Generative AI Definition and Key Aspects
The question asks for the best description of Generative AI. Let's analyze the options:
Identifying Generative AI Capabilities
- Option 1: States AI is designed *only* for storing and retrieving data. This is too limited; many AI types do more, and Generative AI specifically focuses on creation.
- Option 2: Describes an AI model that creates new content (text, images, music, code) based on its training data. This accurately defines Generative AI's core function.
- Option 3: Describes AI used *exclusively* for virus detection. This is a specific application (classification/detection) and not the general definition of Generative AI.
- Option 4: Describes a robotic system performing mechanical tasks *without* data processing. Generative AI fundamentally relies on processing vast amounts of data.
Conclusion on Generative AI
Generative AI's primary characteristic is its ability to generate novel content. It learns patterns and structures from existing data (training data) and uses this knowledge to produce new, original outputs. Option 2 precisely captures this definition.
Therefore, the best description is:
An AI model that creates new content such as text, images, music or code based on training data.
Important Questions from Artificial Intelligence - Teaching
- Which one of the following is not matching the broad functionality?
Which of the following languages is suitable for artificial intelligence?
- Which organization developed ChatGPT?
Match the search algorithms to the properties below. Assume finite branching, positive step costs, and admissible heuristics for the A* variants.
List I:
(A) Greedy best-first tree search without cycle checking
(B) Standard A* retaining its search frontier
(C) Recursive best-first search (RBFS)
(D) Simplified memory-bounded A* (SMA*)
List II:
(I) Uses \(O(bd)\) memory, where \(b\) is the branching factor and \(d\) is the maximum retained path depth.
(II) Can be incomplete on a finite state graph because it may repeatedly traverse a cycle.
(III) Finds an optimal solution if sufficient memory can retain an optimal path; otherwise finds the best solution reachable within the memory bound.
(IV) May require exponential time and memory in the worst case.
Choose the correct answer from the options given below.Which of the following statements are true?
(A) Minimax search is breadth-first: it processes all the nodes at a level before moving to a node in next level.
(B) The effectiveness of the alpha-beta pruning is highly dependent on the order in which the states are examined.
(C) The alpha-beta search algorithm computes the same optimal moves as minimax algorithm.
(D) Optimal play in games of imperfact information does not require reasoning about the current and future belief states of each player.
Choose the correct answer from the options given below:
