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Generate QuizTechnology – Medium Level – GK Questions
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Multi-region deployment improves application availability by protecting against regional outages.
- True
- False
Answer: True
Multi-region architecture distributes workload across geographic regions, enabling failover during regional disasters. Critical for business continuity and global user experience.
Which service enables serverless data processing triggered by events?
- Lambda
- Cloud Functions
- Both A and B
- Neither
Answer: Both A and B
Serverless compute (AWS Lambda, GCP Cloud Functions) executes code in response to events: API calls, file uploads, messages. Auto-scaling, pay-per-execution pricing. Critical for event-driven architectures.
The framework that standardizes security control implementation for cloud environments is called ________.
- Fairness
- Aadhaar
- CSA CCM / Cloud Controls Matrix
- Frequency
Answer: CSA CCM / Cloud Controls Matrix
Cloud Security Alliance Cloud Controls Matrix provides comprehensive security controls for cloud services, mapped to standards like ISO 27001, NIST. Critical for cloud security governance.
Which technology provides endpoint detection and response capabilities for advanced threats?
- EDR
- XDR
- Both A and B
- Neither
Answer: Both A and B
EDR focuses on endpoint telemetry and response; XDR extends to network, cloud, email for cross-domain threat detection. Critical for comprehensive threat protection.
GitOps uses Git repositories as single source of truth for infrastructure and ML deployments.
- True
- False
Answer: True
GitOps (ArgoCD, Flux) declaratively defines desired state in Git; operators sync cluster state. Benefits: audit trail, rollback via git revert, peer review via PRs. Critical for cloud-native MLOps.
Which practice ensures ML models are monitored for performance degradation in production?
- Drift Detection
- Metric Dashboards
- Alerting
- All of these
Answer: All of these
Production monitoring: drift detection for data/concept changes, dashboards for real-time metrics, alerting for anomalies. Critical for maintaining ML system reliability and business value.
Self-supervised learning enables models to learn from unlabeled data by predicting masked tokens.
- True
- False
Answer: True
Self-supervised learning (BERT, GPT pre-training) creates supervisory signals from data structure: mask prediction, next sentence prediction. Enables learning from vast unlabeled corpora.
Which technique enables LLMs to maintain context across long conversations?
- Context Window
- Memory Mechanisms
- Both A and B
- Neither
Answer: Both A and B
Long-context handling: larger context windows (128K+ tokens), memory mechanisms (summarization, retrieval) maintain conversation history. Critical for chatbots and assistants.
The National Education Policy 2020 mandates integration of coding and AI literacy from middle school.
- True
- False
Answer: True
NEP 2020 emphasizes computational thinking, coding, AI exposure from Class 6 onwards, with experiential learning and teacher training. Implemented via DIKSHA, CBSE updates, ATLs.
Which initiative provides a unified platform for startup mentoring, funding, and compliance?
- Startup India Hub
- DPIIT Recognition
- Both A and B
- Neither
Answer: Both A and B
Startup India ecosystem integrates: Hub for resources/networking, DPIIT recognition for benefits, NITI Aayog for policy. Supports innovation, job creation, global competitiveness.
The Indian policy for promoting electric vehicle adoption through subsidies is called ________ India.
- FAME
- TDMA
- e-NAM
- ETL
Answer: FAME
FAME (Faster Adoption and Manufacturing of Electric Vehicles) India provides demand incentives for EVs and charging infrastructure. Phase-II focuses on public transport and shared mobility.
Cross-validation provides more reliable model evaluation than single train-test split.
- True
- False
Answer: True
Cross-validation (k-fold) trains/evaluates on multiple data splits, reducing variance in performance estimates. Critical for small datasets and reliable model selection.
Which visualization is best for comparing proportions of categories?
- Bar Chart
- Pie Chart
- Stacked Bar
- All of these
Answer: All of these
Proportion visualization: bar charts for clear comparison, pie charts for part-to-whole (limited categories), stacked bars for multiple groups. Choice depends on data and audience.
The technique that reduces model complexity to prevent overfitting is called ________.
- Corporation for Assigned Names and Numbers / ICANN
- Common
- Pruning
- Regularization
Answer: Regularization
Regularization (L1/Lasso, L2/Ridge, Dropout) adds penalty terms to loss function or randomly drops units during training. Prevents overfitting by discouraging complex models. Critical for generalization.
Infrastructure as Code scanning tools detect security misconfigurations before deployment.
- True
- False
Answer: True
IaC scanners (Checkov, tfsec) analyze Terraform/CloudFormation for misconfigurations: public storage, weak IAM, unencrypted resources. Critical for shift-left security in DevOps.
Which storage class is most cost-effective for infrequently accessed archival data?
- Standard
- Infrequent Access
- Archive
- Glacier Deep Archive
Answer: Glacier Deep Archive
Glacier Deep Archive offers lowest cost for long-term retention with 12+ hour retrieval times. Ideal for regulatory archives, backups. Trade-off: low storage cost vs high retrieval latency.
The practice of simulating cyberattacks to test organizational defenses is called ________ Testing.
- Integration / Warehousing
- Vision
- Red Team / Penetration
- Account Aggregator
Answer: Red Team / Penetration
Red teaming conducts adversarial simulations (cyber, physical, social) to identify gaps in detection, response, and resilience. Distinct from vulnerability scanning. Critical for mature security programs.
Which technique identifies compromised accounts by analyzing login patterns and behaviors?
- UEBA
- SIEM
- EDR
- All of these
Answer: UEBA
UEBA (User and Entity Behavior Analytics) uses ML to establish behavioral baselines and detect anomalies indicating compromised accounts or insider threats. Critical for identity security.
Model registries track versions, metadata, and lineage of ML models for governance.
- True
- False
Answer: True
Model registries (MLflow, SageMaker) manage model versions, parameters, metrics, and deployment history. Enables auditability, reproducibility, and rollback. Critical for enterprise MLOps.
Which practice ensures ML models are tested for security vulnerabilities before deployment?
- Adversarial Testing
- Penetration Testing
- Both A and B
- Neither
Answer: Both A and B
ML security testing: adversarial examples test robustness, penetration testing finds implementation flaws. Critical for secure AI deployment in sensitive domains.