AI Landscape Quiz: Do You Know the Models That Matter?

A small business evaluates an AI tool and discovers it will fine-tune its model using the company's customer data to improve future recommendations. What is the most important consideration before agreeing?

Whether using customer data for model training complies with the business's privacy policy and applicable data protection regulations — and whether customers consented Whether fine-tuning on small business data produces measurably better results Whether the model will be available to the business for download Whether the model improvement will be visible to the business within 30 days

A company builds a prompt library in Notion with 30 useful templates. After 3 months, some templates produce worse results than they used to. What is the most likely cause and solution?

Notion is not a suitable storage tool for prompt templates AI model updates changed behavior — review and update templates when models are upgraded, and record a version history All templates expire after 3 months due to API policy The team is using too many templates — reduce to fewer than 10

Which layer of the AI stack contains products like ChatGPT, Microsoft Copilot, and Perplexity?

The API and platform layer The foundation model layer The training data layer The application layer

A manager asks an AI to recommend which of two job candidates to hire. What is the correct role for AI in this decision?

AI can make the final hiring decision based on the resume data provided AI is too risky to use in any hiring process AI can help structure the evaluation criteria and surface considerations, but the hiring decision should be made by the human hiring manager AI can make the recommendation, but a human must type it into the HR system

What is the primary reason Meta makes its Llama models available as open-source at no charge?

Open-source is required by US government regulation for AI models Meta's Llama models are too weak to sell commercially To establish Llama as the dominant open-source standard, growing Meta's AI ecosystem influence and accelerating research adoption Meta cannot afford to run a paid API service