UGC NET · PAPER 2
UGC NET Paper 2 Computer Science – Unit 10: Artificial Intelligence (AI) PYQ (22 June 2026)
Q63. Consider the following neural network: input x₁ = 0.5 is connected to node A with weight 0.5; input x₂ = 0.6 is connected to node A with weight −0.8; input x₃ = 0.8 is connected to node A with weight 1; node A also receives a bias input of 0.5. Node A computes the net input y_in, which is then passed through node B (the activation function) to produce the final output y.
What will be the net input y_in and final output 'y' of this neural network given that the activation function is a threshold function defined as follows:
f(x) = 1 if x ≥ 1; f(x) = 0 if x < 1
What will be the net input y_in and final output 'y' of this neural network given that the activation function is a threshold function defined as follows:
f(x) = 1 if x ≥ 1; f(x) = 0 if x < 1
- y_in = 2.03, y = 1
- y_in = 1.53, y = 1
- y_in = 1.07, y = 1
- y_in = 0.57, y = 0
Q64. A doctor knows that the disease Meningitis causes a patient to have a stiff neck say 70% of time. The doctor also knows some unconditional facts: the prior probability that any patient has Meningitis is 1/50,000 and the prior probability that any patient has a stiff neck is 1%. Letting s be the proposition that the patient has a stiff neck and m the proposition that the patient has meningitis, compute the probability P(m/s) using Bayes' rule.
- .014
- .0014
- .14
- .00014
Q96. Which of the following deals with the interaction between computers and humans using natural language?
- PROLOG
- ELIZA
- NLP
- LISP
Q132. Classifying email as spam, labeling web pages based on their context, voice recognition are examples of which of the following?
- Reinforcement learning
- Shortest Path Algorithm
- Supervised learning
- Unsupervised learning