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Answer: AI / Autonomous
AI agents combine LLMs with planning, tool use, memory for autonomous task execution. Applications: research assistants, customer service, workflow automation. Critical for next-gen AI systems.
Answer: True
LoRA adds low-rank matrices to weight updates, reducing trainable parameters by 100-1000x vs full fine-tuning. Enables efficient adaptation of LLMs on consumer hardware. Critical for resource-constrained AI.
Answer: RAG
Retrieval-Augmented Generation (RAG) combines LLMs with vector database retrieval, grounding responses in verified sources. Reduces hallucinations and enables knowledge updates without retraining.
Answer: Consortium / W3C
W3C develops web standards: HTML, CSS, XML, accessibility guidelines. Ensures interoperability and innovation on the web. India participates through W3C India office. Critical for web policy questions.
Answer: Both A and B
ISO/IEC 24760 provides identity management framework; W3C DID enables decentralized identifiers. Both support interoperable, privacy-preserving digital identity systems. Critical for identity policy questions.
Answer: True
Data localization (RBI payment data, DPDP Act provisions) ensures law enforcement access, reduces foreign surveillance risks. Balances sovereignty with global data flow needs. Critical for policy questions.
Answer: Both A and B
Digital India encourages FOSS adoption for cost-effectiveness, security, and vendor independence. MeitY's FOSS policy provides guidelines for government use. Critical for sustainable digital governance.
Answer: Artificial Intelligence / #AIforAll
#AIforAll strategy (NITI Aayog) focuses on leveraging AI for inclusive growth across healthcare, agriculture, education. Emphasizes research, skilling, data governance, and ethical principles.
Answer: SMOTE
SMOTE (Synthetic Minority Over-sampling Technique) creates synthetic examples by interpolating between minority class neighbors. Improves classifier performance on imbalanced data vs simple oversampling.
Answer: True
XAI methods (SHAP, LIME, attention visualization) provide interpretable explanations for AI decisions. Critical for regulated sectors (finance, healthcare) and user acceptance.
Answer: Scatter Plot
Scatter plots display individual data points for two variables, revealing correlations, clusters, and outliers. Foundation for regression analysis and exploratory data science.
Answer: F1
F1 Score = 2 * (Precision * Recall) / (Precision + Recall). Harmonic mean balancing false positives and false negatives. Critical for evaluating models on imbalanced datasets.
Answer: All of these
Data splitting strategies: holdout (simple split), cross-validation (multiple folds), bootstrap (resampling). Critical for reliable model evaluation and generalization assessment.
Answer: True
Serverless (Lambda, Cloud Functions) uses pay-per-execution pricing, auto-scaling from zero. Trade-offs: cold starts, execution limits, vendor lock-in. Critical for cost-optimized cloud architectures.
Answer: Event-Driven Architecture
Event-driven architecture uses message brokers (Kafka, RabbitMQ) for asynchronous, decoupled service communication. Enables scalability, resilience, and real-time processing. Critical for modern distributed systems.
Answer: Multi-AZ / High-Availability
Multi-AZ deployment distributes resources across physically separate data centers within a region, protecting against zone failures. Critical for business continuity and SLA compliance.
Answer: CaaS
CaaS (Container as a Service) provides managed Kubernetes (EKS, AKS, GKE) for container deployment, scaling, and management. Abstracts infrastructure while retaining control. Critical for cloud-native development.
Answer: True
Deception deploys fake assets (servers, credentials) to lure attackers, enabling early detection and threat intelligence. Critical for proactive defense against advanced adversaries.
Answer: All of these
Malware analysis combines: static (code inspection), dynamic (runtime behavior), sandboxing (isolated execution). Critical for threat intelligence and incident response.
Answer: MITRE ATT&CK
MITRE ATT&CK matrix catalogs adversary TTPs across enterprise, cloud, mobile. Enables threat-informed defense, detection engineering, and red teaming. Critical for mature security operations.