect because constraints set limitations rather than specifically ensuring consistent technical language and terminology.
Option d is incorrect because output format determines structure rather than maintaining professional language and terminology consistency.

Correct Answer: Continuous monitoring implementation

Continuous monitoring of AI systems helps detect and prevent hallucinations that generate false but credible-appearing information in articles.
Option a is incorrect because increasing generation speed could actually increase the risk of generating false information rapidly.
Option c is incorrect because reducing storage requirements doesn't address the problem of AI generating false information.
Option d is incorrect because minimizing costs might compromise quality controls needed to prevent false information generation.

Correct Answer: Output format specification

Output format specification determines response structure, and better definition ensures consistent formatting across similar report requests.
Option a is incorrect because context provides background information rather than controlling the consistency of report formatting.
Option b is incorrect because instruction clarity affects task understanding rather than specifically ensuring format consistency.
Option d is incorrect because persona defines tone and perspective rather than structural formatting of reports.

Correct Answer: Cognitive verifier technique

Cognitive verifier technique allows models to ask clarifying questions when facing ambiguity, enabling interactive research parameter clarification.
Option a is incorrect because few-shot prompting provides examples rather than enabling the AI to ask clarifying questions.
Option c is incorrect because self-consistency checking ensures output reliability rather than enabling interactive question asking.
Option d is incorrect because generated knowledge creates context rather than allowing the model to request clarification.

Correct Answer: Pattern recognition capability

Pattern recognition in AI identifies unusual patterns and anomalies in medical images that could indicate potential health issues.
Option a is incorrect because text extraction processes written content rather than analyzing patterns in medical images.
Option c is incorrect because speech generation creates audio output rather than identifying patterns in visual medical data.
Option d is incorrect because document summarization condenses text rather than analyzing patterns in medical imaging.

Correct Answer: Sampling bias occurrence

Sampling bias from imbalanced historical data causes the AI to favor overrepresented geographic areas in routing decisions.
Option a is incorrect because measurement bias involves data collection errors rather than geographic imbalances in historical data.
Option b is incorrect because algorithmic bias stems from design flaws rather than imbalanced geographic representation in data.
Option d is incorrect because confirmation bias reinforces beliefs rather than causing geographic favoritism from data imbalances.

Correct Answer: Reinforcement learning system

Reinforcement learning uses feedback as rewards and penalties to improve performance through continuous interaction and adjustment.
Option a is incorrect because supervised learning requires pre-labeled data rather than learning from ongoing customer interaction feedback.
Option b is incorrect because unsupervised learning finds patterns without feedback mechanisms for improvement through customer interactions.
Option d is incorrect because static programming doesn't adapt or improve based on customer feedback and interactions.

Correct Answer: Constraint parameter setting

Constraint parameters define limitations and boundaries, ensuring the AI clearly communicates uncertainties and limitations in investment suggestions.
Option a is incorrect because output format determines structure rather than ensuring communication of limitations and uncertainties.
Option b is incorrect because context provides background information rather than setting requirements for stating limitations.
Option d is incorrect because instructions direct tasks rather than specifically requiring disclosure of uncertainties and limitations.

Correct Answer: Least-to-most prompting method

Least-to-most prompting progressively increases complexity from simple to complex examples, building understanding and improving solutions gradually.
Option a is incorrect because zero-shot prompting works without examples rather than building progressively from simple to complex.
Option c is incorrect because self-consistency validation checks output reliability rather than progressively building solution complexity.
Option d is incorrect because tree-of-thought explores multiple paths rather than building progressively from simple to complex.

Correct Answer: Optical character recognition

OCR technology specifically converts handwritten and printed text from physical documents into digital, searchable format efficiently.
Option a is incorrect because voice recognition processes audio input rather than converting handwritten text from paper documents.
Option b is incorrect because speech synthesis generates audio from text rather than digitizing handwritten patient records.
Option d is incorrect because natural language generation creates new text rather than converting existing handwritten records.

Correct Answer: Confirmation bias presence

Confirmation bias causes AI to reinforce existing beliefs and preconceptions rather than discovering new, potentially contradictory insights.
Option a is incorrect because selection bias involves non-representative data rather than reinforcing preconceived notions about preferences.
Option c is incorrect because measurement bias involves data collection errors rather than reinforcing existing marketing beliefs.
Option d is incorrect because algorithmic bias stems from design flaws rather than specifically reinforcing preconceived notions.

Correct Answer: Personalization adaptation feature

Personalization allows AI to adapt to individual learning speeds, providing customized tutoring experiences for each student's needs.
Option a is incorrect because real-time processing relates to speed rather than adapting to individual student learning patterns.
Option b is incorrect because pattern recognition identifies trends rather than specifically adapting to individual learning speeds.
Option c is incorrect because prediction capability forecasts outcomes rather than personalizing learning experiences for individuals.

Correct Answer: Zero-shot prompting method

Zero-shot prompting generates outputs without examples, relying on the model's training to create original stories independently.
Option a is incorrect because few-shot prompting requires providing examples, which contradicts the requirement for no examples.
Option c is incorrect because chain-of-thought focuses on reasoning steps rather than generating creative content without examples.
Option d is incorrect because self-consistency ensures reliable outputs rather than specifically enabling example-free story generation.

Correct Answer: Anomaly detection function

Anomaly detection identifies deviations from normal patterns, making it ideal for detecting potential cybersecurity threats in networks.
Option a is incorrect because duplicate removal cleans redundant data rather than identifying security threats through behavioral deviations.
Option c is incorrect because missing value inference fills data gaps rather than detecting abnormal network behavior patterns.
Option d is incorrect because error correction fixes mistakes rather than identifying potential security threats through anomalies.

Correct Answer: Historical bias perpetuation

Training on historical data perpetuates past biases, potentially discriminating against groups underrepresented in previous successful employees.
Option a is incorrect because innovation limitation isn't a bias type but rather a potential consequence of limited training.
Option c is incorrect because processing speed isn't affected by the source of training data used.
Option d is incorrect because storage capacity relates to technical infrastructure rather than bias from historical data.

Correct Answer: Context and constraints

Context provides jurisdictional information while constraints ensure precise legal language, together enabling appropriate contract generation.
Option b is incorrect because format and speed don't ensure legal precision or jurisdictional adaptation in contracts.
Option c is incorrect because storage and retrieval are system functions rather than prompt components for legal precision.
Option d is incorrect because cost and efficiency are operational metrics rather than components ensuring legal accuracy.

Correct Answer: Generated knowledge prompting

Generated knowledge prompting allows models to create necessary context about jargon and terms before processing specialized documents.
Option b is incorrect because zero-shot execution works without preparation, which wouldn't help with understanding specialized terminology.
Option c is incorrect because tree-of-thought explores reasoning paths rather than generating knowledge about technical terms.
Option d is incorrect because self-consistency validates outputs rather than helping understand industry-specific jargon beforehand.