1. Luke runs a small online clothing shop from his dorm. Last year, he avoided adding AI-based product recommendations because the software was too expensive and slow on his laptop. This year, similar tools are much cheaper and run smoothly using cloud services. He notices that many small sellers like him are now using these features. Which concept best explains why these advanced tools are now widely adopted by small businesses?

• A. Switching costs
• B. Moore's Law
• C. Vertical integration
• D. Capital intensity

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Correct Answer: B
Moore's Law explains how computing power becomes cheaper and more powerful over time, enabling broader adoption of advanced tools like AI. This directly matches the scenario where costs drop and accessibility increases. A is incorrect because switching costs relate to difficulty changing systems, not falling prices. C is incorrect because vertical integration involves ownership of supply chain stages. D is incorrect because capital intensity refers to large upfront investment requirements, which are actually decreasing here.

2. A UT student is building a productivity app for a class project. They choose to build it specifically for iOS because it easily connects with Apple's operating system, database tools, and other apps. Later, they consider switching to Android, but realize they would need to rewrite large parts of the app and adjust how it interacts with other software layers. Which concept BEST explains why switching platforms is so difficult in this situation?

• A. Network effects
• B. Konana's software ecosystem
• C. Price elasticity
• D. Parallel processing

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Correct Answer: B
Konana's software ecosystem explains how different layers (hardware, OS, database, applications) depend on each other, creating strong interconnections. In this case, the app is deeply tied to Apple's ecosystem, making switching difficult. A is incorrect because network effects relate to user growth increasing value. C is incorrect because price elasticity concerns demand changes with price. D is incorrect because parallel processing involves dividing computational tasks, not system compatibility or lock-in.

3. A startup builds a photo-editing app that runs entirely on users' phones. As they add more advanced AI features, users complain that their phones overheat and battery life drops quickly. The company decides to move most of the processing to cloud servers instead. Why does offloading computing to the cloud improve the user experience in this case?

• A. It reduces switching costs for users
• B. It increases network effects across users
• C. It lowers the need for local device processing power
• D. It eliminates the need for an operating system

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Correct Answer: C
Offloading computing to the cloud reduces the burden on local devices, solving issues like overheating and battery drain. This directly matches the scenario. A is incorrect because switching costs are unrelated to performance issues. B is incorrect because network effects depend on user base size, not processing location. D is incorrect because devices still require an operating system to function.

4. A UT student is playing an online multiplayer game. Even though their internet plan has very high Mbps, they still experience lag during gameplay. Their friend with a slower plan has smoother gameplay because their connection responds faster. Which factor is MOST responsible for the lag in this scenario?

• A. Low bandwidth
• B. High latency
• C. Limited storage capacity
• D. Weak parallel processing

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Correct Answer: B
Latency refers to the delay in data transmission, which is critical in real-time applications like gaming. The student's high bandwidth but poor responsiveness indicates high latency. A is incorrect because bandwidth relates to total data capacity, not delay. C is incorrect because storage does not affect real-time communication. D is incorrect because parallel processing relates to computation, not network performance.

5. A student team is training a machine learning model for a class project. They first try using a standard laptop CPU, but training takes hours. When they switch to an NVIDIA GPU through a cloud service, the same model trains in minutes. Which concept BEST explains why the GPU performs better in this situation?

• A. It uses fewer transistors per chip
• B. It relies on higher switching costs
• C. It is optimized for sequential processing
• D. It is designed for parallel processing

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Correct Answer: D
NVIDIA GPUs are designed for parallel processing, allowing them to handle many computations at once, which is ideal for machine learning tasks. This directly explains the performance improvement. A is incorrect because GPUs typically have more transistors, not fewer. B is incorrect because switching costs are unrelated to performance. C is incorrect because GPUs excel at parallel, not sequential, processing.