Title: Quiz 4 — AI Software Infrastructure
Course: AIINFRA 100: AI Systems & Development Environments > Section: Week 04 — The AI Software Stack: Frameworks, CUDA, Drivers, Model Formats

Q: PyTorch uses eager execution, which means code generally runs line-by-line in a way that feels similar to ordinary Python.
- True
- False
A: True

Q: Which framework is generally recommended in this course as the best starting point for beginners in 2025–2026?
- TensorFlow
- PyTorch
- ONNX
- CUDA
A: PyTorch

Q: What command can you run in a terminal to check the maximum CUDA version your GPU driver supports?
Feedback: Sample/expected answer: `nvidia-smi`

Q: The CUDA version shown by your GPU driver is always guaranteed to exactly match the CUDA Toolkit version installed on your system.
- True
- False
A: False

Q: What is the main problem that Docker containers solve for AI projects?
- They make models train faster on any hardware automatically
- They package code and dependencies together so the environment runs identically across machines
- They automatically grant GPU access inside every container
- They replace the need for a Python interpreter entirely
A: They package code and dependencies together so the environment runs identically across machines

Q: A standard Docker container automatically has full GPU access as soon as Docker is installed, with no extra setup required.
- True
- False
A: False

Q: Which model file format is specifically designed to be safe from arbitrary code execution when loading weights from an untrusted source?
- Pickle-based `.bin`
- GGUF
- safetensors
- ONNX
A: safetensors

Q: Which model format is described as cross-framework and vendor-neutral, storing the computation graph so a model can move from the framework it was trained in to a different deployment environment?
Feedback: Sample/expected answer: ONNX