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A life-sciences research team wants to use AI to simulate new drug compounds by analyzing patterns in molecular structures. What is a core benefit of AWS for this generative-AI use case?
A
AWS automatically validates all molecular results
B
AWS offers scalable compute, security, and managed AI tools for experimentation
C
AWS guarantees model fairness for all compounds
D
AWS replaces lab researchers with AI agents
Explanation:
Correct Answer: B - AWS offers scalable compute, security, and managed AI tools for experimentation
Why this is correct:
Scalable Compute: AWS provides elastic computing resources that can scale up or down based on the computational needs of molecular structure analysis and drug compound simulation, which can be computationally intensive.
Security: AWS offers robust security features and compliance frameworks that are crucial for handling sensitive research data in life sciences.
Managed AI Tools: AWS provides managed AI/ML services like Amazon SageMaker, which simplifies the process of building, training, and deploying machine learning models for drug discovery without requiring deep infrastructure expertise.
Experimentation Support: AWS enables researchers to experiment with different AI models and approaches quickly and cost-effectively.
Why other options are incorrect:
Key AWS Services for this use case: