A pharmaceutical company wants to implement AI to accelerate drug discovery. What critical factors should be considered to ensure the AI model effectively identifies potential drug candidates?
- Use AI models that are black-box and hard to interpret.
- Focus solely on historical data and ignore new research.
- Incorporate domain expertise, high-quality data, and interpretability into the AI model.
- Rely solely on automation without human oversight.
Option C is the correct choice because incorporating domain expertise, high-quality data, and interpretability into the AI model are critical factors for effectively identifying potential drug candidates.
What is the primary goal of AI?
- To create expert systems.
- To increase processing speed.
- To make machines learn from experience.
- To replace human tasks.
The primary goal of AI is to enable machines to learn from experience, adapt to new inputs, and perform human-like tasks. While it might be used in expert systems, or might replace some human tasks, the core aim is for machines to simulate human intelligence and improve over time.
What is the role of sensors in robotic automation?
- Sensors control the robot's movement.
- Sensors detect and respond to the environment.
- Sensors enable robots to think.
- Sensors provide power to robots.
Sensors in robotic automation play a crucial role in detecting and responding to the environment. They collect data about the robot's surroundings, enabling it to make decisions, avoid obstacles, and interact with its surroundings effectively.
What does "swarm robotics" refer to?
- A group of robots that communicate and coordinate their actions to accomplish tasks collectively.
- A robot that can move at high speeds.
- A type of insect-like robot.
- The use of drones for surveillance.
"Swarm robotics" refers to a field of robotics where a group of robots works together in a coordinated and decentralized manner to achieve a common goal. They communicate and collaborate without a central controller, inspired by the behavior of social insects like ants or bees.
In a scenario where an AI deployed in financial trading starts making highly risky trades due to a data anomaly, how would you design a system to prevent this in the future while maintaining the ability to capitalize on legitimate opportunities?
- Disable the AI system and rely solely on human traders.
- Implement strict trading limits for the AI and increase human oversight.
- Allow the AI to continue risky trading to maximize profits.
- Ignore the anomaly, as it may be a temporary issue.
To prevent risky trading while capitalizing on legitimate opportunities, you should increase human oversight, implement strict limits, and develop algorithms to detect and react to anomalies. Balancing risk and reward is essential in financial AI systems.
Which of the following applications is typically not associated with NLP?
- Sentiment analysis of social media posts.
- Language translation.
- Weather forecasting.
- Virtual personal assistants.
Weather forecasting is typically not associated with NLP. While NLP is essential in understanding and processing human language, weather forecasting relies on meteorological data and scientific models to predict weather conditions.
The principle of "_______" refers to the ethical guideline that AI systems should be transparent and explainable.
- Accountability
- Inscrutability
- Opacity
- Transparency
The principle of "Transparency" in AI ethics emphasizes that AI systems should be designed in a way that their decisions and operations can be understood and explained by humans. This promotes trust and accountability in AI systems.
Developing AI systems that can effectively handle _______ learning is crucial for adapting to dynamic environments with non-stationary data distributions.
- Lifelong
- Reinforcement
- Supervised
- Unsupervised
Developing AI systems capable of Lifelong Learning is crucial for adapting to dynamic environments with non-stationary data distributions. Lifelong learning allows systems to continuously acquire knowledge and adapt to new tasks and data distributions over time.
Which algorithm is least likely to be used in a real-time bidding (RTB) system in programmatic advertising?
- Decision Trees
- K-Means Clustering
- Logistic Regression
- Reinforcement Learning
Reinforcement Learning is the least likely to be used in real-time bidding (RTB) systems in programmatic advertising. RTB systems require rapid decision-making based on historical data and current conditions, which doesn't align with the training process of reinforcement learning.
Which of the following is not a primary function of robots in manufacturing automation?
- Assembling products.
- Cooking food.
- Handling materials.
- Welding components.
Cooking food is not a primary function of robots in manufacturing automation. Robots in manufacturing are typically used for tasks such as assembling products, welding components, and handling materials to improve efficiency and precision in industrial processes.