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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: 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: 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.
Answer: Pruning
Model pruning removes low-importance weights/neurons, reducing size and inference cost. Combined with quantization for efficient edge deployment. Critical for scalable AI systems.
Answer: Artificial Intelligence / GPAI
GPAI (founded 2020) brings together experts for responsible AI: research, policy, best practices. India is founding member. Critical for understanding global AI governance landscape.
Answer: India
India Stack layers: identity (Aadhaar), payments (UPI), data sharing (AA), documents (DigiLocker). Enables innovation on public digital infrastructure. Critical for digital governance questions.
Answer: Precision
Precision = TP / (TP + FP). Critical for imbalanced classification tasks where false positives are costly (fraud detection, medical diagnosis). Complements recall for comprehensive evaluation.
Answer: Hybrid
Hybrid cloud combines on-premises infrastructure with public cloud services. Enables data sovereignty compliance while leveraging cloud scalability. Critical for regulated industries.
Answer: Hunting
Threat hunting uses hypotheses, analytics, and analyst expertise to find hidden adversaries. Complements automated detection. Critical for advanced persistent threat (APT) defense.
Answer: Multi-Task
Multi-task learning shares representations across related tasks, improving sample efficiency and generalization. Critical for building versatile AI systems with limited labeled data per task.
Answer: Artifact / Model Registry
Artifact management (MLflow, DVC) tracks datasets, model versions, hyperparameters, and code commits. Enables reproducibility, auditability, and rollback in ML workflows. Critical for enterprise MLOps.
Answer: Thought
Chain-of-Thought prompting encourages LLMs to generate reasoning steps before final answer, improving performance on complex reasoning tasks. Critical for enhancing LLM reliability in high-stakes applications.
Answer: QR
QR (Quick Response) Code is a two-dimensional barcode that stores payment information. UPI apps can scan merchant QR codes to initiate payments instantly without entering account details. NPCI's Bharat QR is interoperable across banks and payment apps, promoting cashless transactions at small merchants.
Answer: Hashing
Hashing transforms input data of any size into a fixed-length hash value using algorithms like SHA-256 or MD5. It is one-way (irreversible), used for password storage, data integrity verification, and digital signatures. Unlike encryption, hashed data cannot be decrypted to original form.
Answer: 4.0
Industry 4.0 (Fourth Industrial Revolution) integrates IoT, AI, cloud computing, cyber-physical systems, and real-time data analytics into manufacturing. Enables smart factories with predictive maintenance, mass customization, and autonomous decision-making. India's SAMARTH Udyog initiative promotes Industry 4.0 adoption in MSMEs.
Answer: Intranet
Intranet is a private network using TCP/IP protocols, accessible only to organization members. It hosts internal websites, documents, and applications. Extranet extends intranet to authorized external users (partners, vendors). Internet is the public global network. Firewalls protect intranets from external threats.
Answer: Make
Make in India, launched in 2014, aims to transform India into a global manufacturing hub, with focus on 27 sectors including electronics, IT, and telecommunications. It encourages foreign investment, skill development, and innovation to boost domestic production and reduce imports.
Answer: Booting
Booting is the startup sequence when a computer is powered on. BIOS/UEFI performs POST (Power-On Self-Test), locates boot device, loads bootloader, which then loads the OS kernel into RAM. Cold boot = power-on start; warm boot = restart without power cycle.
Answer: Natural Language
Natural Language Processing (NLP) combines linguistics, computer science, and AI to enable machines to understand, interpret, and generate human language. Applications include chatbots, translation services, sentiment analysis, voice assistants, and automated content summarization.
Answer: do-while
do-while loop checks the condition AFTER executing the loop body, guaranteeing at least one execution. In contrast, while and for loops check condition BEFORE execution, potentially skipping the body entirely if condition is initially false. Syntax varies by language but logic remains consistent.