Artificial Intelligence and the IndiaAI Mission: Exam Notes

The correct answer is B, John McCarthy. He coined the phrase artificial intelligence in the proposal for a summer research workshop held at Dartmouth College in 1956, and that conference is treated as the moment the subject was founded; McCarthy also created the LISP programming language and is commonly called the father of artificial intelligence. Option A is wrong because Alan Turing, though he asked whether machines can think and gave the Turing Test in 1950, never used the phrase itself; the field was named six years after his paper. Option C is wrong because Marvin Minsky, a major figure who attended the same Dartmouth meeting and later founded the MIT AI laboratory, did not coin the term. Option D is wrong because Joseph Weizenbaum is remembered for ELIZA, the first conversational program, written in the mid-1960s.

The correct answer is C, 1950. Alan Turing set out the imitation game in his paper Computing Machinery and Intelligence, published in 1950 in the journal Mind; a machine passes if a human judge, exchanging only typed messages, cannot tell it from a human being. Option A is wrong because 1936 is the year of Turing’s earlier and quite different paper on computable numbers, which described the theoretical Turing machine, the foundation of computability rather than a test for intelligence. Option B is wrong because 1943 is associated with the McCulloch and Pitts model of an artificial neuron, the first mathematical model of a neural network. Option D is wrong because 1956 is the year of the Dartmouth Conference, where the term artificial intelligence was coined. Examiners pair 1950 with the test and 1956 with the name, so keep the two dates apart.

The correct answer is C, supervised learning. Here every training example carries the right answer, its label, and the model learns the mapping from input to label, which is how spam filters, handwriting readers and credit-scoring models are built. Option A is wrong because unsupervised learning is given data without labels and must find structure by itself, typically clustering or dimensionality reduction; customer segmentation is the standard example. Option B is wrong because reinforcement learning has neither labels nor fixed answers: an agent acts in an environment and learns from rewards and penalties, the method behind game-playing programs and robot control. Option D is wrong because transfer learning is not a third style of its own but a technique of reusing a model trained on one task as the starting point for another. Remember the pairing: labels mean supervised, no labels mean unsupervised, rewards mean reinforcement.

The correct answer is A, about Rs 10,372 crore. The Union Cabinet approved the IndiaAI Mission on 7 March 2024 with an outlay of 10,371.92 crore rupees, to be spent across its seven components, and the mission is run by the IndiaAI Independent Business Division under the Digital India Corporation in the Ministry of Electronics and Information Technology. Option B is wrong because 76,000 crore rupees is the outlay of the Semicon India programme for semiconductor and display manufacturing, approved in December 2021, a figure examiners deliberately place beside this one. Option C is wrong because 1,500 crore rupees is far too small for a mission that has to buy or hire tens of thousands of GPUs. Option D is wrong because 25,000 crore rupees matches no approved outlay for this mission. Learn the pair: IndiaAI about 10,372 crore, Semicon India 76,000 crore.

The correct answer is C, seven. The approved mission has seven components: IndiaAI Compute Capacity, the IndiaAI Innovation Centre, the IndiaAI Datasets Platform, the IndiaAI Application Development Initiative, IndiaAI FutureSkills, IndiaAI Startup Financing, and Safe and Trusted AI. Option A is wrong, and five is a tempting answer because NITI Aayog’s National Strategy for Artificial Intelligence of 2018 named five focus sectors, namely healthcare, agriculture, education, smart cities and infrastructure, and smart mobility; that five belongs to the strategy, not to the mission. Option B is wrong because six leaves one pillar out, usually Safe and Trusted AI, which is the one most often asked about separately. Option D is wrong because nine matches no official list. The safe way to remember it is compute, models, data, applications, skills, money and safety, which is exactly seven.

The correct answer is B, the IndiaAI Independent Business Division under the Digital India Corporation, which works under the Ministry of Electronics and Information Technology. The Cabinet decision of 7 March 2024 named this division as the implementing agency for all seven components of the mission. Option A is wrong, and it is the trap in this question: NITI Aayog is the body that wrote the National Strategy for Artificial Intelligence in 2018, so it shaped policy, but it does not run the mission. Option C is wrong because the Defence Research and Development Organisation develops defence systems, including its own AI work, but has no role in administering IndiaAI. Option D is wrong because the Indian Space Research Organisation is the national space agency and is unconnected with this mission. Hold the division of labour: NITI Aayog wrote the strategy, MeitY runs the mission.

The correct answer is C, AlphaGo, built by DeepMind, which beat the South Korean Go champion Lee Sedol in a five-game match in 2016; the victory mattered because Go has far more possible positions than chess, so brute-force search alone cannot win and the program relied on deep neural networks with reinforcement learning. Option A is wrong because Deep Blue was IBM’s chess computer, which defeated the world chess champion Garry Kasparov in 1997, nineteen years earlier and at a different game. Option B is wrong because Watson, also from IBM, is the question-answering system that won the American television quiz show Jeopardy! in 2011. Option D is wrong because ELIZA was a simple conversational program of the mid-1960s and played no games at all. Keep the three pairs: Deep Blue and chess, Watson and a quiz, AlphaGo and Go.

The correct answer is B, NITI Aayog, which published the National Strategy for Artificial Intelligence in June 2018 under the slogan AI for All, and identified five priority sectors: healthcare, agriculture, education, smart cities and infrastructure, and smart mobility and transportation. Option A is wrong, though it is the closest distractor, because the Ministry of Electronics and Information Technology runs the IndiaAI Mission approved in 2024 but did not write the 2018 strategy paper. Option C is wrong because the Reserve Bank of India is the central bank and its work on technology concerns payments, digital lending and the digital rupee, not a national AI strategy. Option D is wrong because the University Grants Commission regulates higher education and frames curricula; it does not issue national technology strategies. Pair the year with the body: 2018 with NITI Aayog, 2024 with MeitY.

The correct answer is B, generative pre-trained transformer. Each word carries meaning: generative, because the model produces new text rather than only sorting what it is shown; pre-trained, because it first learns general language from a very large body of text before being adapted to particular tasks; and transformer, the neural network architecture, built on an attention mechanism, that made such models practical. Option A is wrong because general processing technology is not a term used for these models and describes nothing specific. Option C is wrong because graphical pattern trainer confuses the model with the graphics processing unit, the GPU, which is the hardware used to train it, not the model itself. Option D is wrong because global predictive tool is an invented expansion. Expect the full forms of AI, ML, NLP, GPU and GPT to be asked directly in objective papers.

The correct answer is B, artificial narrow intelligence, also called weak AI. It is trained for a single defined task and cannot transfer that skill to another; every system working today, from spam filters and voice assistants to chess engines and face recognition, is narrow AI. Option A is wrong because artificial general intelligence would equal a human being across any intellectual task, moving freely from one problem to another, and no such system exists. Option C is wrong because artificial super intelligence, which would surpass human ability in every field including creativity and social skill, is purely theoretical and is the stage debated in writing on AI risk. Option D is wrong because theory of mind belongs to the other classification, the one by functionality, which runs reactive machines, limited memory, theory of mind and self-aware machines; it describes a machine that would read emotions and intentions.