IBM A1000-074: Assessment: Foundations of Watson AI v2 Advanced Practice Exam: Hard Questions 2025

An enterprise is deploying Watson Discovery to analyze financial documents containing complex tables, charts, and narrative text. They need to extract specific clause information from contracts while maintaining relationships between parties, dates, and obligations. The documents have inconsistent formatting across vendors. Which combination of Watson Discovery features would provide the most accurate extraction while minimizing custom development effort?

A Watson Assistant chatbot deployed in production experiences degraded performance when users ask questions outside the trained intents. The system often triggers the 'anything_else' node inappropriately, even for questions that should match existing intents. Analysis shows confidence scores clustering between 0.15 and 0.35 for legitimate queries. What is the most effective troubleshooting approach to resolve this issue?

A healthcare organization is designing an AI system to assist radiologists in detecting anomalies in medical images. The system must handle class imbalance (rare diseases), provide explainability for regulatory compliance, and maintain high recall while managing false positives. Which architectural approach best addresses these requirements?

During model training for a natural language classification task, you observe that training accuracy reaches 98% while validation accuracy plateaus at 72%. The model uses word embeddings and a neural network architecture. Cross-validation shows consistent performance across folds, but production performance is even lower at 65%. What is the most likely root cause and appropriate solution?

An organization is implementing Watson Natural Language Understanding to analyze customer feedback across multiple languages. They need to extract custom entities (product names, internal codes) and analyze sentiment for each entity mention. The feedback contains code-switched text (multiple languages in one document) and domain-specific terminology. What implementation strategy would provide the most accurate results?

A Watson Discovery implementation for legal document search is experiencing poor relevance despite extensive training. Users report that exact phrase matches are being ranked lower than documents with scattered keyword matches. The collection has 50,000 documents and uses default query settings. What configuration changes would most effectively improve phrase matching relevance?

An AI system uses multiple models in a pipeline: speech-to-text, natural language understanding, and dialog management. The end-to-end system latency is 4.5 seconds, exceeding the acceptable 2-second threshold. Speech-to-text takes 1.8s, NLU takes 1.5s, and dialog takes 1.2s. The system handles 1000 concurrent users during peak times. What optimization strategy would provide the greatest latency reduction while maintaining accuracy?

A company is evaluating whether to use supervised learning, unsupervised learning, or reinforcement learning for a customer service optimization problem. They want to automatically categorize incoming tickets, discover unknown issue patterns, and improve routing decisions based on resolution outcomes. They have 50,000 labeled historical tickets and continuous new unlabeled tickets. Which approach would best address all three objectives?

A Watson Assistant skill is deployed across multiple channels (web, mobile app, voice). Users report that context is not maintained when they switch channels mid-conversation. The skill uses slots, digressions, and contextual entities. Session data shows conversations appearing as new sessions on channel switch. What architectural modification would resolve this issue while maintaining security and user privacy?

An enterprise is designing a Watson-based solution for analyzing sensitive customer data that must comply with GDPR, HIPAA, and industry-specific regulations. The solution needs to use Watson Discovery for document analysis and Watson Assistant for conversational interfaces. Which architectural considerations are essential for maintaining compliance while delivering functionality?