✅ Answer: B) ₹10,372 croreThe India AI Mission was approved by the Union Cabinet in March 2024 with an outlay of ₹10,372 crore over 5 years. Key components: IndiaAI Compute Facility (10,000+ GPU cluster), IndiaAI Innovation Centre (indigenous AI models), IndiaAI Datasets Platform, IndiaAI Startup Financing, and IndiaAI Future Skills. The mission aims to make India a global AI hub and ensure responsible AI development.

✅ Answer: B) Predicts the 3D structure of proteins from amino acid sequencesAlphaFold, developed by DeepMind (Google), predicts the 3D structure of proteins from their amino acid sequences. This is a major breakthrough in biology — protein structure determines function, and understanding it is crucial for drug discovery. AlphaFold has predicted structures for nearly all known proteins (~200 million). The developers won the Nobel Prize in Chemistry 2024. This could revolutionise drug discovery and disease treatment.

✅ Answer: A) Supreme Court of India for legal researchSUPACE (Supreme Court Portal for Assistance in Courts Efficiency) is an AI tool developed for the Supreme Court of India to assist judges with legal research. It processes case files and provides relevant legal information. It was launched in 2021. India’s judiciary is exploring AI to reduce the massive backlog of cases (over 40 million pending cases). AI can help with case management, legal research, and predicting case outcomes.

✅ Answer: B) AI-generated synthetic media (video/audio/image) that appears real but is fakeDeepfakes are AI-generated synthetic media (videos, audio, images) that appear real but are fabricated. They use deep learning (GANs — Generative Adversarial Networks) to superimpose faces or voices onto other people. Deepfakes pose serious risks: political misinformation, fraud, non-consensual intimate images. India’s IT Rules 2021 (amended 2023) require platforms to remove deepfakes within 24 hours. Detection tools are being developed to identify deepfakes.

✅ Answer: A) Healthcare, Agriculture, Education, Smart Cities, Smart MobilityNITI Aayog’s National Strategy for AI (2018), titled “#AIforAll,” focuses on 5 sectors: Healthcare (disease diagnosis, drug discovery), Agriculture (precision farming, crop monitoring), Education (personalised learning), Smart Cities (traffic, waste, energy management), and Smart Mobility (autonomous vehicles, logistics). The strategy aims to leverage AI for India’s socioeconomic development and position India as a global AI leader.

✅ Answer: A) Deep Learning uses multi-layered neural networks; ML uses simpler algorithmsDeep Learning is a subset of Machine Learning that uses multi-layered artificial neural networks (inspired by the human brain). ML uses simpler algorithms (decision trees, regression, SVM). Deep Learning excels at complex tasks like image recognition, speech recognition, and NLP. Deep Learning requires large amounts of data and computing power. ML can work with smaller datasets. Deep Learning powers ChatGPT, image recognition, and autonomous vehicles.

✅ Answer: B) Narrow AI (Large Language Model)ChatGPT is a Narrow AI — specifically a Large Language Model (LLM) developed by OpenAI. It is trained on vast amounts of text data and can generate human-like text, answer questions, write code, and more. Despite its impressive capabilities, it is still Narrow AI — designed for language tasks. General AI (AGI) would have human-level intelligence across all domains — it doesn’t exist yet. ChatGPT-4 was released in 2023 and sparked global AI discussions.

✅ Answer: A) Systematic errors in AI outputs due to biased training data or algorithmsAI bias refers to systematic errors in AI outputs that result from biased training data or flawed algorithms. Examples: facial recognition systems less accurate for dark-skinned people (trained mostly on light-skinned faces); hiring algorithms discriminating against women (trained on historical male-dominated hiring data); loan approval algorithms discriminating against minorities. AI bias can perpetuate and amplify existing social inequalities. Addressing bias requires diverse training data and algorithmic auditing.

✅ Answer: A) Creates new content (text, images, music, code) based on training dataGenerative AI creates new content (text, images, music, video, code) based on patterns learned from training data. Examples: ChatGPT (text), DALL-E (images), Midjourney (images), GitHub Copilot (code), Suno (music). Generative AI uses models like GANs (Generative Adversarial Networks) and Transformers. It has revolutionised creative industries but also raised concerns about copyright, misinformation, and job displacement. India’s AI Mission includes developing indigenous generative AI models.

✅ Answer: A) Using data from sensors, satellites, and AI to optimise farming decisionsPrecision farming uses data from soil sensors, weather stations, satellite imagery, and AI to optimise farming decisions — when to irrigate, how much fertilizer to apply, when to harvest. It reduces waste, increases yield, and minimises environmental impact. AI apps can identify crop diseases from photos. Drones spray pesticides precisely. India’s government promotes precision farming through schemes like PMKSY and Digital Agriculture Mission. It is crucial for India’s food security with limited land and water resources.