Question

Whose name has been replaced with `[\!1]' in the passage above?

• A. Alan Turing
• B. Peter Hilton
• C. Albert Einstein
• D. Kurt Gödel
• A. Deep Mind
• B. Deep Blue
• C. Watson
• D. Blue Gene
• A. Donna Strickland
• B. Max Tegmark
• C. Peter Higgs
• D. Roger Penrose
• A. Neural network
• B. Cognitive computing
• C. Natural language processing
• D. Data mining
• A. Landing Macro Data Applications
• B. Language Model for Dialogue Applications
• C. Large Model Data Applications
• D. Last Mile Dialogue Assessment
• A. FTP
• B. OPT
• C. HTTP
• D. SMTP
• A. SURAM
• B. GPT-3
• C. SUPACE
• D. E-Courts

Answer 1

The Correct Option is A

The passage refers to a 1950 paper published in the journal \emph{Mind}, in which Alan Turing proposed the Turing Test to evaluate whether a machine can exhibit intelligent, human-like behaviour. This test is often called the “imitation game,” matching the description in the passage.

Answer 2

Elimination Approach:
Albert Einstein and Kurt Gödel were not concerned with testing machine intelligence; their major contributions lay in physics and mathematical logic respectively. Peter Hilton was a mathematician known for topology and wartime code-breaking work but is not credited with the imitation game concept. Alan Turing, however, published a 1950 paper in the journal Mind proposing exactly this kind of test, matching the description in the passage, which confirms him as the answer.

Answer 3

The question asks whose name was replaced with "[1]" in the passage, which describes a 1950 paper in the journal Mind proposing a test based on an imitation game. Checking each name against this description answers it.

1. Alan Turing: In 1950, Turing published a paper in the journal Mind proposing exactly this kind of test, later known as the Turing Test or imitation game, to judge whether a machine can show intelligent, human-like behaviour.
2. Peter Hilton: He was a mathematician known for his work in topology and for wartime code-breaking, but he is not credited with proposing the imitation game.
3. Albert Einstein: His major work was in physics, particularly relativity, and he had no involvement in proposing tests for machine intelligence.
4. Kurt Godel: He is known for his incompleteness theorems in mathematical logic, an important but entirely different area from testing machine behaviour.

Only Turing's 1950 paper matches the passage's description exactly.

So the correct answer is Alan Turing.

Answer 4

In 1997, IBM's supercomputer Deep Blue defeated Garry Kasparov in a historic chess match, marking a major milestone in the development of artificial intelligence and computer chess engines.

Answer 5

Elimination Approach:
Deep Mind is a company, later acquired by Google, known for AlphaGo, not a 1997 chess machine. Watson is IBM's question-answering system, famous for winning on Jeopardy!, not for playing chess. Blue Gene refers to a later IBM supercomputer series used mainly for scientific computing. It is Deep Blue, IBM's dedicated chess computer, that defeated Garry Kasparov in 1997.

Answer 6

The question asks which supercomputer defeated Garry Kasparov in 1997. Checking each name against IBM's actual history of computing projects answers it.

1. Deep Mind: This is a company, later acquired by Google, known for AlphaGo and other AI research, not a 1997 chess machine.
2. Deep Blue: IBM built this machine specifically to play chess, and it defeated the reigning world champion Garry Kasparov in a six-game match in 1997, a widely reported milestone for computer chess.
3. Watson: This is IBM's question-answering system, best known for winning on the quiz show Jeopardy! in 2011, not for playing chess.
4. Blue Gene: This refers to a later IBM supercomputer series used mainly for scientific and research computing, not chess.

Only Deep Blue is the machine actually built for, and used in, that 1997 chess match.

So the correct answer is Deep Blue.

Answer 7

\textit{The Emperor’s New Mind} was written by Sir Roger Penrose, a British mathematician and physicist. He was awarded the 2020 Nobel Prize in Physics for his work on black holes and the discovery that black hole formation is a robust prediction of general relativity.

Answer 8

Elimination Approach:
Donna Strickland won the 2018 Nobel Prize in Physics for work on laser pulses, not 2020. Peter Higgs won in 2013 for predicting the Higgs boson. Max Tegmark is a physicist known for his writing on AI and cosmology but has not won a Nobel Prize. Roger Penrose, however, shared the 2020 Nobel Prize in Physics for showing that black hole formation follows from general relativity, and he is also the author of The Emperor's New Mind (1989).

Answer 9

The question asks which British mathematician wrote The Emperor's New Mind and won the 2020 Nobel Prize in Physics. Checking each name against actual Nobel history and authorship settles it.

1. Donna Strickland: She won the Nobel Prize in Physics in 2018 for her work on high-intensity laser pulses, not in 2020, and she did not write this book.
2. Max Tegmark: He is a physicist known for popular writing on AI and cosmology, but he has not won a Nobel Prize.
3. Peter Higgs: He won the Nobel Prize in Physics in 2013 for predicting the Higgs boson, not in 2020.
4. Roger Penrose: He shared the 2020 Nobel Prize in Physics for showing that black hole formation is a robust prediction of general relativity, and he is the author of The Emperor's New Mind, published in 1989.

Only Penrose matches both the book's authorship and the 2020 Nobel Prize.

So the correct answer is Roger Penrose.

Answer 10

A neural network is designed to mimic the behaviour of biological neurons. It consists of interconnected nodes (artificial neurons) that process information through weighted connections, resembling the way the human brain transmits and interprets signals.

