Which of the following methods scales poorly with large data sets?
Answer(s): C
Hierarchical clustering scales poorly with large datasets because it requires calculating and storing a full distance matrix between all data points, leading to high computational and memory costs. This makes it inefficient and impractical as dataset size grows.
Which of the following trains a predictive model from input data?
Machine learning trains predictive models from input data by identifying patterns and relationships, enabling the system to make predictions or decisions without being explicitly programmed.
What is PowerShell?
PowerShell is a legitimate Windows command-line shell and scripting language used for system administration, but attackers often exploit it as an advanced hacking tool for tasks such as executing malicious scripts, bypassing defenses, and maintaining persistence.
Which of the following ethical challenges is the use of AI MOST likely to present?
Answer(s): A
The use of AI is most likely to present the ethical challenge of bias in content output, since AI systems learn from training data that may reflect existing prejudices or imbalances, leading to biased predictions or decisions.
Which of the following is the MOST significant outcome from flawed program code that is likely to lead to ethical concerns?
Flawed program code can cause AI systems to produce unpredictable outcomes, which is the most significant ethical concern because it directly impacts reliability, trust, and the potential for harmful or unintended consequences.
Which of the following logic types is BEST to use for an AI algorithm that determines whether drivers are stopping for red traffic lights?
Answer(s): B
Determining whether drivers stop for red traffic lights depends on analyzing behavior over time (e.g., vehicle motion as the light changes). Temporal logic is best suited because it evaluates conditions and events in relation to time.
Which of the following is an example of video synthesis?
Video synthesis involves generating or altering video content, and face-swapping is a prime example where AI modifies video frames to replace one person's face with another, creating synthetic media.
Which type of data is MOST commonly augmented using techniques like pitch shifting and time stretching?
Audio data is most commonly augmented using techniques like pitch shifting and time stretching, which alter the frequency or duration of sounds to expand training datasets and improve model robustness.
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