Answer 11

Elimination Approach:
Natural language processing deals specifically with understanding and generating human language, not with mimicking neuron signalling in general. Data mining is about discovering patterns in large datasets and has no direct link to brain-like signal exchange. Cognitive computing is a broader umbrella term for systems that simulate human thought, but it is not itself modelled directly on neuron-to-neuron signalling. A neural network is the model built specifically to imitate how neurons pass signals through weighted connections, making it the correct choice.

Answer 12

The question asks which computing model resembles how biological neurons exchange signals in the brain. Checking each option's actual design against this description answers it.

1. Neural network: This model is built from interconnected nodes, artificial neurons, that pass information to each other through weighted connections, directly copying how biological neurons transmit and interpret signals.
2. Cognitive computing: This is a broad umbrella term for systems that try to simulate human thought processes in general, but it is not itself a specific model built on neuron-to-neuron signalling.
3. Natural language processing: This field focuses on understanding and generating human language, and while it may use neural networks internally, the field itself is defined by the language task, not by mimicking brain signalling.
4. Data mining: This is about finding patterns in large datasets, with no direct link to how neurons pass signals.

Only the neural network model is specifically designed around imitating neuron-to-neuron signal exchange.

So the correct answer is Neural network.

Answer 13

LaMDA stands for Language Model for Dialogue Applications, a conversational AI model developed by Google that is optimized for natural, free-flowing dialogue.

Answer 14

Elimination Approach:
Breaking the acronym down letter by letter: 'La' stands for Language, 'M' for Model, 'D' for Dialogue, and 'A' for Applications. None of the other options, Landing Macro Data Applications, Large Model Data Applications, or Last Mile Dialogue Assessment, matches this letter-by-letter decomposition, leaving Language Model for Dialogue Applications as the only fit.

Answer 15

The question asks for the full form of the acronym LaMDA. Breaking the acronym into its letters and checking each option against that breakdown answers it.

1. Landing Macro Data Applications: None of these words match the letters "La", "M", "D", "A" in a way that fits a conversational AI system; "Landing" and "Macro" have no connection to LaMDA's actual purpose.
2. Language Model for Dialogue Applications: "La" stands for Language, "M" for Model, "D" for Dialogue, and "A" for Applications, which matches both the letters and Google's own description of the system as a conversational AI model built for dialogue.
3. Large Model Data Applications: This drops the specific reference to "language" and "dialogue" that defines what LaMDA actually is.
4. Last Mile Dialogue Assessment: While this option does include "Dialogue", the rest of the phrase does not describe a language model at all, and "assessment" is not part of LaMDA's function.

Only the second option correctly decodes each letter of the acronym.

So the correct answer is Language Model for Dialogue Applications.

Answer 16

Meta released a fully trained large language model named OPT (Open Pre-trained Transformer), intended as a more transparent and research-friendly alternative to other large-scale AI models.

Answer 17

Elimination Approach:
FTP, HTTP and SMTP are all internet communication protocols, for file transfer, web browsing, and email respectively, and have nothing to do with AI language models. OPT, short for Open Pre-trained Transformer, is the large language model that Meta released, positioned as a more open alternative to closed models such as GPT-3, making it the correct answer.

Answer 18

The question asks for the name of Meta's fully trained large language AI model. Checking each option against what it actually stands for answers it.

1. FTP: This stands for File Transfer Protocol, an internet standard for moving files between computers, with no connection to AI language models.
2. OPT: This stands for Open Pre-trained Transformer, the large language model Meta released as a more transparent, research-friendly alternative to closed models such as GPT-3.
3. HTTP: This stands for HyperText Transfer Protocol, the basic protocol used for browsing the web, again unrelated to AI models.
4. SMTP: This stands for Simple Mail Transfer Protocol, used for sending email, also unrelated to AI models.

Three of the four options are internet communication protocols, and only OPT refers to an actual AI language model.

So the correct answer is OPT.

Answer 19

The Supreme Court of India launched SUPACE (Supreme Court Portal for Assistance in Courts Efficiency) in April 2021. It is an AI-driven tool designed to assist judges with legal research, case summarization, and efficient handling of judicial data.

Answer 20

Elimination Approach:
GPT-3 is a general-purpose language model built by OpenAI and is unrelated to the Indian judiciary. SURAM is not a recognised official tool of the Supreme Court. E-Courts is a broader, older mission-mode project for digitising court processes, not an AI research assistant launched specifically in 2021. SUPACE, the Supreme Court Portal for Assistance in Courts Efficiency, is the AI-based research tool launched by the Supreme Court of India in April 2021, matching the description exactly.

Answer 21

The question asks for the name of the AI-enabled legal research tool launched by the Supreme Court of India in April 2021. Checking each option against actual judicial IT initiatives answers it.

1. SURAM: This is not a recognised official tool of the Supreme Court of India.
2. GPT-3: This is a general-purpose language model built by OpenAI, unrelated to the Indian judiciary or any court-specific project.
3. SUPACE: Short for Supreme Court Portal for Assistance in Courts Efficiency, this is the AI-driven tool the Supreme Court launched in April 2021 to help judges with legal research, case summarisation, and handling large volumes of case data.
4. E-Courts: This is a broader, older mission-mode project aimed at digitising court processes across India generally, not the specific AI research assistant launched in 2021.

Only SUPACE matches both the description of an AI research assistant and the April 2021 launch date.

So the correct answer is SUPACE.